Fibro-check: a combination of direct and indirect markers for liver fibrosis staging in chronic hepatitis C patients

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Attallah, Mohamed El-Far, Camelia A. Abdel Malak, Mohamed M. Omran, Khaled Farid, Mostafa A. Hussien, Mohamed S. Albannan, Ahmed A. Attallah, Mohamed S. Elbendary, Dalia A. Elbesh, Noha A. Elmenier, Mohamed O. Abdallah" "autores" => array:12 [ 0 => array:4 [ "nombre" => "Abdelfattah M." "apellidos" => "Attallah" "email" => array:1 [ 0 => "amattallah@hotmail.com" ] "referencia" => array:2 [ 0 => array:2 [ "etiqueta" => "*" "identificador" => "aff0005" ] 1 => array:2 [ "etiqueta" => "*" "identificador" => "cor0005" ] ] ] 1 => array:3 [ "nombre" => "Mohamed" "apellidos" => "El-Far" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "†" "identificador" => "aff0010" ] ] ] 2 => array:3 [ "nombre" => "Camelia A. Abdel" "apellidos" => "Malak" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "‡" "identificador" => "aff0015" ] ] ] 3 => array:3 [ "nombre" => "Mohamed M." 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"apellidos" => "Elbesh" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "*" "identificador" => "aff0005" ] ] ] 10 => array:3 [ "nombre" => "Noha A." "apellidos" => "Elmenier" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "*" "identificador" => "aff0005" ] ] ] 11 => array:3 [ "nombre" => "Mohamed O." "apellidos" => "Abdallah" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "*" "identificador" => "aff0005" ] ] ] ] "afiliaciones" => array:6 [ 0 => array:3 [ "entidad" => "Research & Development Department, Biotechnology Research Center, New Damietta City, Egypt" "etiqueta" => "*" "identificador" => "aff0005" ] 1 => array:3 [ "entidad" => "Faculty of Science, Mansoura University, Mansoura, Egypt" "etiqueta" => "†" "identificador" => "aff0010" ] 2 => array:3 [ "entidad" => "Faculty of Science, Damietta University, New Damietta, Egypt" "etiqueta" => "‡" "identificador" => "aff0015" ] 3 => array:3 [ "entidad" => "Faculty of Science, Helwan University, Cairo, Egypt" "etiqueta" => "§" "identificador" => "aff0020" ] 4 => array:3 [ "entidad" => "Tropical Medicine Department, Faculty of Medicine, Mansoura University, Mansoura, Egypt" "etiqueta" => "||" "identificador" => "aff0025" ] 5 => array:3 [ "entidad" => "Faculty of Science, Port-Said University, Port-Said, Egypt" "etiqueta" => "¶" "identificador" => "aff0030" ] ] "correspondencia" => array:1 [ 0 => array:3 [ "identificador" => "cor0005" "etiqueta" => "*" "correspondencia" => "Correspondence and reprint request:" ] ] ] ] "resumenGrafico" => array:2 [ "original" => 0 "multimedia" => array:7 [ "identificador" => "f0010" "etiqueta" => "Figure 2" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr2.jpeg" "Alto" => 824 "Ancho" => 451 "Tamanyo" => 43299 ] ] "descripcion" => array:1 [ "en" => "Area under the ROC curve for Fibro-check and comparison with APRI and Fibrosis index for predicting (A) significant fibrosis, (B) cirrhosis in chronic hepatitis C patients in the estimation study (n = 168). Calculations for Fibro-check, APRI and fibrosis index are shown in <a class="elsevierStyleCrossRef" href="#t0015">table 3</a>." ] ] ] "textoCompleto" => "IntroductionHepatitis C virus (HCV) infection is a global health burden affecting approximately 160-170 million people worldwide.<a class="elsevierStyleCrossRef" href="#bib0005">1</a> Once chronic HCV infection is established, spontaneous HCV clearance rarely occurs. Chronic hepatitis C (CHC) can cause continuous liver damage resulting in liver cirrhosis and subsequently hepatocellular carcinoma (HCC).<a class="elsevierStyleCrossRef" href="#bib0010">2</a> Staging of liver fibrosis is necessary in CHC patients because it is the important factor for initiation of treatment in patients with hepatitis C infection.<a class="elsevierStyleCrossRef" href="#bib0015">3</a> Liver biopsy is the most commonly used reference standard for assessing liver fibrosis. However, liver biopsy is an invasive and is associated with a significant risk of complications ranged from minor complications like pain and transient hypotension to major complications like significant bleeding which may cause death.<a class="elsevierStyleCrossRef" href="#bib0020">4</a> These limitations have stimulated the development of non-invasive techniques for assessing the presence and the degree of liver fibrosis. The great majority of studies have investigated the diagnostic value of serum markers of liver fibrosis. These markers were divided into two categories; direct markers, which are supposed to be directly involved in the deposition and removal of extracellular matrix (ECM), i.e. in fibrogenesis and fibrolysis and indirect markers, which reflect alterations in hepatic function, but not directly ECM metabolism.<a class="elsevierStyleCrossRef" href="#bib0025">5</a> Fibrosis is characterized by the deposition of collagen and other extracellular matrix proteins and their organization in complex polymers, which are insoluble and induce loss of the liver architecture.<a class="elsevierStyleCrossRef" href="#bib0030">6</a> Collagen is synthesized as a procollagen by hepatic stellate cells (HSCs), later it is transformed to collagen by enzymatic splitting of the C-terminal and N-terminal end by procollagen C-proteinase and procollagen N-proteinase.<a class="elsevierStyleCrossRef" href="#bib0035">7</a> Matrix metalloproteinases are the main degrading enzyme of these ECM proteins, and have been implicated in the processes of liver fibrosis. Among them, the matrix metalloproteinase-1 (MMP-1) that cleaves the native helix of fibrillar collagens I, II and III.<a class="elsevierStyleCrossRef" href="#bib0040">8</a> Herein, we aimed to determine the expression of collagen III and its degrading enzyme MMP-1 simultaneously and then estimating their performances as surrogate markers for liver fibrosis diagnosis. Furthermore, we aimed to develop a sensitive function incorporated both collagen III and its degrading enzyme MMP-1 together with other indirect markers which reflect alteration in hepatic function for liver fibrosis staging in CHC patients and then estimated its performance in comparison with some published noninvasive tests in CHC.<a class="elsevierStyleCrossRef" href="#bib0045">9</a>,<a class="elsevierStyleCrossRef" href="#bib0050">10</a>Materials and MethodsSamplesBlood samples and liver biopsies of two hundred sixty-nine HCV infected individuals were collected from the Tropical Medicine department, Mansoura University hospitals, Mansoura, Egypt. One hundred sixty-eight patients constituted the estimation group whereas 101 patients constituted the validation group. All tissue and serum samples were obtained with informed consent. All patients were tested negative for HBsAg (Dia.Pro, Milan, Italy). Also, all patients were tested positive for anti-HCV antibodies (Biomedica, Sorin, Italy). Patients were then confirmed for the presence of HCV-RNA using quantitative polymerase chain reaction assay (COBAS Ampliprep/ COBAS TaqMan, Roche Diagnostics, Pleasanton, USA). Cirrhotic patients were compensated at the time of inclusion. Patients with an evidence of coexistent liver disease, a history of hepatocellular carcinoma, a previous interferon treatment and a decompensated liver disease were excluded from this study. Needle liver biopsy specimens were obtained with an 18-gauge or larger needle. To be considered as adequate for scoring, the liver biopsies had to measure at least 15 mm and/or contain at least five portal tracts, except for cirrhosis for which no limitation was required. Biopsies were interpreted according to METAVIR scoring system.<a class="elsevierStyleCrossRef" href="#bib0055">11</a> Liver function tests [albumin, total bilirubin, aspartate aminotransferase (AST), alanine aminotransferase (ALT) and alkaline phosphatase (ALP)] were all measured on an automated biochemistry analyzer (Hitachi 917; Roche Diagnostics, Mannheim, Germany). Complete blood count was performed using KX-21 Sysmex automated hematology analyzer (Sysmex Corporation, Kobe, Japan). Alpha fetoprotein (AFP) level was estimated by chemiluminescence, with Immulite (1000) AFP kit (Diagnostic Products Corporation; Los Angeles, CA, USA).Western blotting and gel electroelutionFirst, sodium dodecyl sulfate-polyacrylamide gel electrophoresis was carried out in 0.75 mm-thick, 12% vertical slab gels according to the method of Laemmli.<a class="elsevierStyleCrossRef" href="#bib0060">12</a> Next, Western electroblotting was used for transferring the separated protein bands onto a nitrocellulose membrane (0.45 mm pore size, Sigma) in a protein transfer unit according to Towbin, et al.<a class="elsevierStyleCrossRef" href="#bib0065">13</a> Then, they were immunostained using monospecific antibodies corresponding to human collagen type III and MMP-1 separately. Finally, both collagen III and MMP-1 bands were cut and electroeluted separately from preparative polyacrylamide gels at 200 V for 3 h in a dialysis bag (Sigma). The protein content of the purified bands was determined<a class="elsevierStyleCrossRef" href="#bib0070">14</a> and the remainder was stored at -20 °C.Quantitation of collagen III and MMP-1 using ELISADiluted serum samples (1:50) in coating buffer (50 mM carbonate/bicarbonate buffer, pH 9.6) were tested (50 μL/well) for collagen III bound on a 96-well microtiter plate at 4 °C overnight. After blocking with 0.5% BSA in coating buffer (200 μL/well), mono-specific antibody for collagen III at dilution 1:200 in PBS was added (50 μL/well) and incubated at 37 °C for 2 h. Goat anti-rabbit antibody conjugated with alkaline phosphatase (Sigma) 1:700 in 0.2% BSA in PBS-T20 was incubated at 37 °C for 1 h. Similarly, diluted serum samples (1:50) in coating buffer were tested (50 μL/well) for MMP-1 bound on a 96-well microtiter plate at 4 °C overnight. Likewise, after blocking with 0.6% BSA in coating buffer (200 μL/well), mono-specific antibody for MMP-1 at dilution 1:500 in PBS was added (50 μL/well) and incubated at 37 °C for 2 h. Also, goat anti-rabbit antibody conjugated with alkaline phosphatase (Sigma) 1:500 in 0.2% BSA in PBS-T20 was incubated at 37 °C for 1 h. The plates were washed with PBS+0.5% Tween 20 after every step. The substrate was 1 mg/ mL p-nitrophenyl phosphate and the intensity of the signal was determined by measuring the absorbance at 450 nm after 10 minutes using a microtiter plate reader (Σ960, Metretech Inc, Germany). The calibration curves of the serial concentrations for the purified Collagen III (0.1-30 μg/mL) and MMP-1 (0.5-24 μg/mL) were then determined.Statistical analysisAll statistical calculations were done by SPSS software v.15.0 (SPSS Inc., Chicago, IL) and Graph-Pad Prism package; v.5.0 (GraphPad Software, San Diego, CA). Continuous variables were expressed as mean ± standard error of mean. A value of P < 0.05 was considered statistically significant. There were 2 endpoints in this study: presence of significant fibrosis and cirrhosis. The correlation was evaluated by Spearman’s rank correlation coefficient. Univariate analysis identified the predictors of fibrosis by using the Student’s t test. The diagnostic value was assessed by calculating the area under the receiver operating characteristic (ROC) curves. An area under the curve (AUC) of 1.0 is characteristic of an ideal test, whereas 0.5 indicates a test of no diagnostic value. All variables with high AUCs and high significance on univariate analysis were entered in stepwise linear regression analysis to develop a model for identifying significant fibrosis. Based on the ROC analysis, the best cutoff points were selected and diagnostic performances (sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV)) were determined.ResultsPatient characteristicsOne hundred sixty-eight HCV-monoinfected patients fulfilled the selection criteria. The sample comprised one hundred and eleven men and fifty-seven women. Laboratory characteristics of all patients at the time of liver biopsy are summarized in <a class="elsevierStyleCrossRef" href="#t0005">table 1</a>. Comparison of the baseline characteristics of patients according to the stage of liver fibrosis are outlined in <a class="elsevierStyleCrossRef" href="#t0010">table 2</a>. As individuals with significant fibrosis (F2-F4) are at increased risk of developing cirrhosis and are usually accepted as an indication to commence treatment, the laboratory features of patients with minimal fibrosis (F1) and F2-F4 were compared by univariate analysis based on the Student’s t test. As a result, patients with F1 were young with a mean (± SEM) of 40.2 (± 0.9) years as compared to those who developed F2-F4. Moreover, patients with F2-F4 were associated with higher AST, ALT, AAR, ALP, APRI and AFP levels than those with F1. On contrary, the mean value of albumin and platelet count decreased with the progression of liver fibrosis being lower in patients who developed F2-F4 (<a class="elsevierStyleCrossRef" href="#t0010">Table 2</a>).<elsevierMultimedia ident="t0005"></elsevierMultimedia><elsevierMultimedia ident="t0010"></elsevierMultimedia>Identification and quantitation of collagen III and MMP-1SDS-PAGE and Western blotting were used as described previously to identify the target collagen III and its degrading enzyme MMP-1. As a result, a single immunoreactive band was shown at 70 kDa and 245 kDa for collagen type III and MMP-1, respectively, due to their binding with their respective mono-specific antibodies. Patients with significant fibrosis (F2-F4) were associated with higher concentration of collagen III than those with minimal fibrosis (F1). On the other hand, patients with F2-F4 were associated with lower concentration of MMP-1 than those with F1 (as shown in <a class="elsevierStyleCrossRef" href="#t0010">table 2</a>). The use of collagen III per se could discriminate F2-F4 from F1 with an AUC = 0.75 while the use of MMP-1 per se yielded an AUC = 0.70 for identifying F2-F4 (<a class="elsevierStyleCrossRef" href="#f0005">Figures 1</a>A, 1B). Surprisingly, it has been observed that collagen III/MMP-1 ratio (CMR) yielded values that increased significantly in patients with F2-F4 vs. those with F1 (<a class="elsevierStyleCrossRef" href="#t0010">Table 2</a>) and identified F2-F4 with a better AUC = 0.80 than each marker separately (<a class="elsevierStyleCrossRef" href="#f0005">Figure 1</a>C). Hence, the overlap in collagen III and MMP-1 among patients with F1 and F2-F4 has been diminished and the difference in their value has been amplified. Then, based on ROC curve, a cutoff point greater than 2.5 was selected for CMR for separating patients with F2-F4 from those with F1 yielding a sensitivity of 77% and specificity of 71%.<elsevierMultimedia ident="f0005"></elsevierMultimedia>Development of the Fibro-checkThe next step was aimed to enhance the diagnostic accuracy of CMR for diagnosing F2-F4. So, it is necessary for this ratio to be combined with other routine marker. On univariate analysis, nine of the ten evaluated routine markers included in this study showed a significant association with fibrosis stages F2-F4 (P < 0.05). They were age, AAR, albumin, total bilirubin, platelet count, APRI, AFP, AST and ALP. Serum ALT did not differentiate between F1 and F2-F4 (P > 0.05) as presented in <a class="elsevierStyleCrossRef" href="#t0010">table 2</a>. However, multivariate regression modeling demonstrated that only AAR, platelet count, and AFP together with CMR retained significance when combined with each other. Thus, CMR, AFP, AAR and platelet count were selected as the best combination for diagnosing F2-F4. Then, we put the positive correlation parameters (CMR, AAR and AFP) in the numerator and the negative correlation parameters (platelet count) in the denominator to formulate the following function (<a class="elsevierStyleCrossRef" href="#t0015">Table 3</a>):<elsevierMultimedia ident="f005"></elsevierMultimedia><elsevierMultimedia ident="t0015"></elsevierMultimedia>Diagnostic performance of Fibro-checkThe diagnostic value of Fibro-check was then assessed by calculating the area under the ROC curve that showed a superior AUC of 0.91 for identifying F2-F4. Next, an optimal cutoff point of 0.05 was selected based on the ROC curve analysis. For Fibro-check greater than 0.05, 65 out of 79 (82% PPV) would have significant fibrosis and only 14 of 89 without significant fibrosis would be classified falsely. At this cutoff point, significant fibrosis could be excluded with 84% NPV i.e., 16% of patients with Fibro-check less than 0.05 had significant fibrosis. Furthermore, the effectiveness of Fibro-check in predicting cirrhosis was then preformed using ROC curve producing an AUC of 0.83 lower than that produced in identifying significant fibrosis. An optimal cutoff point of 0.1 was selected based on the ROC curve analysis. At this cutoff point, Fibro-check had sensitivity of 74% with PPV of 45% and specificity of 77% with a NPV of 92% for predicting cirrhosis i.e. 8% of patients with Fibro-check value less than 0.1 had cirrhosis (<a class="elsevierStyleCrossRef" href="#t0020">Table 4</a>).<elsevierMultimedia ident="t0020"></elsevierMultimedia>Performance of Fibro-check in comparison with APRI and fibrosis indexNext, our results were compared with those of the previous reports,<a class="elsevierStyleCrossRef" href="#bib0045">9</a>,<a class="elsevierStyleCrossRef" href="#bib0050">10</a> ROC curves of APRI<a class="elsevierStyleCrossRef" href="#bib0045">9</a> and fibrosis index<a class="elsevierStyleCrossRef" href="#bib0050">10</a> (their calculations are shown in <a class="elsevierStyleCrossRef" href="#t0015">table 3</a>) vs. Fibro-check were constructed and superimposed to determine which score would have the most clinical utility to predict significant fibrosis as displayed in <a class="elsevierStyleCrossRef" href="#f0010">figure 2</a>A. The AUC using the procedure described by Hanley and McNeil<a class="elsevierStyleCrossRef" href="#bib0075">15</a> was better for Fibro-check (AUC = 0.91) than fibrosis index (AUC = 0.73) followed by APRI (AUC = 0.69). Next, ROC curves were also constructed and superimposed to determine which score would have the most clinical utility in predicting cirrhosis. The AUC was higher for Fibro-check (AUC = 0.83) than fibrosis index (AUC = 0.79) followed by APRI (AUC = 0.68) as displayed in <a class="elsevierStyleCrossRef" href="#f0010">figure 2</a>.B. Additionally, the sensitivity, specificity, PPV and NPV for these fibrosis tests were calculated using cutoff values exactly as originally described by their authors<a class="elsevierStyleCrossRef" href="#bib0045">9</a>,<a class="elsevierStyleCrossRef" href="#bib0050">10</a> which were not found to be optimal as shown in <a class="elsevierStyleCrossRef" href="#t0020">table 4</a>. Moreover, Bivariate Spearman’s rank correlation coefficient (r) was calculated to measure the relationship between these aforementioned tests and the METAVIR fibrosis score. As a result, Fibro-check significantly correlated with liver fibrosis stages with a better correlation coefficient (r = 0.70, P < 0.0001) than those produced by APRI (r = 0.34, P < 0.0001) and fibrosis index (r = 0.43, P < 0.0001). Then, the diagnostic performances of Fibro-check in discriminating F1 from F2-F3, F1 from F4 and F2-F3 from F4 were evaluated and presented in <a class="elsevierStyleCrossRef" href="#t0025">table 5</a>.<elsevierMultimedia ident="f0010"></elsevierMultimedia><elsevierMultimedia ident="t0025"></elsevierMultimedia>Validation studyThe Fibro-check was then applied to a validation cohort comprising one hundred and one patients to test its accuracy and reproducibility. The characteristics of the validation group were similar to that of the estimation group with no significant differences in any of the assessed variables (<a class="elsevierStyleCrossRef" href="#t0005">Table 1</a>). The Fibro-check significantly correlated with liver fibrosis stages (r = 0.60, P < 0.0001). The diagnostic power of Fibro-check was assessed in the validation group by ROC curve showing AUCs of 0.90 and 0.86 for identifying significant fibrosis and cirrhosis, respectively. At cutoff point > 0.05, Fibro-check produced 80% sensitivity with 83% PPV and 86% specificity with 82% NPV for identifying significant fibrosis. At cutoff point > 0.1, Fibro-check produced 80% sensitivity with 50% PPV and 78% specificity with 93% NPV for identifying cirrhosis. Additionally, the diagnostic performances of Fibro-check in separating between F1, F2-F3 and F4 were validated as seen in <a class="elsevierStyleCrossRef" href="#t0025">table 5</a>.DiscussionIt is worthy noting that serum levels of proteins directly related to the hepatic fibrogenic process could be used as surrogate markers of liver fibrosis.<a class="elsevierStyleCrossRef" href="#bib0080">16</a> They reflect the greater deposition of ECM in the liver due to either increased synthesis by activated stellate cells or slow removal by Kupffer and endothelial sinusoidal cells.<a class="elsevierStyleCrossRef" href="#bib0085">17</a> These tests include measures of hepatic metabolic activity, extracellular matrix remodeling proteins, collagen synthesis and degradation products, and enzymes involved in matrix degradation. Collagen is considered to be the main component of connective tissue, and is the most abundant protein in mammals.<a class="elsevierStyleCrossRef" href="#bib0090">18</a> Of the many collagen subtypes described, only five have been detected in liver; they are types I, III, IV, V and VI.<a class="elsevierStyleCrossRef" href="#bib0095">19</a>Extracellular degradation of matrix proteins is regulated by a family of zinc-dependent neutral proteases called the matrix metalloproteinases (MMPs). These MMPs are subdivided into 3 groups; collagenases that have a role in degrading and denaturing interstitial collagens (types I, II and III), type IV collagenases/gelatinases that degrade basement membrane (type IV) collagen and gelatins as well as stromelysins that degrade fibronectin, gelatins, proteoglycans and laminin.<a class="elsevierStyleCrossRef" href="#bib0100">20</a> There is a relatively large literature suggesting that MMP activity in liver decreases as fibrosis progresses. Decreased activity of ECM-removing MMPs is mainly due to an overexpression of their specific inhibitors (TIMPs) <a class="elsevierStyleCrossRef" href="#bib0105">(21)</a>. Interstitial collagenase “MMP-1” is one of these MMPs which cleaves the native helix of fibrillar collagens types I, II and III, specifically at a single site into one-quarter and three-quarter products; these are susceptible to further degradation by other proteinases.<a class="elsevierStyleCrossRef" href="#bib0040">8</a>Therefore, this work was concerned with the identification and quantitative determination of both collagen III and MMP-1 and then estimating their performances as surrogate markers for accurate diagnosis of liver fibrosis. Our results showed that patients with F2-F4 were associated with higher collagen III concentration than that observed in patients with F1 with extremely significant difference yielding AUC = 0.75 for diagnosing F2-F4. The latter result may be explained by the fact that ECM is a highly dynamic substratum with a precisely regulated balance between synthesis and degradation. But upon injury, the HSCs become activated and secrete large amounts of ECM. Consequently, ECM production exceeds ECM degradation, and hepatic fibrosis develops as a result of the progressive thickening of fibrotic septae and chemical cross-linking of collagen.<a class="elsevierStyleCrossRef" href="#bib0110">22</a>On contrary, the mean value of MMP-1 concentration decreased with the progression of liver fibrosis being lower in patients who developed F2-F4 than those with F1 with extremely significant difference yielding AUC = 0.70 for identifying F2-F4. The decreased activity of ECM-removing MMPs may be explained by the fact that TIMPs are co-expressed with MMPs and contribute to the regulation of local metalloproteinase activity. An increased hepatic TIMP expression may thus account for reduced metalloproteinase activity and is thought to be important for hepatic fibroproliferation.<a class="elsevierStyleCrossRef" href="#bib0115">23</a>In order to amplify the difference in collagen III and MMP-1 values among patients with F1 and F2-F4 and increase their aptitude, collagen III/MMP-1 ratio was devised that showed a better AUC = 0.80 than that produced by each individually. Indeed, it was necessary for collagen III/MMP-1 ratio to be combined with other variables to improve its diagnostic ability for F2-F4 diagnosis. In this work, patients with F2-F4 were found to have significant lower platelet count than that observed in patients with F1. The decreased level of platelet count could be interpreted by the fact that hepatic fibrosis may cause thrombocytopenia as a consequence of impaired synthesis of thrombopoietin and/or sequestering of platelets in an enlarged spleen. Many studies supported that platelet count alone may be clinically valuable as a noninvasive marker for liver fibrosis and cirrhosis.<a class="elsevierStyleCrossRef" href="#bib0120">24</a>,<a class="elsevierStyleCrossRef" href="#bib0125">25</a> Ono, et al.<a class="elsevierStyleCrossRef" href="#bib0130">26</a> has reported that platelet count alone could discriminate F4 from F1-F3 in 75-80% of CHC patients. Consequently, platelet count was identified as a significant predictor of fibrosis.On the other hand, the clinical use of AAR in the diagnostic workup of patients with chronic liver disease is supported by studies conducted in several countries.<a class="elsevierStyleCrossRef" href="#bib0135">27</a> AAR has been reported as a surrogate marker of liver fibrosis with values greater than one being suggestive of cirrhosis.<a class="elsevierStyleCrossRef" href="#bib0140">28</a> That’s because of the increased release of mitochondrial AST, the decreased clearance of AST and/or impaired synthesis of ALT in advanced stages of liver disease.<a class="elsevierStyleCrossRef" href="#bib0145">29</a> With regard to AFP, it is an important marker in diagnosing HCC. However, elevated AFP level has also been observed in chronic hepatitis C patients.<a class="elsevierStyleCrossRef" href="#bib0150">30</a>As a consequence of these analyses, a discriminant function called Fibro-check composed of collagen III, MMP-1 together with platelet count, AAR and AFP was created. The diagnostic value of Fibro-check was then assessed by the ROC curve giving 0.91 AUC for identifying F2-F4 and 0.83 AUC for identifying F4. The present work was concerned with identifying the presence of F2-F4 and F4. That is because the presence of F2-F4 is accepted as an indication to commence treatment<a class="elsevierStyleCrossRef" href="#bib0155">31</a>,<a class="elsevierStyleCrossRef" href="#bib0160">32</a> and the presence of F4 also has implications regarding screening for HCC.<a class="elsevierStyleCrossRef" href="#bib0165">33</a>Next, we evaluated the diagnostic accuracies of some non-invasive scores for assessing the degree of liver fibrosis in comparison with our developed score in our study group. Among these, APRI<a class="elsevierStyleCrossRef" href="#bib0045">9</a> and fibrosis index.<a class="elsevierStyleCrossRef" href="#bib0050">10</a> Diagnostic accuracies for these aforementioned scores were evaluated using categories and cutoff values exactly as originally described which were not found to be optimal and had AUCs lower than those reported previously by their authors in their original study. These discrepancies may be related to differences in the prevalence of F2-F4 and F4. Also, they may be related to differences in the patient characteristics and the histopathological assessment. It is worthy noting that in Egypt, patient delay seeking medical care until symptoms get worsen that explain the lack of patient with F0 from our study population. We acknowledge that there is a limitation to the clinical use of MMP-1 and collagen III because they are not routinely available in all hospital settings.Finally, we evaluated whether the predictive criteria identified in the estimation study were able to reproduce their predictive ability in a subsequent different, but related group of patients. In conclusion, we showed that a five-marker model combining collagen III, MMP-1 together with platelet count, AAR and AFP may improve liver fibrosis staging with a high degree of accuracy and seems more efficient than APRI and fibrosis index in our hands. Further prospective studies involving a greater number of patients are warranted to validate the usefulness of the produced score in clinical practice.Abbreviations<ul class="elsevierStyleList" id="l0005"><li class="elsevierStyleListItem" id="u0005">•AAR: AST/ ALT ratio.</li><li class="elsevierStyleListItem" id="u0010">•ALT: alanine aminotransferase.</li><li class="elsevierStyleListItem" id="u0015">•ALP: alkaline phosphatase.</li><li class="elsevierStyleListItem" id="u0020">•APRI: aspartate to platelet ratio index.</li><li class="elsevierStyleListItem" id="u0025">•AST: aspartate aminotransferase.</li><li class="elsevierStyleListItem" id="u0030">•AFP: alpha fetoprotein.</li><li class="elsevierStyleListItem" id="u0035">•CHC: chronic hepatitis C.</li><li class="elsevierStyleListItem" id="u0040">•CMR: collagen III/ Matrix metalloproteinase-1 ratio.</li><li class="elsevierStyleListItem" id="u0045">•ECM: extracellular matrix.</li><li class="elsevierStyleListItem" id="u0050">•HCC: hepatocellular carcinoma.</li><li class="elsevierStyleListItem" id="u0055">•HCV: hepatitis C virus.</li><li class="elsevierStyleListItem" id="u0060">•MMP-1: matrix metalloproteinase-1.</li></ul>Conflict of InterestThe authors declared that there is no conflict of interest.AcknowledgementsThis study has been completely supported financially and carried out at Biotechnology Research Center, New Damietta, Egypt." "textoCompletoSecciones" => array:1 [ "secciones" => array:10 [ 0 => array:3 [ "identificador" => "xres1198582" "titulo" => "Abstract" "secciones" => array:1 [ 0 => array:1 [ "identificador" => "abs0010" ] ] ] 1 => array:2 [ "identificador" => "xpalclavsec1117076" "titulo" => "Keywords" ] 2 => array:2 [ "identificador" => "s0005" "titulo" => "Introduction" ] 3 => array:3 [ "identificador" => "s0010" "titulo" => "Materials and Methods" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "s0015" "titulo" => "Samples" ] 1 => array:2 [ "identificador" => "s0020" "titulo" => "Western blotting and gel electroelution" ] 2 => array:2 [ "identificador" => "s0025" "titulo" => "Quantitation of collagen III and MMP-1 using ELISA" ] 3 => array:2 [ "identificador" => "s0030" "titulo" => "Statistical analysis" ] ] ] 4 => array:3 [ "identificador" => "s0035" "titulo" => "Results" "secciones" => array:6 [ 0 => array:2 [ "identificador" => "s0040" "titulo" => "Patient characteristics" ] 1 => array:2 [ "identificador" => "s0045" "titulo" => "Identification and quantitation of collagen III and MMP-1" ] 2 => array:2 [ "identificador" => "s0050" "titulo" => "Development of the Fibro-check" ] 3 => array:2 [ "identificador" => "s0055" "titulo" => "Diagnostic performance of Fibro-check" ] 4 => array:2 [ "identificador" => "s0060" "titulo" => "Performance of Fibro-check in comparison with APRI and fibrosis index" ] 5 => array:2 [ "identificador" => "s0065" "titulo" => "Validation study" ] ] ] 5 => array:2 [ "identificador" => "s0070" "titulo" => "Discussion" ] 6 => array:2 [ "identificador" => "s0075" "titulo" => "Abbreviations" ] 7 => array:2 [ "identificador" => "s0080" "titulo" => "Conflict of Interest" ] 8 => array:2 [ "identificador" => "s0085" "titulo" => "Acknowledgements" ] 9 => array:1 [ "titulo" => "References" ] ] ] "pdfFichero" => "main.pdf" "tienePdf" => true "fechaRecibido" => "2014-08-15" "fechaAceptado" => "2014-10-07" "PalabrasClave" => array:1 [ "en" => array:1 [ 0 => array:4 [ "clase" => "keyword" "titulo" => "Keywords" "identificador" => "xpalclavsec1117076" "palabras" => array:4 [ 0 => "Collagen III" 1 => "Liver biopsy" 2 => "Metalloproteinases" 3 => "Non-invasive" ] ] ] ] "tieneResumen" => true "resumen" => array:1 [ "en" => array:2 [ "titulo" => "Abstract" "resumen" => "Background and rationale for the study. The assessment of liver fibrosis provides useful information not only for diagnosis but also for therapeutic decision. This study was concerned with determining the levels of collagen III and its degrading enzyme matrix metalloproteinase-1 (MMP-1) as direct and complementary markers for liver fibrosis staging.Results. A total of 269 chronic hepatitis C patients constituted this study. Western blotting was used for identifying collagen III and MMP-1 in serum samples. As a result, collagen III and MMP-1 were identified, respectively, at 70 and 245 kDa using their respective mono-specific antibodies. These two markers were quantified in sera of patients using ELISA. Next, Fibro-check was constructed combining collagen III and MMP-1 together with other indirect markers which reflect alteration in hepatic functions that proved useful to stage liver fibrosis. Fibro-check produced area under the receiver-operating characteristic curve (AUC) 0.91 and 0.83 for significant (F2-F4) and cirrhosis (F4), respectively. Additionally, we estimated the performance of Fibro-check in comparison with aspartate to platelet ratio index (APRI) and fibrosis index. Fibro-check seems to be more efficient than both of them. Fibro-check was then applied to the validation study to test its accuracy and reproducibility showing AUCs 0.90 for F2-F4 and 0.86 for F4.Conclusions. Fibro-check combining ‘direct’ and ‘indirect’ markers using a mathematical formula may improve the staging of liver fibrosis with a high degree of accuracy and seems more efficient than APRI and Fibrosis index in this group of Egyptian patients." ] ] "multimedia" => array:8 [ 0 => array:7 [ "identificador" => "f0005" "etiqueta" => "Figure 1" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr1.jpeg" "Alto" => 1107 "Ancho" => 460 "Tamanyo" => 41182 ] ] "descripcion" => array:1 [ "en" => "Areas under receiver-operating characteristic curve (AUCs) for A. Collagen III with an AUC of 0.75, B. MMP-1 with an AUC of 0.70, C. Collagen/MMP-1 ratio (CMR) with an AUC of 0.80 for predicting significant fibrosis (F2-F4) in chronic hepatitis C patients in the estimation study. Each point on the ROC plot represents a sensitivity/specificity pair corresponding to a particular decision threshold. An AUC of 1.0 is characteristic of an ideal test whereas an AUC of 0.5 or less indicates a test of no diagnostic value." ] ] 1 => array:7 [ "identificador" => "f0010" "etiqueta" => "Figure 2" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr2.jpeg" "Alto" => 824 "Ancho" => 451 "Tamanyo" => 43299 ] ] "descripcion" => array:1 [ "en" => "Area under the ROC curve for Fibro-check and comparison with APRI and Fibrosis index for predicting (A) significant fibrosis, (B) cirrhosis in chronic hepatitis C patients in the estimation study (n = 168). Calculations for Fibro-check, APRI and fibrosis index are shown in <a class="elsevierStyleCrossRef" href="#t0015">table 3</a>." ] ] 2 => array:7 [ "identificador" => "t0005" "etiqueta" => "Table 1" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "tabla" => array:3 [ "leyenda" => "Variables were expressed as mean ± SEM." "tablatextoimagen" => array:1 [ 0 => array:2 [ "tabla" => array:1 [ 0 => """ <table border="0" frame="\n \t\t\t\t\tvoid\n \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Variable \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Estimation group (n = 168) \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Validation group (n = 101) \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">P value<a class="elsevierStyleCrossRef" href="#tblfn0015">c</a> \t\t\t\t\t\t\n \t\t\t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Age (years) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">43.7 ± 0.5 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">45.2 ± 0.5 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">NS \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">AST (U/L)<a class="elsevierStyleCrossRef" href="#tblfn0005">a</a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">57.1 ± 2.5 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">55.9 ± 3.4 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">NS \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">ALT (U/L)<a class="elsevierStyleCrossRef" href="#tblfn0005">a</a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">62.0 ± 2.7 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">58.5 ± 3.7 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">NS \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">AST/ ALT (AAR) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.9 ± 0.03 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.0 ± 0.04 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">NS \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">ALP (U/L)<a class="elsevierStyleCrossRef" href="#tblfn0005">a</a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">84.3 ± 4.6 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">87.4 ± 5.7 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">NS \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Albumin (g/dL)<a class="elsevierStyleCrossRef" href="#tblfn0005">a</a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">4.2 ± 0.04 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">4.0 ± 0.05 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">NS \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Total bilirubin (mg/dL)<a class="elsevierStyleCrossRef" href="#tblfn0005">a</a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.9 ± 0.04 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.0 ± 0.06 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">NS \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Platelet count (109/L)<a class="elsevierStyleCrossRef" href="#tblfn0005">a</a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">181 ± 4.6 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">176 ± 0.6 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">NS \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">APRI<a class="elsevierStyleCrossRef" href="#tblfn0010">b</a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.0 ± 0.07 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.9 ± 0.1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">NS \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">AFP (U/L)<a class="elsevierStyleCrossRef" href="#tblfn0005">a</a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">6.4 ± 0.8 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">6.8 ± 1.1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">NS \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Collagen III (μg/mL) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">9.0 ± 0.4 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">8.6 ± 0.4 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">NS \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">MMP-1 (μg/mL)<a class="elsevierStyleCrossRef" href="#tblfn0010">b</a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">6.6 ± 0.6 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">7.2 ± 0.8 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">NS \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Collagen III/ MMP-1 (CMR) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">3.7 ± 0.4 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">4.2 ± 0.5 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">NS \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Metavir fibrosis stages \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">n (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">n (%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">F1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">89 (53) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">51 (50.5) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">F2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">31 (18.5) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">13 (12.9) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">F3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">14 (8.3) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">14 (13.9) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">F4 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">34 (20.2) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">23 (22.8) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab2046995.png" ] ] ] "notaPie" => array:3 [ 0 => array:3 [ "identificador" => "tblfn0005" "etiqueta" => "a" "nota" => "Reference values: aspartate aminotransferase (AST) (male up to 37 U/L, female up to 31 U/L); alanine aminotransferase (ALT) (male up to 41 U/L, female up to 31 U/L); alkaline phosphatase (ALP) 22-92 U/L; albumin 3.8-5.4 g/dL; total bilirubin up to 1 mg/dL; platelet count 150-400 × 109/L; alpha fetoprotein (AFP) up to 10 U/L." ] 1 => array:3 [ "identificador" => "tblfn0010" "etiqueta" => "b" "nota" => "APRI: [(AST (U/L)/upper limits of normal)/platelet count (109/L)] × 100; MMP-1: matrix metalloproteinase-1." ] 2 => array:3 [ "identificador" => "tblfn0015" "etiqueta" => "c" "nota" => "P > 0.05 is considered non significant (NS); P < 0.05 is considered significant." ] ] ] "descripcion" => array:1 [ "en" => "Comparison of patient characteristics in the estimation and validation groups." ] ] 3 => array:7 [ "identificador" => "t0010" "etiqueta" => "Table 2" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "tabla" => array:3 [ "leyenda" => "Variables were expressed as mean ± SEM." "tablatextoimagen" => array:1 [ 0 => array:2 [ "tabla" => array:1 [ 0 => """ <table border="0" frame="\n \t\t\t\t\tvoid\n \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Variable \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">F1 (n = 89) \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">F2-F3 (n = 45) \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">F2-F4 (n = 79) \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">F4 (n = 34) \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">P value<a class="elsevierStyleCrossRef" href="#tblfn0030">c</a> \t\t\t\t\t\t\n \t\t\t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Age (years) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">40.2 ± 0.9 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">44.24 ± 0.8 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">47.4 ± 0.7 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">50.2 ± 1.0 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">< 0.0001 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">AST (U/L)<a class="elsevierStyleCrossRef" href="#tblfn0020">a</a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">50.7 ± 2.4 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">63.51 ± 5.7 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">64.5 ± 4.6 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">65.8 ± 7.6 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.006 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">ALT (U/L)<a class="elsevierStyleCrossRef" href="#tblfn0020">a</a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">59.2 ± 2.2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">52.2 ± 7.0 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">64.1 ± 5.2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">73.7 ± 7.1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.402 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">AAR<a class="elsevierStyleCrossRef" href="#tblfn0025">b</a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.8 ± 0.03 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.0 ± 0.07 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.2 ± 0.06 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.4 ± 0.1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">< 0.0001 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">ALP (U/L)<a class="elsevierStyleCrossRef" href="#tblfn0020">a</a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">73.4 ± 6.0 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">79.0 ± 8.0 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">95.2 ± 6.6 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">119 ± 8.6 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.017 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Albumin (g/dL)<a class="elsevierStyleCrossRef" href="#tblfn0020">a</a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">4.3 ± 0.03 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">4.1 ± 0.09 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">3.9 ± 0.08 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">3.7 ± 0.1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">< 0.0001 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">T. bilirubin (mg/dL)<a class="elsevierStyleCrossRef" href="#tblfn0020">a</a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.7 ± 0.04 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.9 ± 0.07 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.1 ± 0.08 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.3 ± 0.1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">< 0.0001 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Platelet count (109/L)<a class="elsevierStyleCrossRef" href="#tblfn0020">a</a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">198 ± 4.8 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">173 ± 8.0 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">162 ± 7.5 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">149 ± 13.6 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">< 0.0001 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">APRI<a class="elsevierStyleCrossRef" href="#tblfn0025">b</a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.7 ± 0.04 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.0 ± 0.1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.3 ± 0.1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.6 ± 0.3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">< 0.0001 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">AFP (U/L)<a class="elsevierStyleCrossRef" href="#tblfn0020">a</a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">2.6 ± 0.2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">10.4 ± 1.7 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">10.6 ± 0.9 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">10.8 ± 2.7 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">< 0.0001 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Collagen III (μg/mL) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">6.9 ± 0.4 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">10.5 ± 0.9 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">11.8 ± 0.7 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">12.8 ± 1.0 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">< 0.0001 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">MMP-1 (μg/mL) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">8.8 ± 0.9 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">3.4 ± 0.6 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">3.2 ± 0.4 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">3.0 ± 0.4 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">< 0.0001 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">CMR<a class="elsevierStyleCrossRef" href="#tblfn0025">b</a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">2.2 ± 0.3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">5.7 ± 1.2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">7.1 ± 0.9 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">8.2 ± 1.3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">< 0.0001 \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab2046996.png" ] ] ] "notaPie" => array:3 [ 0 => array:3 [ "identificador" => "tblfn0020" "etiqueta" => "a" "nota" => "Reference values: aspartate aminotransferase (AST) (male up to 37 U/L, female up to 31 U/L); alanine aminotransferase (ALT) (male up to 41 U/L, female up to 31 U/L); alkaline phosphatase (ALP) 22-92 U/L; albumin 3.8-5.4 g/dL; total bilirubin (T. bilirubin) up to 1 mg/dL; platelet count 150-400 × 109/L; alpha fetoprotein (AFP) up to 10 U/L." ] 1 => array:3 [ "identificador" => "tblfn0025" "etiqueta" => "b" "nota" => "APRI: AST level (U/L)/40 (upper limits of normal)/platelets count (109/L) × 100. CMR: Collagen III/ MMP-1 ratio." ] 2 => array:3 [ "identificador" => "tblfn0030" "etiqueta" => "c" "nota" => "P > 0.05 is considered non significant; P < 0.05 is considered significant; P < 0.001 is considered very significant and P < 0.0001 is considered extremely significant." ] ] ] "descripcion" => array:1 [ "en" => "Variables associated with the presence of significant fibrosis (F2-F4) by univariate analysis in the estimation group (n = 168)." ] ] 4 => array:7 [ "identificador" => "t0015" "etiqueta" => "Table 3" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "tabla" => array:2 [ "tablatextoimagen" => array:1 [ 0 => array:2 [ "tabla" => array:1 [ 0 => """ <table border="0" frame="\n \t\t\t\t\tvoid\n \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Fibrosis testRef. \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Calculation<a class="elsevierStyleCrossRef" href="#tblfn0035">a</a> \t\t\t\t\t\t\n \t\t\t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Fibro-check \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">[CMR × AFP (U/L) × AAR/platelet count (109/L)] \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">APRI9 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">[(AST/upper limit of normal)/platelet count (109/L)] × 100 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Fibrosis index10 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">[8.0-0.01 × platelet count (109/L)-albumin (g/dL)] \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab2046993.png" ] ] ] "notaPie" => array:1 [ 0 => array:3 [ "identificador" => "tblfn0035" "etiqueta" => "a" "nota" => "CMR: collagen III/ MMP-1 ratio; AFP: alpha fetoprotein; AAR: aspartate aminotransferase (AST)/alanine aminotransferase (ALT) ratio." ] ] ] "descripcion" => array:1 [ "en" => "Calculations of fibrosis tests in comparison with Fibro-check in the present study." ] ] 5 => array:7 [ "identificador" => "t0020" "etiqueta" => "Table 4" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "tabla" => array:2 [ "tablatextoimagen" => array:1 [ 0 => array:2 [ "tabla" => array:1 [ 0 => """ <table border="0" frame="\n \t\t\t\t\tvoid\n \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Fibrosis testRef. \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Cutoff<a class="elsevierStyleCrossRef" href="#tblfn0040">a</a> \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Sn<a class="elsevierStyleCrossRef" href="#tblfn0040">a</a> \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Sp<a class="elsevierStyleCrossRef" href="#tblfn0040">a</a> \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">PPV<a class="elsevierStyleCrossRef" href="#tblfn0040">a</a> \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">NPV<a class="elsevierStyleCrossRef" href="#tblfn0040">a</a> \t\t\t\t\t\t\n \t\t\t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Significant fibrosis (F2-F4) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Fibro-check<a class="elsevierStyleCrossRef" href="#tblfn0040">a</a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">> 0.05 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">82 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">84 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">82 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">84 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">APRI9 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">> 1.5 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">29 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">96 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">85 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">60 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Fibrosis index10 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">≥ 2.1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">57 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">73 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">65 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">66 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Cirrhosis (F4) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Fibro-check<a class="elsevierStyleCrossRef" href="#tblfn0040">a</a> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">> 0.1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">74 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">77 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">45 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">92 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">APRI9 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">> 2.0 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">18 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">94 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">43 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">82 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Fibrosis index10 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">≥ 3.3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">35 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">99 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">86 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">86 \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab2046997.png" ] ] ] "notaPie" => array:1 [ 0 => array:3 [ "identificador" => "tblfn0040" "etiqueta" => "a" "nota" => "Fibro-check = [CMR × AFP (U/L) × AAR/platelet count (109/L)]; Sn: sensitivity; Sp: specificity; PPV: positive predictive value; NPV: negative predictive value." ] ] ] "descripcion" => array:1 [ "en" => "Diagnostic performances for Fibro-check in comparison with APRI and Fibrosis index for predicting significant fibrosis and cirrhosis in chronic hepatitis C patients." ] ] 6 => array:7 [ "identificador" => "t0025" "etiqueta" => "Table 5" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "tabla" => array:2 [ "tablatextoimagen" => array:1 [ 0 => array:2 [ "tabla" => array:1 [ 0 => """ <table border="0" frame="\n \t\t\t\t\tvoid\n \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">METAVIR stages \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Cutoff \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">AUC<a class="elsevierStyleCrossRef" href="#tblfn0045">a</a> \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">SE<a class="elsevierStyleCrossRef" href="#tblfn0045">a</a> \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">P value<a class="elsevierStyleCrossRef" href="#tblfn0050">b</a> \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">(95% CI<a class="elsevierStyleCrossRef" href="#tblfn0045">a</a>) \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Sn<a class="elsevierStyleCrossRef" href="#tblfn0045">a</a> \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Sp<a class="elsevierStyleCrossRef" href="#tblfn0045">a</a> \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">PPV<a class="elsevierStyleCrossRef" href="#tblfn0045">a</a> \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">NPV<a class="elsevierStyleCrossRef" href="#tblfn0045">a</a> \t\t\t\t\t\t\n \t\t\t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Estimation study (n = 168) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">F1 vs. F2-F3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">> 0.027 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.87 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.04 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">< 0.0001 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.80-0.94 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">80 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">71 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">55 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">88 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">F1 vs. F4 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">> 0.046 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.94 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.02 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">< 0.0001 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.90-0.99 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">94 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">84 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">70 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">97 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">F2-F3 vs. F4 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">> 0.12 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.62 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.07 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.06 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.50-0.57 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">71 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">54 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">57 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">68 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Validation study (n = 101) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">F1 vs. F2-F3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">> 0.027 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.87 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.05 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">< 0.0001 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.78-0.96 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">79 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">78 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">63 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">88 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">F1 vs. F4 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">> 0.046 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.97 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.02 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">< 0.0001 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.93-1.00 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">78 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">86 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">74 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">93 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">F2-F3 vs. F4 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">> 0.12 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.69 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.09 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.03 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.53-0.84 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">80 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">50 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">57 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">75 \t\t\t\t\t\t\n 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Abdelfattah M. Attallah

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, Mohamed El-Far†, Camelia A. Abdel Malak‡, Mohamed M. Omran§, Khaled Farid||, Mostafa A. Hussien¶, Mohamed S. Albannan*, Ahmed A. Attallah*, Mohamed S. Elbendary*, Dalia A. Elbesh*, Noha A. Elmenier*, Mohamed O. Abdallah*

* Research & Development Department, Biotechnology Research Center, New Damietta City, Egypt

† Faculty of Science, Mansoura University, Mansoura, Egypt

‡ Faculty of Science, Damietta University, New Damietta, Egypt

§ Faculty of Science, Helwan University, Cairo, Egypt

|| Tropical Medicine Department, Faculty of Medicine, Mansoura University, Mansoura, Egypt

¶ Faculty of Science, Port-Said University, Port-Said, Egypt

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          "en" => "<p id="sp0010" class="elsevierStyleSimplePara elsevierViewall">Area under the ROC curve for Fibro-check and comparison with APRI and Fibrosis index for predicting &#40;A&#41; significant fibrosis&#44; &#40;B&#41; cirrhosis in chronic hepatitis C patients in the estimation study &#40;n &#61; 168&#41;&#46; Calculations for Fibro-check&#44; APRI and fibrosis index are shown in <a class="elsevierStyleCrossRef" href="#t0015">table 3</a>&#46;</p>"
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    "textoCompleto" => "<span class="elsevierStyleSections"><span id="s0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="st0015">Introduction</span><p id="p0005" class="elsevierStylePara elsevierViewall">Hepatitis C virus &#40;HCV&#41; infection is a global health burden affecting approximately 160-170 million people worldwide&#46;<a class="elsevierStyleCrossRef" href="#bib0005"><span class="elsevierStyleSup">1</span></a> Once chronic HCV infection is established&#44; spontaneous HCV clearance rarely occurs&#46; Chronic hepatitis C &#40;CHC&#41; can cause continuous liver damage resulting in liver cirrhosis and subsequently hepatocellular carcinoma &#40;HCC&#41;&#46;<a class="elsevierStyleCrossRef" href="#bib0010"><span class="elsevierStyleSup">2</span></a> Staging of liver fibrosis is necessary in CHC patients because it is the important factor for initiation of treatment in patients with hepatitis C infection&#46;<a class="elsevierStyleCrossRef" href="#bib0015"><span class="elsevierStyleSup">3</span></a> Liver biopsy is the most commonly used reference standard for assessing liver fibrosis&#46; However&#44; liver biopsy is an invasive and is associated with a significant risk of complications ranged from minor complications like pain and transient hypotension to major complications like significant bleeding which may cause death&#46;<a class="elsevierStyleCrossRef" href="#bib0020"><span class="elsevierStyleSup">4</span></a> These limitations have stimulated the development of non-invasive techniques for assessing the presence and the degree of liver fibrosis&#46; The great majority of studies have investigated the diagnostic value of serum markers of liver fibrosis&#46; These markers were divided into two categories&#59; direct markers&#44; which are supposed to be directly involved in the deposition and removal of extracellular matrix &#40;ECM&#41;&#44; i&#46;e&#46; in fibrogenesis and fibrolysis and indirect markers&#44; which reflect alterations in hepatic function&#44; but not directly ECM metabolism&#46;<a class="elsevierStyleCrossRef" href="#bib0025"><span class="elsevierStyleSup">5</span></a> Fibrosis is characterized by the deposition of collagen and other extracellular matrix proteins and their organization in complex polymers&#44; which are insoluble and induce loss of the liver architecture&#46;<a class="elsevierStyleCrossRef" href="#bib0030"><span class="elsevierStyleSup">6</span></a> Collagen is synthesized as a procollagen by hepatic stellate cells &#40;HSCs&#41;&#44; later it is transformed to collagen by enzymatic splitting of the C-terminal and N-terminal end by procollagen C-proteinase and procollagen N-proteinase&#46;<a class="elsevierStyleCrossRef" href="#bib0035"><span class="elsevierStyleSup">7</span></a> Matrix metalloproteinases are the main degrading enzyme of these ECM proteins&#44; and have been implicated in the processes of liver fibrosis&#46; Among them&#44; the matrix metalloproteinase-1 &#40;MMP-1&#41; that cleaves the native helix of fibrillar collagens I&#44; II and III&#46;<a class="elsevierStyleCrossRef" href="#bib0040"><span class="elsevierStyleSup">8</span></a> Herein&#44; we aimed to determine the expression of collagen III and its degrading enzyme MMP-1 simultaneously and then estimating their performances as surrogate markers for liver fibrosis diagnosis&#46; Furthermore&#44; we aimed to develop a sensitive function incorporated both collagen III and its degrading enzyme MMP-1 together with other indirect markers which reflect alteration in hepatic function for liver fibrosis staging in CHC patients and then estimated its performance in comparison with some published noninvasive tests in CHC&#46;<a class="elsevierStyleCrossRef" href="#bib0045"><span class="elsevierStyleSup">9</span></a>&#44;<a class="elsevierStyleCrossRef" href="#bib0050"><span class="elsevierStyleSup">10</span></a></p></span><span id="s0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="st0020">Materials and Methods</span><span id="s0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="st0025">Samples</span><p id="p0010" class="elsevierStylePara elsevierViewall">Blood samples and liver biopsies of two hundred sixty-nine HCV infected individuals were collected from the Tropical Medicine department&#44; Mansoura University hospitals&#44; Mansoura&#44; Egypt&#46; One hundred sixty-eight patients constituted the estimation group whereas 101 patients constituted the validation group&#46; All tissue and serum samples were obtained with informed consent&#46; All patients were tested negative for HBsAg &#40;Dia&#46;Pro&#44; Milan&#44; Italy&#41;&#46; Also&#44; all patients were tested positive for anti-HCV antibodies &#40;Biomedica&#44; Sorin&#44; Italy&#41;&#46; Patients were then confirmed for the presence of HCV-RNA using quantitative polymerase chain reaction assay &#40;COBAS Ampliprep&#47; COBAS TaqMan&#44; Roche Diagnostics&#44; Pleasanton&#44; USA&#41;&#46; Cirrhotic patients were compensated at the time of inclusion&#46; Patients with an evidence of coexistent liver disease&#44; a history of hepatocellular carcinoma&#44; a previous interferon treatment and a decompensated liver disease were excluded from this study&#46; Needle liver biopsy specimens were obtained with an 18-gauge or larger needle&#46; To be considered as adequate for scoring&#44; the liver biopsies had to measure at least 15 mm and&#47;or contain at least five portal tracts&#44; except for cirrhosis for which no limitation was required&#46; Biopsies were interpreted according to METAVIR scoring system&#46;<a class="elsevierStyleCrossRef" href="#bib0055"><span class="elsevierStyleSup">11</span></a> Liver function tests &#91;albumin&#44; total bilirubin&#44; aspartate aminotransferase &#40;AST&#41;&#44; alanine aminotransferase &#40;ALT&#41; and alkaline phosphatase &#40;ALP&#41;&#93; were all measured on an automated biochemistry analyzer &#40;Hitachi 917&#59; Roche Diagnostics&#44; Mannheim&#44; Germany&#41;&#46; Complete blood count was performed using KX-21 Sysmex automated hematology analyzer &#40;Sysmex Corporation&#44; Kobe&#44; Japan&#41;&#46; Alpha fetoprotein &#40;AFP&#41; level was estimated by chemiluminescence&#44; with Immulite &#40;1000&#41; AFP kit &#40;Diagnostic Products Corporation&#59; Los Angeles&#44; CA&#44; USA&#41;&#46;</p></span><span id="s0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="st0030">Western blotting and gel electroelution</span><p id="p0015" class="elsevierStylePara elsevierViewall">First&#44; sodium dodecyl sulfate-polyacrylamide gel electrophoresis was carried out in 0&#46;75 mm-thick&#44; 12&#37; vertical slab gels according to the method of Laemmli&#46;<a class="elsevierStyleCrossRef" href="#bib0060"><span class="elsevierStyleSup">12</span></a> Next&#44; Western electroblotting was used for transferring the separated protein bands onto a nitrocellulose membrane &#40;0&#46;45 mm pore size&#44; Sigma&#41; in a protein transfer unit according to Towbin&#44; <span class="elsevierStyleItalic">et al</span>&#46;<a class="elsevierStyleCrossRef" href="#bib0065"><span class="elsevierStyleSup">13</span></a> Then&#44; they were immunostained using monospecific antibodies corresponding to human collagen type III and MMP-1 separately&#46; Finally&#44; both collagen III and MMP-1 bands were cut and electroeluted separately from preparative polyacrylamide gels at 200 V for 3 h in a dialysis bag &#40;Sigma&#41;&#46; The protein content of the purified bands was determined<a class="elsevierStyleCrossRef" href="#bib0070"><span class="elsevierStyleSup">14</span></a> and the remainder was stored at -20 &#176;C&#46;</p></span><span id="s0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="st0035">Quantitation of collagen III and MMP-1 using ELISA</span><p id="p0020" class="elsevierStylePara elsevierViewall">Diluted serum samples &#40;1&#58;50&#41; in coating buffer &#40;50 mM carbonate&#47;bicarbonate buffer&#44; pH 9&#46;6&#41; were tested &#40;50 <span class="elsevierStyleItalic">&#956;</span>L&#47;well&#41; for collagen III bound on a 96-well microtiter plate at 4 &#176;C overnight&#46; After blocking with 0&#46;5&#37; BSA in coating buffer &#40;200 <span class="elsevierStyleItalic">&#956;</span>L&#47;well&#41;&#44; mono-specific antibody for collagen III at dilution 1&#58;200 in PBS was added &#40;50 <span class="elsevierStyleItalic">&#956;</span>L&#47;well&#41; and incubated at 37 &#176;C for 2 h&#46; Goat anti-rabbit antibody conjugated with alkaline phosphatase &#40;Sigma&#41; 1&#58;700 in 0&#46;2&#37; BSA in PBS-T20 was incubated at 37 &#176;C for 1 h&#46; Similarly&#44; diluted serum samples &#40;1&#58;50&#41; in coating buffer were tested &#40;50 <span class="elsevierStyleItalic">&#956;</span>L&#47;well&#41; for MMP-1 bound on a 96-well microtiter plate at 4 &#176;C overnight&#46; Likewise&#44; after blocking with 0&#46;6&#37; BSA in coating buffer &#40;200 <span class="elsevierStyleItalic">&#956;</span>L&#47;well&#41;&#44; mono-specific antibody for MMP-1 at dilution 1&#58;500 in PBS was added &#40;50 <span class="elsevierStyleItalic">&#956;</span>L&#47;well&#41; and incubated at 37 &#176;C for 2 h&#46; Also&#44; goat anti-rabbit antibody conjugated with alkaline phosphatase &#40;Sigma&#41; 1&#58;500 in 0&#46;2&#37; BSA in PBS-T20 was incubated at 37 &#176;C for 1 h&#46; The plates were washed with PBS&#43;0&#46;5&#37; Tween 20 after every step&#46; The substrate was 1 mg&#47; mL p-nitrophenyl phosphate and the intensity of the signal was determined by measuring the absorbance at 450 nm after 10 minutes using a microtiter plate reader &#40;&#931;960&#44; Metretech Inc&#44; Germany&#41;&#46; The calibration curves of the serial concentrations for the purified Collagen III &#40;0&#46;1-30 <span class="elsevierStyleItalic">&#956;</span>g&#47;mL&#41; and MMP-1 &#40;0&#46;5-24 <span class="elsevierStyleItalic">&#956;</span>g&#47;mL&#41; were then determined&#46;</p></span><span id="s0030" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="st0040">Statistical analysis</span><p id="p0025" class="elsevierStylePara elsevierViewall">All statistical calculations were done by SPSS software v&#46;15&#46;0 &#40;SPSS Inc&#46;&#44; Chicago&#44; IL&#41; and Graph-Pad Prism package&#59; v&#46;5&#46;0 &#40;GraphPad Software&#44; San Diego&#44; CA&#41;&#46; Continuous variables were expressed as mean &#177; standard error of mean&#46; A value of P &#60; 0&#46;05 was considered statistically significant&#46; There were 2 endpoints in this study&#58; presence of significant fibrosis and cirrhosis&#46; The correlation was evaluated by Spearman&#8217;s rank correlation coefficient&#46; Univariate analysis identified the predictors of fibrosis by using the Student&#8217;s <span class="elsevierStyleItalic">t</span> test&#46; The diagnostic value was assessed by calculating the area under the receiver operating characteristic &#40;ROC&#41; curves&#46; An area under the curve &#40;AUC&#41; of 1&#46;0 is characteristic of an ideal test&#44; whereas 0&#46;5 indicates a test of no diagnostic value&#46; All variables with high AUCs and high significance on univariate analysis were entered in stepwise linear regression analysis to develop a model for identifying significant fibrosis&#46; Based on the ROC analysis&#44; the best cutoff points were selected and diagnostic performances &#40;sensitivity&#44; specificity&#44; positive predictive value &#40;PPV&#41; and negative predictive value &#40;NPV&#41;&#41; were determined&#46;</p></span></span><span id="s0035" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="st0045">Results</span><span id="s0040" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="st0050">Patient characteristics</span><p id="p0030" class="elsevierStylePara elsevierViewall">One hundred sixty-eight HCV-monoinfected patients fulfilled the selection criteria&#46; The sample comprised one hundred and eleven men and fifty-seven women&#46; Laboratory characteristics of all patients at the time of liver biopsy are summarized in <a class="elsevierStyleCrossRef" href="#t0005">table 1</a>&#46; Comparison of the baseline characteristics of patients according to the stage of liver fibrosis are outlined in <a class="elsevierStyleCrossRef" href="#t0010">table 2</a>&#46; As individuals with significant fibrosis &#40;F2-F4&#41; are at increased risk of developing cirrhosis and are usually accepted as an indication to commence treatment&#44; the laboratory features of patients with minimal fibrosis &#40;F1&#41; and F2-F4 were compared by univariate analysis based on the Student&#8217;s <span class="elsevierStyleItalic">t</span> test&#46; As a result&#44; patients with F1 were young with a mean &#40;&#177; SEM&#41; of 40&#46;2 &#40;&#177; 0&#46;9&#41; years as compared to those who developed F2-F4&#46; Moreover&#44; patients with F2-F4 were associated with higher AST&#44; ALT&#44; AAR&#44; ALP&#44; APRI and AFP levels than those with F1&#46; On contrary&#44; the mean value of albumin and platelet count decreased with the progression of liver fibrosis being lower in patients who developed F2-F4 &#40;<a class="elsevierStyleCrossRef" href="#t0010">Table 2</a>&#41;&#46;</p><elsevierMultimedia ident="t0005"></elsevierMultimedia><elsevierMultimedia ident="t0010"></elsevierMultimedia></span><span id="s0045" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="st0055">Identification and quantitation of collagen III and MMP-1</span><p id="p0035" class="elsevierStylePara elsevierViewall">SDS-PAGE and Western blotting were used as described previously to identify the target collagen III and its degrading enzyme MMP-1&#46; As a result&#44; a single immunoreactive band was shown at 70 kDa and 245 kDa for collagen type III and MMP-1&#44; respectively&#44; due to their binding with their respective mono-specific antibodies&#46; Patients with significant fibrosis &#40;F2-F4&#41; were associated with higher concentration of collagen III than those with minimal fibrosis &#40;F1&#41;&#46; On the other hand&#44; patients with F2-F4 were associated with lower concentration of MMP-1 than those with F1 &#40;as shown in <a class="elsevierStyleCrossRef" href="#t0010">table 2</a>&#41;&#46; The use of collagen III <span class="elsevierStyleItalic">per se</span> could discriminate F2-F4 from F1 with an AUC &#61; 0&#46;75 while the use of MMP-1 <span class="elsevierStyleItalic">per se</span> yielded an AUC &#61; 0&#46;70 for identifying F2-F4 &#40;<a class="elsevierStyleCrossRef" href="#f0005">Figures 1</a>A&#44; 1B&#41;&#46; Surprisingly&#44; it has been observed that collagen III&#47;MMP-1 ratio &#40;CMR&#41; yielded values that increased significantly in patients with F2-F4 <span class="elsevierStyleItalic">vs&#46;</span> those with F1 &#40;<a class="elsevierStyleCrossRef" href="#t0010">Table 2</a>&#41; and identified F2-F4 with a better AUC &#61; 0&#46;80 than each marker separately &#40;<a class="elsevierStyleCrossRef" href="#f0005">Figure 1</a>C&#41;&#46; Hence&#44; the overlap in collagen III and MMP-1 among patients with F1 and F2-F4 has been diminished and the difference in their value has been amplified&#46; Then&#44; based on ROC curve&#44; a cutoff point greater than 2&#46;5 was selected for CMR for separating patients with F2-F4 from those with F1 yielding a sensitivity of 77&#37; and specificity of 71&#37;&#46;</p><elsevierMultimedia ident="f0005"></elsevierMultimedia></span><span id="s0050" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="st0060">Development of the Fibro-check</span><p id="p0040" class="elsevierStylePara elsevierViewall">The next step was aimed to enhance the diagnostic accuracy of CMR for diagnosing F2-F4&#46; So&#44; it is necessary for this ratio to be combined with other routine marker&#46; On univariate analysis&#44; nine of the ten evaluated routine markers included in this study showed a significant association with fibrosis stages F2-F4 &#40;P &#60; 0&#46;05&#41;&#46; They were age&#44; AAR&#44; albumin&#44; total bilirubin&#44; platelet count&#44; APRI&#44; AFP&#44; AST and ALP&#46; Serum ALT did not differentiate between F1 and F2-F4 &#40;P &#62; 0&#46;05&#41; as presented in <a class="elsevierStyleCrossRef" href="#t0010">table 2</a>&#46; However&#44; multivariate regression modeling demonstrated that only AAR&#44; platelet count&#44; and AFP together with CMR retained significance when combined with each other&#46; Thus&#44; CMR&#44; AFP&#44; AAR and platelet count were selected as the best combination for diagnosing F2-F4&#46; Then&#44; we put the positive correlation parameters &#40;CMR&#44; AAR and AFP&#41; in the numerator and the negative correlation parameters &#40;platelet count&#41; in the denominator to formulate the following function &#40;<a class="elsevierStyleCrossRef" href="#t0015">Table 3</a>&#41;&#58;<elsevierMultimedia ident="f005"></elsevierMultimedia></p><elsevierMultimedia ident="t0015"></elsevierMultimedia></span><span id="s0055" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="st0065">Diagnostic performance of Fibro-check</span><p id="p0045" class="elsevierStylePara elsevierViewall">The diagnostic value of Fibro-check was then assessed by calculating the area under the ROC curve that showed a superior AUC of 0&#46;91 for identifying F2-F4&#46; Next&#44; an optimal cutoff point of 0&#46;05 was selected based on the ROC curve analysis&#46; For Fibro-check greater than 0&#46;05&#44; 65 out of 79 &#40;82&#37; PPV&#41; would have significant fibrosis and only 14 of 89 without significant fibrosis would be classified falsely&#46; At this cutoff point&#44; significant fibrosis could be excluded with 84&#37; NPV i&#46;e&#46;&#44; 16&#37; of patients with Fibro-check less than 0&#46;05 had significant fibrosis&#46; Furthermore&#44; the effectiveness of Fibro-check in predicting cirrhosis was then preformed using ROC curve producing an AUC of 0&#46;83 lower than that produced in identifying significant fibrosis&#46; An optimal cutoff point of 0&#46;1 was selected based on the ROC curve analysis&#46; At this cutoff point&#44; Fibro-check had sensitivity of 74&#37; with PPV of 45&#37; and specificity of 77&#37; with a NPV of 92&#37; for predicting cirrhosis i&#46;e&#46; 8&#37; of patients with Fibro-check value less than 0&#46;1 had cirrhosis &#40;<a class="elsevierStyleCrossRef" href="#t0020">Table 4</a>&#41;&#46;</p><elsevierMultimedia ident="t0020"></elsevierMultimedia></span><span id="s0060" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="st0070">Performance of Fibro-check in comparison with APRI and fibrosis index</span><p id="p0050" class="elsevierStylePara elsevierViewall">Next&#44; our results were compared with those of the previous reports&#44;<a class="elsevierStyleCrossRef" href="#bib0045"><span class="elsevierStyleSup">9</span></a>&#44;<a class="elsevierStyleCrossRef" href="#bib0050"><span class="elsevierStyleSup">10</span></a> ROC curves of APRI<a class="elsevierStyleCrossRef" href="#bib0045"><span class="elsevierStyleSup">9</span></a> and fibrosis index<a class="elsevierStyleCrossRef" href="#bib0050"><span class="elsevierStyleSup">10</span></a> &#40;their calculations are shown in <a class="elsevierStyleCrossRef" href="#t0015">table 3</a>&#41; <span class="elsevierStyleItalic">vs&#46;</span> Fibro-check were constructed and superimposed to determine which score would have the most clinical utility to predict significant fibrosis as displayed in <a class="elsevierStyleCrossRef" href="#f0010">figure 2</a>A&#46; The AUC using the procedure described by Hanley and McNeil<a class="elsevierStyleCrossRef" href="#bib0075"><span class="elsevierStyleSup">15</span></a> was better for Fibro-check &#40;AUC &#61; 0&#46;91&#41; than fibrosis index &#40;AUC &#61; 0&#46;73&#41; followed by APRI &#40;AUC &#61; 0&#46;69&#41;&#46; Next&#44; ROC curves were also constructed and superimposed to determine which score would have the most clinical utility in predicting cirrhosis&#46; The AUC was higher for Fibro-check &#40;AUC &#61; 0&#46;83&#41; than fibrosis index &#40;AUC &#61; 0&#46;79&#41; followed by APRI &#40;AUC &#61; 0&#46;68&#41; as displayed in <a class="elsevierStyleCrossRef" href="#f0010">figure 2</a>&#46;B&#46; Additionally&#44; the sensitivity&#44; specificity&#44; PPV and NPV for these fibrosis tests were calculated using cutoff values exactly as originally described by their authors<a class="elsevierStyleCrossRef" href="#bib0045"><span class="elsevierStyleSup">9</span></a>&#44;<a class="elsevierStyleCrossRef" href="#bib0050"><span class="elsevierStyleSup">10</span></a> which were not found to be optimal as shown in <a class="elsevierStyleCrossRef" href="#t0020">table 4</a>&#46; Moreover&#44; Bivariate Spearman&#8217;s rank correlation coefficient <span class="elsevierStyleItalic">&#40;r&#41;</span> was calculated to measure the relationship between these aforementioned tests and the METAVIR fibrosis score&#46; As a result&#44; Fibro-check significantly correlated with liver fibrosis stages with a better correlation coefficient &#40;r &#61; 0&#46;70&#44; P &#60; 0&#46;0001&#41; than those produced by APRI &#40;r &#61; 0&#46;34&#44; P &#60; 0&#46;0001&#41; and fibrosis index &#40;r &#61; 0&#46;43&#44; P &#60; 0&#46;0001&#41;&#46; Then&#44; the diagnostic performances of Fibro-check in discriminating F1 from F2-F3&#44; F1 from F4 and F2-F3 from F4 were evaluated and presented in <a class="elsevierStyleCrossRef" href="#t0025">table 5</a>&#46;</p><elsevierMultimedia ident="f0010"></elsevierMultimedia><elsevierMultimedia ident="t0025"></elsevierMultimedia></span><span id="s0065" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="st0075">Validation study</span><p id="p0055" class="elsevierStylePara elsevierViewall">The Fibro-check was then applied to a validation cohort comprising one hundred and one patients to test its accuracy and reproducibility&#46; The characteristics of the validation group were similar to that of the estimation group with no significant differences in any of the assessed variables &#40;<a class="elsevierStyleCrossRef" href="#t0005">Table 1</a>&#41;&#46; The Fibro-check significantly correlated with liver fibrosis stages &#40;r &#61; 0&#46;60&#44; P &#60; 0&#46;0001&#41;&#46; The diagnostic power of Fibro-check was assessed in the validation group by ROC curve showing AUCs of 0&#46;90 and 0&#46;86 for identifying significant fibrosis and cirrhosis&#44; respectively&#46; At cutoff point &#62; 0&#46;05&#44; Fibro-check produced 80&#37; sensitivity with 83&#37; PPV and 86&#37; specificity with 82&#37; NPV for identifying significant fibrosis&#46; At cutoff point &#62; 0&#46;1&#44; Fibro-check produced 80&#37; sensitivity with 50&#37; PPV and 78&#37; specificity with 93&#37; NPV for identifying cirrhosis&#46; Additionally&#44; the diagnostic performances of Fibro-check in separating between F1&#44; F2-F3 and F4 were validated as seen in <a class="elsevierStyleCrossRef" href="#t0025">table 5</a>&#46;</p></span></span><span id="s0070" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="st0080">Discussion</span><p id="p0060" class="elsevierStylePara elsevierViewall">It is worthy noting that serum levels of proteins directly related to the hepatic fibrogenic process could be used as surrogate markers of liver fibrosis&#46;<a class="elsevierStyleCrossRef" href="#bib0080"><span class="elsevierStyleSup">16</span></a> They reflect the greater deposition of ECM in the liver due to either increased synthesis by activated stellate cells or slow removal by Kupffer and endothelial sinusoidal cells&#46;<a class="elsevierStyleCrossRef" href="#bib0085"><span class="elsevierStyleSup">17</span></a> These tests include measures of hepatic metabolic activity&#44; extracellular matrix remodeling proteins&#44; collagen synthesis and degradation products&#44; and enzymes involved in matrix degradation&#46; Collagen is considered to be the main component of connective tissue&#44; and is the most abundant protein in mammals&#46;<a class="elsevierStyleCrossRef" href="#bib0090"><span class="elsevierStyleSup">18</span></a> Of the many collagen subtypes described&#44; only five have been detected in liver&#59; they are types I&#44; III&#44; IV&#44; V and VI&#46;<a class="elsevierStyleCrossRef" href="#bib0095"><span class="elsevierStyleSup">19</span></a></p><p id="p0065" class="elsevierStylePara elsevierViewall">Extracellular degradation of matrix proteins is regulated by a family of zinc-dependent neutral proteases called the matrix metalloproteinases &#40;MMPs&#41;&#46; These MMPs are subdivided into 3 groups&#59; collagenases that have a role in degrading and denaturing interstitial collagens &#40;types I&#44; II and III&#41;&#44; type IV collagenases&#47;gelatinases that degrade basement membrane &#40;type IV&#41; collagen and gelatins as well as stromelysins that degrade fibronectin&#44; gelatins&#44; proteoglycans and laminin&#46;<a class="elsevierStyleCrossRef" href="#bib0100"><span class="elsevierStyleSup">20</span></a> There is a relatively large literature suggesting that MMP activity in liver decreases as fibrosis progresses&#46; Decreased activity of ECM-removing MMPs is mainly due to an overexpression of their specific inhibitors &#40;TIMPs&#41; <a class="elsevierStyleCrossRef" href="#bib0105">&#40;21&#41;</a>&#46; Interstitial collagenase &#8220;MMP-1&#8221; is one of these MMPs which cleaves the native helix of fibrillar collagens types I&#44; II and III&#44; specifically at a single site into one-quarter and three-quarter products&#59; these are susceptible to further degradation by other proteinases&#46;<a class="elsevierStyleCrossRef" href="#bib0040"><span class="elsevierStyleSup">8</span></a></p><p id="p0070" class="elsevierStylePara elsevierViewall">Therefore&#44; this work was concerned with the identification and quantitative determination of both collagen III and MMP-1 and then estimating their performances as surrogate markers for accurate diagnosis of liver fibrosis&#46; Our results showed that patients with F2-F4 were associated with higher collagen III concentration than that observed in patients with F1 with extremely significant difference yielding AUC &#61; 0&#46;75 for diagnosing F2-F4&#46; The latter result may be explained by the fact that ECM is a highly dynamic substratum with a precisely regulated balance between synthesis and degradation&#46; But upon injury&#44; the HSCs become activated and secrete large amounts of ECM&#46; Consequently&#44; ECM production exceeds ECM degradation&#44; and hepatic fibrosis develops as a result of the progressive thickening of fibrotic septae and chemical cross-linking of collagen&#46;<a class="elsevierStyleCrossRef" href="#bib0110"><span class="elsevierStyleSup">22</span></a></p><p id="p0075" class="elsevierStylePara elsevierViewall">On contrary&#44; the mean value of MMP-1 concentration decreased with the progression of liver fibrosis being lower in patients who developed F2-F4 than those with F1 with extremely significant difference yielding AUC &#61; 0&#46;70 for identifying F2-F4&#46; The decreased activity of ECM-removing MMPs may be explained by the fact that TIMPs are co-expressed with MMPs and contribute to the regulation of local metalloproteinase activity&#46; An increased hepatic TIMP expression may thus account for reduced metalloproteinase activity and is thought to be important for hepatic fibroproliferation&#46;<a class="elsevierStyleCrossRef" href="#bib0115"><span class="elsevierStyleSup">23</span></a></p><p id="p0080" class="elsevierStylePara elsevierViewall">In order to amplify the difference in collagen III and MMP-1 values among patients with F1 and F2-F4 and increase their aptitude&#44; collagen III&#47;MMP-1 ratio was devised that showed a better AUC &#61; 0&#46;80 than that produced by each individually&#46; Indeed&#44; it was necessary for collagen III&#47;MMP-1 ratio to be combined with other variables to improve its diagnostic ability for F2-F4 diagnosis&#46; In this work&#44; patients with F2-F4 were found to have significant lower platelet count than that observed in patients with F1&#46; The decreased level of platelet count could be interpreted by the fact that hepatic fibrosis may cause thrombocytopenia as a consequence of impaired synthesis of thrombopoietin and&#47;or sequestering of platelets in an enlarged spleen&#46; Many studies supported that platelet count alone may be clinically valuable as a noninvasive marker for liver fibrosis and cirrhosis&#46;<a class="elsevierStyleCrossRef" href="#bib0120"><span class="elsevierStyleSup">24</span></a>&#44;<a class="elsevierStyleCrossRef" href="#bib0125"><span class="elsevierStyleSup">25</span></a> Ono&#44; <span class="elsevierStyleItalic">et al</span>&#46;<a class="elsevierStyleCrossRef" href="#bib0130"><span class="elsevierStyleSup">26</span></a> has reported that platelet count alone could discriminate F4 from F1-F3 in 75-80&#37; of CHC patients&#46; Consequently&#44; platelet count was identified as a significant predictor of fibrosis&#46;</p><p id="p0085" class="elsevierStylePara elsevierViewall">On the other hand&#44; the clinical use of AAR in the diagnostic workup of patients with chronic liver disease is supported by studies conducted in several countries&#46;<a class="elsevierStyleCrossRef" href="#bib0135"><span class="elsevierStyleSup">27</span></a> AAR has been reported as a surrogate marker of liver fibrosis with values greater than one being suggestive of cirrhosis&#46;<a class="elsevierStyleCrossRef" href="#bib0140"><span class="elsevierStyleSup">28</span></a> That&#8217;s because of the increased release of mitochondrial AST&#44; the decreased clearance of AST and&#47;or impaired synthesis of ALT in advanced stages of liver disease&#46;<a class="elsevierStyleCrossRef" href="#bib0145"><span class="elsevierStyleSup">29</span></a> With regard to AFP&#44; it is an important marker in diagnosing HCC&#46; However&#44; elevated AFP level has also been observed in chronic hepatitis C patients&#46;<a class="elsevierStyleCrossRef" href="#bib0150"><span class="elsevierStyleSup">30</span></a></p><p id="p0090" class="elsevierStylePara elsevierViewall">As a consequence of these analyses&#44; a discriminant function called Fibro-check composed of collagen III&#44; MMP-1 together with platelet count&#44; AAR and AFP was created&#46; The diagnostic value of Fibro-check was then assessed by the ROC curve giving 0&#46;91 AUC for identifying F2-F4 and 0&#46;83 AUC for identifying F4&#46; The present work was concerned with identifying the presence of F2-F4 and F4&#46; That is because the presence of F2-F4 is accepted as an indication to commence treatment<a class="elsevierStyleCrossRef" href="#bib0155"><span class="elsevierStyleSup">31</span></a>&#44;<a class="elsevierStyleCrossRef" href="#bib0160"><span class="elsevierStyleSup">32</span></a> and the presence of F4 also has implications regarding screening for HCC&#46;<a class="elsevierStyleCrossRef" href="#bib0165"><span class="elsevierStyleSup">33</span></a></p><p id="p0095" class="elsevierStylePara elsevierViewall">Next&#44; we evaluated the diagnostic accuracies of some non-invasive scores for assessing the degree of liver fibrosis in comparison with our developed score in our study group&#46; Among these&#44; APRI<a class="elsevierStyleCrossRef" href="#bib0045"><span class="elsevierStyleSup">9</span></a> and fibrosis index&#46;<a class="elsevierStyleCrossRef" href="#bib0050"><span class="elsevierStyleSup">10</span></a> Diagnostic accuracies for these aforementioned scores were evaluated using categories and cutoff values exactly as originally described which were not found to be optimal and had AUCs lower than those reported previously by their authors in their original study&#46; These discrepancies may be related to differences in the prevalence of F2-F4 and F4&#46; Also&#44; they may be related to differences in the patient characteristics and the histopathological assessment&#46; It is worthy noting that in Egypt&#44; patient delay seeking medical care until symptoms get worsen that explain the lack of patient with F0 from our study population&#46; We acknowledge that there is a limitation to the clinical use of MMP-1 and collagen III because they are not routinely available in all hospital settings&#46;</p><p id="p0100" class="elsevierStylePara elsevierViewall">Finally&#44; we evaluated whether the predictive criteria identified in the estimation study were able to reproduce their predictive ability in a subsequent different&#44; but related group of patients&#46; In conclusion&#44; we showed that a five-marker model combining collagen III&#44; MMP-1 together with platelet count&#44; AAR and AFP may improve liver fibrosis staging with a high degree of accuracy and seems more efficient than APRI and fibrosis index in our hands&#46; Further prospective studies involving a greater number of patients are warranted to validate the usefulness of the produced score in clinical practice&#46;</p></span><span id="s0075" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="st0085">Abbreviations</span><p id="p0105" class="elsevierStylePara elsevierViewall"><ul class="elsevierStyleList" id="l0005"><li class="elsevierStyleListItem" id="u0005"><span class="elsevierStyleLabel">&#8226;</span><p id="p0110" class="elsevierStylePara elsevierViewall"><span class="elsevierStyleBold">AAR</span>&#58; AST&#47; ALT ratio&#46;</p></li><li class="elsevierStyleListItem" id="u0010"><span class="elsevierStyleLabel">&#8226;</span><p id="p0115" class="elsevierStylePara elsevierViewall"><span class="elsevierStyleBold">ALT</span>&#58; alanine aminotransferase&#46;</p></li><li class="elsevierStyleListItem" id="u0015"><span class="elsevierStyleLabel">&#8226;</span><p id="p0120" class="elsevierStylePara elsevierViewall"><span class="elsevierStyleBold">ALP</span>&#58; alkaline phosphatase&#46;</p></li><li class="elsevierStyleListItem" id="u0020"><span class="elsevierStyleLabel">&#8226;</span><p id="p0125" class="elsevierStylePara elsevierViewall"><span class="elsevierStyleBold">APRI</span>&#58; aspartate to platelet ratio index&#46;</p></li><li class="elsevierStyleListItem" id="u0025"><span class="elsevierStyleLabel">&#8226;</span><p id="p0130" class="elsevierStylePara elsevierViewall"><span class="elsevierStyleBold">AST</span>&#58; aspartate aminotransferase&#46;</p></li><li class="elsevierStyleListItem" id="u0030"><span class="elsevierStyleLabel">&#8226;</span><p id="p0135" class="elsevierStylePara elsevierViewall"><span class="elsevierStyleBold">AFP</span>&#58; alpha fetoprotein&#46;</p></li><li class="elsevierStyleListItem" id="u0035"><span class="elsevierStyleLabel">&#8226;</span><p id="p0140" class="elsevierStylePara elsevierViewall"><span class="elsevierStyleBold">CHC</span>&#58; chronic hepatitis C&#46;</p></li><li class="elsevierStyleListItem" id="u0040"><span class="elsevierStyleLabel">&#8226;</span><p id="p0145" class="elsevierStylePara elsevierViewall"><span class="elsevierStyleBold">CMR</span>&#58; collagen III&#47; Matrix metalloproteinase-1 ratio&#46;</p></li><li class="elsevierStyleListItem" id="u0045"><span class="elsevierStyleLabel">&#8226;</span><p id="p0150" class="elsevierStylePara elsevierViewall"><span class="elsevierStyleBold">ECM</span>&#58; extracellular matrix&#46;</p></li><li class="elsevierStyleListItem" id="u0050"><span class="elsevierStyleLabel">&#8226;</span><p id="p0155" class="elsevierStylePara elsevierViewall"><span class="elsevierStyleBold">HCC</span>&#58; hepatocellular carcinoma&#46;</p></li><li class="elsevierStyleListItem" id="u0055"><span class="elsevierStyleLabel">&#8226;</span><p id="p0160" class="elsevierStylePara elsevierViewall"><span class="elsevierStyleBold">HCV</span>&#58; hepatitis C virus&#46;</p></li><li class="elsevierStyleListItem" id="u0060"><span class="elsevierStyleLabel">&#8226;</span><p id="p0165" class="elsevierStylePara elsevierViewall"><span class="elsevierStyleBold">MMP-1</span>&#58; matrix metalloproteinase-1&#46;</p></li></ul></p></span><span id="s0080" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="st0090">Conflict of Interest</span><p id="p0170" class="elsevierStylePara elsevierViewall">The authors declared that there is no conflict of interest&#46;</p></span><span id="s0085" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="st0095">Acknowledgements</span><p id="p0175" class="elsevierStylePara elsevierViewall">This study has been completely supported financially and carried out at Biotechnology Research Center&#44; New Damietta&#44; Egypt&#46;</p></span></span>"
    "textoCompletoSecciones" => array:1 [
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        0 => array:3 [
          "identificador" => "xres1198582"
          "titulo" => "Abstract"
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            0 => array:1 [
              "identificador" => "abs0010"
            ]
          ]
        ]
        1 => array:2 [
          "identificador" => "xpalclavsec1117076"
          "titulo" => "Keywords"
        ]
        2 => array:2 [
          "identificador" => "s0005"
          "titulo" => "Introduction"
        ]
        3 => array:3 [
          "identificador" => "s0010"
          "titulo" => "Materials and Methods"
          "secciones" => array:4 [
            0 => array:2 [
              "identificador" => "s0015"
              "titulo" => "Samples"
            ]
            1 => array:2 [
              "identificador" => "s0020"
              "titulo" => "Western blotting and gel electroelution"
            ]
            2 => array:2 [
              "identificador" => "s0025"
              "titulo" => "Quantitation of collagen III and MMP-1 using ELISA"
            ]
            3 => array:2 [
              "identificador" => "s0030"
              "titulo" => "Statistical analysis"
            ]
          ]
        ]
        4 => array:3 [
          "identificador" => "s0035"
          "titulo" => "Results"
          "secciones" => array:6 [
            0 => array:2 [
              "identificador" => "s0040"
              "titulo" => "Patient characteristics"
            ]
            1 => array:2 [
              "identificador" => "s0045"
              "titulo" => "Identification and quantitation of collagen III and MMP-1"
            ]
            2 => array:2 [
              "identificador" => "s0050"
              "titulo" => "Development of the Fibro-check"
            ]
            3 => array:2 [
              "identificador" => "s0055"
              "titulo" => "Diagnostic performance of Fibro-check"
            ]
            4 => array:2 [
              "identificador" => "s0060"
              "titulo" => "Performance of Fibro-check in comparison with APRI and fibrosis index"
            ]
            5 => array:2 [
              "identificador" => "s0065"
              "titulo" => "Validation study"
            ]
          ]
        ]
        5 => array:2 [
          "identificador" => "s0070"
          "titulo" => "Discussion"
        ]
        6 => array:2 [
          "identificador" => "s0075"
          "titulo" => "Abbreviations"
        ]
        7 => array:2 [
          "identificador" => "s0080"
          "titulo" => "Conflict of Interest"
        ]
        8 => array:2 [
          "identificador" => "s0085"
          "titulo" => "Acknowledgements"
        ]
        9 => array:1 [
          "titulo" => "References"
        ]
      ]
    ]
    "pdfFichero" => "main.pdf"
    "tienePdf" => true
    "fechaRecibido" => "2014-08-15"
    "fechaAceptado" => "2014-10-07"
    "PalabrasClave" => array:1 [
      "en" => array:1 [
        0 => array:4 [
          "clase" => "keyword"
          "titulo" => "Keywords"
          "identificador" => "xpalclavsec1117076"
          "palabras" => array:4 [
            0 => "Collagen III"
            1 => "Liver biopsy"
            2 => "Metalloproteinases"
            3 => "Non-invasive"
          ]
        ]
      ]
    ]
    "tieneResumen" => true
    "resumen" => array:1 [
      "en" => array:2 [
        "titulo" => "Abstract"
        "resumen" => "<span id="abs0010" class="elsevierStyleSection elsevierViewall"><p id="sp0040" class="elsevierStyleSimplePara elsevierViewall"><span class="elsevierStyleBold">Background and rationale for the study</span>&#46; The assessment of liver fibrosis provides useful information not only for diagnosis but also for therapeutic decision&#46; This study was concerned with determining the levels of collagen III and its degrading enzyme matrix metalloproteinase-1 &#40;MMP-1&#41; as direct and complementary markers for liver fibrosis staging&#46;</p><p id="sp1040" class="elsevierStyleSimplePara elsevierViewall"><span class="elsevierStyleBold">Results</span>&#46; A total of 269 chronic hepatitis C patients constituted this study&#46; Western blotting was used for identifying collagen III and MMP-1 in serum samples&#46; As a result&#44; collagen III and MMP-1 were identified&#44; respectively&#44; at 70 and 245 kDa using their respective mono-specific antibodies&#46; These two markers were quantified in sera of patients using ELISA&#46; Next&#44; Fibro-check was constructed combining collagen III and MMP-1 together with other indirect markers which reflect alteration in hepatic functions that proved useful to stage liver fibrosis&#46; Fibro-check produced area under the receiver-operating characteristic curve &#40;AUC&#41; 0&#46;91 and 0&#46;83 for significant &#40;F2-F4&#41; and cirrhosis &#40;F4&#41;&#44; respectively&#46; Additionally&#44; we estimated the performance of Fibro-check in comparison with aspartate to platelet ratio index &#40;APRI&#41; and fibrosis index&#46; Fibro-check seems to be more efficient than both of them&#46; Fibro-check was then applied to the validation study to test its accuracy and reproducibility showing AUCs 0&#46;90 for F2-F4 and 0&#46;86 for F4&#46;</p><p id="sp1050" class="elsevierStyleSimplePara elsevierViewall"><span class="elsevierStyleBold">Conclusions</span>&#46; Fibro-check combining &#8216;direct&#8217; and &#8216;indirect&#8217; markers using a mathematical formula may improve the staging of liver fibrosis with a high degree of accuracy and seems more efficient than APRI and Fibrosis index in this group of Egyptian patients&#46;</p></span>"
      ]
    ]
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          "en" => "<p id="sp0005" class="elsevierStyleSimplePara elsevierViewall">Areas under receiver-operating characteristic curve &#40;AUCs&#41; for A&#46; Collagen III with an AUC of 0&#46;75&#44; B&#46; MMP-1 with an AUC of 0&#46;70&#44; C&#46; Collagen&#47;MMP-1 ratio &#40;CMR&#41; with an AUC of 0&#46;80 for predicting significant fibrosis &#40;F2-F4&#41; in chronic hepatitis C patients in the estimation study&#46; Each point on the ROC plot represents a sensitivity&#47;specificity pair corresponding to a particular decision threshold&#46; An AUC of 1&#46;0 is characteristic of an ideal test whereas an AUC of 0&#46;5 or less indicates a test of no diagnostic value&#46;</p>"
        ]
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        "etiqueta" => "Figure 2"
        "tipo" => "MULTIMEDIAFIGURA"
        "mostrarFloat" => true
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          "en" => "<p id="sp0010" class="elsevierStyleSimplePara elsevierViewall">Area under the ROC curve for Fibro-check and comparison with APRI and Fibrosis index for predicting &#40;A&#41; significant fibrosis&#44; &#40;B&#41; cirrhosis in chronic hepatitis C patients in the estimation study &#40;n &#61; 168&#41;&#46; Calculations for Fibro-check&#44; APRI and fibrosis index are shown in <a class="elsevierStyleCrossRef" href="#t0015">table 3</a>&#46;</p>"
        ]
      ]
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          "leyenda" => "<p id="np0005" class="elsevierStyleSimplePara elsevierViewall">Variables were expressed as mean &#177; SEM&#46;</p>"
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                  <table border="0" frame="\n
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                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Variable&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Estimation group &#40;n &#61; 168&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-head\n
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                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Validation group &#40;n &#61; 101&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">P value<a class="elsevierStyleCrossRef" href="#tblfn0015"><span class="elsevierStyleSup">c</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td" title="\n
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                  \t\t\t\t">Age &#40;years&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">43&#46;7 &#177; 0&#46;5&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
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                  \t\t\t\t">45&#46;2 &#177; 0&#46;5&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
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                  \t\t\t\t  " align="left" valign="\n
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                  \t\t\t\t">NS&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t">AST &#40;U&#47;L&#41;<a class="elsevierStyleCrossRef" href="#tblfn0005"><span class="elsevierStyleSup">a</span></a>&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t">55&#46;9 &#177; 3&#46;4&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t">NS&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t">ALT &#40;U&#47;L&#41;<a class="elsevierStyleCrossRef" href="#tblfn0005"><span class="elsevierStyleSup">a</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">62&#46;0 &#177; 2&#46;7&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">58&#46;5 &#177; 3&#46;7&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">NS&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">AST&#47; ALT &#40;AAR&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">0&#46;9 &#177; 0&#46;03&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">1&#46;0 &#177; 0&#46;04&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">NS&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">ALP &#40;U&#47;L&#41;<a class="elsevierStyleCrossRef" href="#tblfn0005"><span class="elsevierStyleSup">a</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">84&#46;3 &#177; 4&#46;6&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">87&#46;4 &#177; 5&#46;7&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">NS&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Albumin &#40;g&#47;dL&#41;<a class="elsevierStyleCrossRef" href="#tblfn0005"><span class="elsevierStyleSup">a</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">4&#46;2 &#177; 0&#46;04&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">4&#46;0 &#177; 0&#46;05&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">NS&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Total bilirubin &#40;mg&#47;dL&#41;<a class="elsevierStyleCrossRef" href="#tblfn0005"><span class="elsevierStyleSup">a</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">0&#46;9 &#177; 0&#46;04&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">1&#46;0 &#177; 0&#46;06&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">NS&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Platelet count &#40;109&#47;L&#41;<a class="elsevierStyleCrossRef" href="#tblfn0005"><span class="elsevierStyleSup">a</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">181 &#177; 4&#46;6&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">176 &#177; 0&#46;6&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">NS&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">APRI<a class="elsevierStyleCrossRef" href="#tblfn0010"><span class="elsevierStyleSup">b</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">1&#46;0 &#177; 0&#46;07&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">0&#46;9 &#177; 0&#46;1&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">NS&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">AFP &#40;U&#47;L&#41;<a class="elsevierStyleCrossRef" href="#tblfn0005"><span class="elsevierStyleSup">a</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">6&#46;4 &#177; 0&#46;8&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">6&#46;8 &#177; 1&#46;1&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">NS&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Collagen III &#40;&#956;g&#47;mL&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">9&#46;0 &#177; 0&#46;4&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">8&#46;6 &#177; 0&#46;4&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">NS&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">MMP-1 &#40;&#956;g&#47;mL&#41;<a class="elsevierStyleCrossRef" href="#tblfn0010"><span class="elsevierStyleSup">b</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">6&#46;6 &#177; 0&#46;6&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">7&#46;2 &#177; 0&#46;8&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">NS&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Collagen III&#47; MMP-1 &#40;CMR&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">3&#46;7 &#177; 0&#46;4&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">4&#46;2 &#177; 0&#46;5&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">NS&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Metavir fibrosis stages&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">n &#40;&#37;&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">n &#40;&#37;&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">F1&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">89 &#40;53&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">51 &#40;50&#46;5&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">F2&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">31 &#40;18&#46;5&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">13 &#40;12&#46;9&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">F3&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">14 &#40;8&#46;3&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">14 &#40;13&#46;9&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">F4&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">34 &#40;20&#46;2&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">23 &#40;22&#46;8&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr></tbody></table>
                  """
              ]
              "imagenFichero" => array:1 [
                0 => "xTab2046995.png"
              ]
            ]
          ]
          "notaPie" => array:3 [
            0 => array:3 [
              "identificador" => "tblfn0005"
              "etiqueta" => "a"
              "nota" => "<p class="elsevierStyleNotepara" id="npar0005">Reference values&#58; aspartate aminotransferase &#40;AST&#41; &#40;male up to 37 U&#47;L&#44; female up to 31 U&#47;L&#41;&#59; alanine aminotransferase &#40;ALT&#41; &#40;male up to 41 U&#47;L&#44; female up to 31 U&#47;L&#41;&#59; alkaline phosphatase &#40;ALP&#41; 22-92 U&#47;L&#59; albumin 3&#46;8-5&#46;4 g&#47;dL&#59; total bilirubin up to 1 mg&#47;dL&#59; platelet count 150-400 &#215; 10<span class="elsevierStyleSup">9</span>&#47;L&#59; alpha fetoprotein &#40;AFP&#41; up to 10 U&#47;L&#46;</p>"
            ]
            1 => array:3 [
              "identificador" => "tblfn0010"
              "etiqueta" => "b"
              "nota" => "<p class="elsevierStyleNotepara" id="npar0010">APRI&#58; &#91;&#40;AST &#40;U&#47;L&#41;&#47;upper limits of normal&#41;&#47;platelet count &#40;10<span class="elsevierStyleSup">9</span>&#47;L&#41;&#93; &#215; 100&#59; MMP-1&#58; matrix metalloproteinase-1&#46;</p>"
            ]
            2 => array:3 [
              "identificador" => "tblfn0015"
              "etiqueta" => "c"
              "nota" => "<p class="elsevierStyleNotepara" id="npar0015">P &#62; 0&#46;05 is considered non significant &#40;NS&#41;&#59; P &#60; 0&#46;05 is considered significant&#46;</p>"
            ]
          ]
        ]
        "descripcion" => array:1 [
          "en" => "<p id="sp0015" class="elsevierStyleSimplePara elsevierViewall">Comparison of patient characteristics in the estimation and validation groups&#46;</p>"
        ]
      ]
      3 => array:7 [
        "identificador" => "t0010"
        "etiqueta" => "Table 2"
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                  \t\t\t\t">10&#46;8 &#177; 2&#46;7&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#60; 0&#46;0001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Collagen III &#40;&#956;g&#47;mL&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">6&#46;9 &#177; 0&#46;4&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">10&#46;5 &#177; 0&#46;9&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">11&#46;8 &#177; 0&#46;7&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">12&#46;8 &#177; 1&#46;0&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#60; 0&#46;0001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">MMP-1 &#40;&#956;g&#47;mL&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">8&#46;8 &#177; 0&#46;9&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">3&#46;4 &#177; 0&#46;6&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">3&#46;2 &#177; 0&#46;4&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">3&#46;0 &#177; 0&#46;4&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#60; 0&#46;0001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">CMR<a class="elsevierStyleCrossRef" href="#tblfn0025"><span class="elsevierStyleSup">b</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">2&#46;2 &#177; 0&#46;3&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">5&#46;7 &#177; 1&#46;2&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">7&#46;1 &#177; 0&#46;9&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">8&#46;2 &#177; 1&#46;3&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#60; 0&#46;0001&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr></tbody></table>
                  """
              ]
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                0 => "xTab2046996.png"
              ]
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            0 => array:3 [
              "identificador" => "tblfn0020"
              "etiqueta" => "a"
              "nota" => "<p class="elsevierStyleNotepara" id="npar0020">Reference values&#58; aspartate aminotransferase &#40;AST&#41; &#40;male up to 37 U&#47;L&#44; female up to 31 U&#47;L&#41;&#59; alanine aminotransferase &#40;ALT&#41; &#40;male up to 41 U&#47;L&#44; female up to 31 U&#47;L&#41;&#59; alkaline phosphatase &#40;ALP&#41; 22-92 U&#47;L&#59; albumin 3&#46;8-5&#46;4 g&#47;dL&#59; total bilirubin &#40;T&#46; bilirubin&#41; up to 1 mg&#47;dL&#59; platelet count 150-400 &#215; 10<span class="elsevierStyleSup">9</span>&#47;L&#59; alpha fetoprotein &#40;AFP&#41; up to 10 U&#47;L&#46;</p>"
            ]
            1 => array:3 [
              "identificador" => "tblfn0025"
              "etiqueta" => "b"
              "nota" => "<p class="elsevierStyleNotepara" id="npar0025">APRI&#58; AST level &#40;U&#47;L&#41;&#47;40 &#40;upper limits of normal&#41;&#47;platelets count &#40;10<span class="elsevierStyleSup">9</span>&#47;L&#41; &#215; 100&#46; CMR&#58; Collagen III&#47; MMP-1 ratio&#46;</p>"
            ]
            2 => array:3 [
              "identificador" => "tblfn0030"
              "etiqueta" => "c"
              "nota" => "<p class="elsevierStyleNotepara" id="npar0030">P &#62; 0&#46;05 is considered non significant&#59; P &#60; 0&#46;05 is considered significant&#59; P &#60; 0&#46;001 is considered very significant and P &#60; 0&#46;0001 is considered extremely significant&#46;</p>"
            ]
          ]
        ]
        "descripcion" => array:1 [
          "en" => "<p id="sp0020" class="elsevierStyleSimplePara elsevierViewall">Variables associated with the presence of significant fibrosis &#40;F2-F4&#41; by univariate analysis in the estimation group &#40;n &#61; 168&#41;&#46;</p>"
        ]
      ]
      4 => array:7 [
        "identificador" => "t0015"
        "etiqueta" => "Table 3"
        "tipo" => "MULTIMEDIATABLA"
        "mostrarFloat" => true
        "mostrarDisplay" => false
        "tabla" => array:2 [
          "tablatextoimagen" => array:1 [
            0 => array:2 [
              "tabla" => array:1 [
                0 => """
                  <table border="0" frame="\n
                  \t\t\t\t\tvoid\n
                  \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Fibrosis test<span class="elsevierStyleSup">Ref&#46;</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Calculation<a class="elsevierStyleCrossRef" href="#tblfn0035"><span class="elsevierStyleSup">a</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Fibro-check&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#91;CMR &#215; AFP &#40;U&#47;L&#41; &#215; AAR&#47;platelet count &#40;10<span class="elsevierStyleSup">9</span>&#47;L&#41;&#93;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">APRI<span class="elsevierStyleSup">9</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#91;&#40;AST&#47;upper limit of normal&#41;&#47;platelet count &#40;10<span class="elsevierStyleSup">9</span>&#47;L&#41;&#93; &#215; 100&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Fibrosis index<span class="elsevierStyleSup">10</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#91;8&#46;0-0&#46;01 &#215; platelet count &#40;10<span class="elsevierStyleSup">9</span>&#47;L&#41;-albumin &#40;g&#47;dL&#41;&#93;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr></tbody></table>
                  """
              ]
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                0 => "xTab2046993.png"
              ]
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            0 => array:3 [
              "identificador" => "tblfn0035"
              "etiqueta" => "a"
              "nota" => "<p class="elsevierStyleNotepara" id="npar0035">CMR&#58; collagen III&#47; MMP-1 ratio&#59; AFP&#58; alpha fetoprotein&#59; AAR&#58; aspartate aminotransferase &#40;AST&#41;&#47;alanine aminotransferase &#40;ALT&#41; ratio&#46;</p>"
            ]
          ]
        ]
        "descripcion" => array:1 [
          "en" => "<p id="sp0025" class="elsevierStyleSimplePara elsevierViewall">Calculations of fibrosis tests in comparison with Fibro-check in the present study&#46;</p>"
        ]
      ]
      5 => array:7 [
        "identificador" => "t0020"
        "etiqueta" => "Table 4"
        "tipo" => "MULTIMEDIATABLA"
        "mostrarFloat" => true
        "mostrarDisplay" => false
        "tabla" => array:2 [
          "tablatextoimagen" => array:1 [
            0 => array:2 [
              "tabla" => array:1 [
                0 => """
                  <table border="0" frame="\n
                  \t\t\t\t\tvoid\n
                  \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Fibrosis test<span class="elsevierStyleSup">Ref&#46;</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Cutoff<a class="elsevierStyleCrossRef" href="#tblfn0040"><span class="elsevierStyleSup">a</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Sn<a class="elsevierStyleCrossRef" href="#tblfn0040"><span class="elsevierStyleSup">a</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Sp<a class="elsevierStyleCrossRef" href="#tblfn0040"><span class="elsevierStyleSup">a</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">PPV<a class="elsevierStyleCrossRef" href="#tblfn0040"><span class="elsevierStyleSup">a</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">NPV<a class="elsevierStyleCrossRef" href="#tblfn0040"><span class="elsevierStyleSup">a</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Significant fibrosis &#40;F2-F4&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Fibro-check<a class="elsevierStyleCrossRef" href="#tblfn0040"><span class="elsevierStyleSup">a</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#62; 0&#46;05&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">82&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">84&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">82&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">84&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">APRI<span class="elsevierStyleSup">9</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#62; 1&#46;5&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">29&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">96&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">85&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">60&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Fibrosis index<span class="elsevierStyleSup">10</span>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#8805; 2&#46;1&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">57&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">73&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
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                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t">&#62; 0&#46;1&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t</td><td class="td" title="\n
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                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">METAVIR stages&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">P value<a class="elsevierStyleCrossRef" href="#tblfn0050"><span class="elsevierStyleSup">b</span></a>&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Sn<a class="elsevierStyleCrossRef" href="#tblfn0045"><span class="elsevierStyleSup">a</span></a>&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Sp<a class="elsevierStyleCrossRef" href="#tblfn0045"><span class="elsevierStyleSup">a</span></a>&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">PPV<a class="elsevierStyleCrossRef" href="#tblfn0045"><span class="elsevierStyleSup">a</span></a>&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">NPV<a class="elsevierStyleCrossRef" href="#tblfn0045"><span class="elsevierStyleSup">a</span></a>&nbsp;\t\t\t\t\t\t\n
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Article information

ISSN: 16652681
Original language: English

DOI:10.1016/S1665-2681(19)30785-9

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Year/Month	Html	Pdf	Total

2024 October	9	4	13
2024 September	17	5	22
2024 August	19	10	29
2024 July	18	6	24
2024 June	15	2	17
2024 May	22	8	30
2024 April	7	7	14
2024 March	31	3	34
2024 February	32	2	34
2024 January	27	7	34
2023 December	24	8	32
2023 November	30	7	37
2023 October	34	13	47
2023 September	18	9	27
2023 August	14	10	24
2023 July	18	9	27
2023 June	22	4	26
2023 May	24	4	28
2023 April	17	2	19
2023 March	11	3	14
2023 February	11	6	17
2023 January	13	17	30
2022 December	22	2	24
2022 November	13	11	24
2022 October	21	11	32
2022 September	10	6	16
2022 August	15	10	25
2022 July	21	9	30
2022 June	16	6	22
2022 May	32	7	39
2022 April	29	7	36
2022 March	22	12	34
2022 February	29	8	37
2022 January	50	14	64
2021 December	21	14	35
2021 November	12	8	20
2021 October	18	9	27
2021 September	8	11	19
2021 August	6	4	10
2021 July	11	7	18
2021 June	8	6	14
2021 May	16	5	21
2021 April	36	6	42
2021 March	11	5	16
2021 February	43	10	53
2021 January	5	11	16
2020 December	12	4	16
2020 November	5	11	16
2020 October	10	4	14
2020 September	12	5	17
2020 August	8	4	12
2020 July	5	1	6
2020 June	4	3	7
2020 May	13	15	28
2020 April	8	2	10
2020 March	5	5	10
2020 February	6	4	10
2020 January	7	8	15
2019 December	10	10	20
2019 November	4	1	5
2019 October	0	2	2
2019 September	2	4	6
2019 August	1	1	2
2019 July	9	10	19
2019 June	7	13	20

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