was read the article
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Fiorella, J.L. Marenco, J.M. Mascarós, Á. Borque-Fernando, L.M. Esteban, A. Calatrava, B. Pastor, J.A. López-Guerrero, J. Rubio-Briones" "autores" => array:9 [ 0 => array:3 [ "nombre" => "D." "apellidos" => "Fiorella" "referencia" => array:2 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">a</span>" "identificador" => "aff0005" ] 1 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">♢</span>" "identificador" => "fn0005" ] ] ] 1 => array:3 [ "nombre" => "J.L." "apellidos" => "Marenco" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">a</span>" "identificador" => "aff0005" ] ] ] 2 => array:3 [ "nombre" => "J.M." "apellidos" => "Mascarós" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">a</span>" "identificador" => "aff0005" ] ] ] 3 => array:3 [ "nombre" => "Á." 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"apellidos" => "López-Guerrero" "referencia" => array:3 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">e</span>" "identificador" => "aff0025" ] 1 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">f</span>" "identificador" => "aff0030" ] 2 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">g</span>" "identificador" => "aff0035" ] ] ] 8 => array:4 [ "nombre" => "J." "apellidos" => "Rubio-Briones" "email" => array:1 [ 0 => "jrubio@fivo.org" ] "referencia" => array:3 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">a</span>" "identificador" => "aff0005" ] 1 => array:2 [ "etiqueta" => "*" "identificador" => "cor0005" ] 2 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">♢</span>" "identificador" => "fn0005" ] ] ] ] "afiliaciones" => array:7 [ 0 => array:3 [ "entidad" => "Departamento de Urología, Instituto Valenciano de Oncología, Valencia, Spain" "etiqueta" => "a" "identificador" => "aff0005" ] 1 => array:3 [ "entidad" => "Departamento de Urología, IIS-Aragón, Hospital Universitario Miguel Servet, Zaragoza, Spain" "etiqueta" => "b" "identificador" => "aff0010" ] 2 => array:3 [ "entidad" => "Departamento de Matemáticas Aplicadas, Escuela Universitaria Politécnica de La Almunia, Universidad de Zaragoza, La Almuniade Doña Godina, Zaragoza, Spain" "etiqueta" => "c" "identificador" => "aff0015" ] 3 => array:3 [ "entidad" => "Departamento de Patología, Instituto Valenciano de Oncología, Valencia, Spain" "etiqueta" => "d" "identificador" => "aff0020" ] 4 => array:3 [ "entidad" => "Laboratorio de Biología Molecular, Instituto Valenciano de Oncología, Valencia, Spain" "etiqueta" => "e" "identificador" => "aff0025" ] 5 => array:3 [ "entidad" => "IVO-CIPF Joint Research Unit of Cancer, Centro de Investigación Príncipe Felipe (CIPF), Valencia, Spain" "etiqueta" => "f" "identificador" => "aff0030" ] 6 => array:3 [ "entidad" => "Departamento de Patología, Facultad de Medicina, Universidad Católica de Valencia San Vicente Mártir, Valencia, Spain" "etiqueta" => "g" "identificador" => "aff0035" ] ] "correspondencia" => array:1 [ 0 => array:3 [ "identificador" => "cor0005" "etiqueta" => "⁎" "correspondencia" => "Corresponding author." ] ] ] ] "titulosAlternativos" => array:1 [ "es" => array:1 [ "titulo" => "Papel de PCA3 y SelectMDx en la optimización de la vigilancia activa en el cáncer de próstata" ] ] "resumenGrafico" => array:2 [ "original" => 0 "multimedia" => array:8 [ "identificador" => "fig0015" "etiqueta" => "Figure 3" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr3.jpeg" "Alto" => 760 "Ancho" => 2508 "Tamanyo" => 146315 ] ] "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at0015" "detalle" => "Figure " "rol" => "short" ] ] "descripcion" => array:1 [ "en" => "<p id="spar0015" class="elsevierStyleSimplePara elsevierViewall">(a) ROC curves for SelectMDx, PCA3, PSA, PSAd, ERSPC-RC and PBCG for pathological progression; (b) Harrel’s C-index for for SelectMDx, PCA3, PSA, PSAd, ERSPC-RC, PBCG and model with SelectMDx and PCA3.</p>" ] ] ] "textoCompleto" => "<span class="elsevierStyleSections"><span id="sec0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0065">Introduction</span><p id="par0005" class="elsevierStylePara elsevierViewall">Prostate cancer (PCa) screening demonstrated a decrease in mortality according to the 16 years follow up results of the European Randomized study of Screening for Prostate Cancer (ERSPC), with 570 men screened and 18 diagnosed in order to save a live<a class="elsevierStyleCrossRef" href="#bib0005"><span class="elsevierStyleSup">1</span></a>. In order to improve detection of clinically significant PCa, the use of serum and urine biomarkers has been investigated and validated<a class="elsevierStyleCrossRefs" href="#bib0010"><span class="elsevierStyleSup">2–4</span></a>. However, the role of biomarkers in PCa diagnosis have been largely superseded by multiparametric magnetic resonance image (mpMRI)<a class="elsevierStyleCrossRef" href="#bib0025"><span class="elsevierStyleSup">5</span></a>. To avoid overtreatment of indolent PCa, active surveillance (AS) is a recommended management option across all guidelines<a class="elsevierStyleCrossRef" href="#bib0030"><span class="elsevierStyleSup">6</span></a>. This is particularly supported by low cancer-specific mortality at long-term follow up for low risk PCa<a class="elsevierStyleCrossRef" href="#bib0035"><span class="elsevierStyleSup">7</span></a>.</p><p id="par0010" class="elsevierStylePara elsevierViewall">Just like mpMRI was initially evaluated for PCa diagnosis and then applied to monitor low grade PCa<a class="elsevierStyleCrossRef" href="#bib0040"><span class="elsevierStyleSup">8</span></a>, the role of biomarkers to predict reclassification in AS has also been investigated. This is the case of 4KScore® and Prostate Health Index (<span class="elsevierStyleItalic">phi</span>) tests on serum which help to identify men at larger risk of reclassification on confirmatory biopsy<a class="elsevierStyleCrossRef" href="#bib0045"><span class="elsevierStyleSup">9</span></a>. Further, Oncotype Dx Genomic Prostate Score® (GPS), Prolaris® and Decipher® tests predicted adverse pathology features on radical prostatectomy specimen<a class="elsevierStyleCrossRef" href="#bib0050"><span class="elsevierStyleSup">10</span></a>. On the other hand, urine PCA3 levels were not correlated with reclassification risk at short term<a class="elsevierStyleCrossRef" href="#bib0055"><span class="elsevierStyleSup">11</span></a>. Other non-commercially available kits are being investigated with promising results albeit in an early research phase<a class="elsevierStyleCrossRefs" href="#bib0060"><span class="elsevierStyleSup">12,13</span></a>.</p><p id="par0015" class="elsevierStylePara elsevierViewall">Our aim is to evaluate the role of PCA3 and SelectMDx obtained before PCa diagnosis or confirmatory biopsy once AS has been suggested to predict pathological progression free survival (PPFS) on further follow up biopsies on a single centre AS cohort.</p></span><span id="sec0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0070">Material and methods</span><p id="par0020" class="elsevierStylePara elsevierViewall">542 patients were enrolled in a single centre AS protocol from 2009 to 2019. Eighty-six of them had urine samples obtained previously to PCa diagnosis or during their confirmatory period (before confirmation biopsy in the following 12 months) and had the results for both PCA3 and SelectMDx. Urine samples were stored at -80 °C at the Biobank of our center. Patient recruitment and sampling procedures were carried out following all local regulatory requirements and laws, in accordance with the Declaration of Helsinki, and after approval from our Ethics Committee (CAPROSIVO, PROMETEO/2016/103) on May 2015. All patients signed a written informed consent before entrance in the study.</p><p id="par0025" class="elsevierStylePara elsevierViewall">Selection criteria for AS were life expectancy greater than 10 years, stage cT1, Grade Group I (Gleason 3 + 3), PSA ≤10 ng/mL, PSA density (PSAd) <0.20 ng/mL, ≤2 positive cores with less of 50% cancer involvement or less than 5 mm in length. We also accepted for AS men older than 70 years with GGII (3 + 4) with less than 10% of Gleason 4 and no additional of the previous mentioned variables for the GGI patients. Men who did have their confirmatory biopsy after 12 months of AS entry were excluded for analysis. No patient was taking 5-α-reductase inhibitors.</p><p id="par0030" class="elsevierStylePara elsevierViewall">Urine (20–30 mL) was collected after a standardized digital rectal examination (DRE) following recommendations for the PCA3 test (Physician Brochure for the PRoGensa® PCA3 assay). 2.5 mL were processed using the Progensa PCA3 urine specimen transport kit (Hologic, Inc, San Diego) and then stored at −80 °C at our Biobank. For SelectMDx analysis a pilot set of 30 samples was shipped on dry ice to the testing lab (MDxHealth, SA, Nijmegen, NL), to verify mRNA stability and ensure valid assay results. MDxHealth provided urinary mRNA‐based risk scores blinded to biopsy results. The test measured mRNA levels of <span class="elsevierStyleItalic">distal-less homeobox 1</span> (<span class="elsevierStyleItalic">DLX1</span>) and <span class="elsevierStyleItalic">homeobox C6</span> (<span class="elsevierStyleItalic">HOXC6</span>) genes in a post-DRE urine specimen and combines these with serum PSA, PSAd, DRE status, age, and family history of PCa<a class="elsevierStyleCrossRef" href="#bib0070"><span class="elsevierStyleSup">14</span></a>.</p><p id="par0035" class="elsevierStylePara elsevierViewall">Transrectal ultrasonography (TRUS) derived total prostate volume was calculated using the prostate ellipse formula (0.52 × length × width × height). On initial biopsy 10–12 systematic TRUS cores were taken. Confirmatory biopsy consisted of transperineal 30 cores plus targeted cores when a suspicious mpMRI area was identified. All biopsy specimens were evaluated by a single experienced uro-pathologist (AC). mpMRI was not routinely performed in this cohort given the inclusion period; PIRADS-v2 score was included when available.</p><span id="sec0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0075">Statistical analysis</span><p id="par0040" class="elsevierStylePara elsevierViewall">The main objective of the study was to evaluate the impact of PCA3 and SelectMDx, individually and combined, in predicting pathological progression, defined as an increase in Grade Group or by means of PCa volumen increase (>3 positive cores and >3 involved prostatic areas in transperineal biopsy) or any core with >5 mm or >50% involvement, independently of GG. Univariate and multivariate analysis were performed to correlate PCA3 and SelectMDx scores as well as clinic and pathological variables such as age, PSAd, DRE, Gleason score at diagnoses and PIRADS score when available with pathological progression (PP).</p><p id="par0045" class="elsevierStylePara elsevierViewall">Chi square test was used to compare categorical variables. To compare continuous variables, t-student was used when normality could be accepted and U Mann–Whitney otherwise. Kaplan–Meier curves were used for survival analysis and the Log-Rank test to compare groups. When feasible, Cox Proportional Hazards Regression models were applied to predict PP. Step function was used to select the best model according to Akaike information criterion (AIC). Discrimination ability was estimated using C-index. Sensitivities, specificities, positive, and negative predictive values were estimated at 5 years of follow up. To set “optimal” cut-off point for the biomarkers, Youden index was used<a class="elsevierStyleCrossRef" href="#bib0075"><span class="elsevierStyleSup">15</span></a>. Two-sided tests with a level of significance of 5% were used. Data analysis was performed using R language programming v. 3.6.3 (The R Foundation for statistical computing, Vienna, Austria)<a class="elsevierStyleCrossRef" href="#bib0080"><span class="elsevierStyleSup">16</span></a>.</p></span></span><span id="sec0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0080">Results</span><p id="par0050" class="elsevierStylePara elsevierViewall"><a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a> shows clinical characteristics of our 86 selected patients. Mean follow up for these patients from their PCa diagnoses was 69.2 months (standard deviation: 25.7 months) with a median of 69.92 (range: 48–91) months.</p><elsevierMultimedia ident="tbl0005"></elsevierMultimedia><p id="par0055" class="elsevierStylePara elsevierViewall">During the first year of follow up, just 7 patients did not have a properly confirmatory biopsy due to different reasons (transperineal initial biopsy in one case and patient preferences or intercurrent diseases that did it not advisable in the rest); 20 out of 79 (25.32%) were reclassificated at the confirmatory biopsy. In the univariate study neither age, PSAd, DRE, PCA3, SelectMDx, Gleason score nor PIRADS classification showed statistically significant differences in terms of reclassification on confirmatory biopsy.</p><p id="par0060" class="elsevierStylePara elsevierViewall">Irrespectively of timing for biopsy, all 86 patients had at least one biopsy after entrance in AS; 41 patients (47.67%) had one biopsy, 30 patients (34.88%) had two and 15 patients (17.44%) had three or more biopsies. At 5 years, PPFS was 46.48% (95%confidence interval (CI) 36.42–59.32).</p><p id="par0065" class="elsevierStylePara elsevierViewall">Out of all 86 patients, 45 (52.33%) suffered PP, 43 of them before 5 years. The univariate analysis with the aforementioned variables (<a class="elsevierStyleCrossRef" href="#tbl0010">Table 2</a>) showed that SelectMDx correlated with PP during follow up with a hazard ratio (HR) of 1.035 (95%CI 1.012−1.057; p = 0.002). As can be observed in the box plot chart (<a class="elsevierStyleCrossRef" href="#fig0005">Fig. 1</a>), median SelectMDx value was double for the group that presented PP (<a class="elsevierStyleCrossRef" href="#tbl0010">Table 2</a>), obtaining a value in the Harrel’s C-index of 0.670 (95%CI 0.529−0.810). Using STEP function, SelectMDx and PCA3 had the best figures compared to different combinations of the rest of the variable but PCA3 remains in the model without statistically significant.</p><elsevierMultimedia ident="tbl0010"></elsevierMultimedia><elsevierMultimedia ident="fig0005"></elsevierMultimedia><p id="par0070" class="elsevierStylePara elsevierViewall">Using the Youden index, the “optimal” SelectMDx cut-off for PP was 5. <a class="elsevierStyleCrossRef" href="#tbl0015">Table 3</a> shows the association of SelectMDx at this cut-off with the PP rate at 5 years, resulting in a sensibility (S), specificity (Sp), negative predictive value (NPV) and positive predictive value (PPV) of 69.77 (95%CI 53.87–82.82), 67.44 (95%CI 51.46–80.02), 69.05 (95%CI 52.91–82.38) and 68.18 (95%CI 52.42–81.39) respectively. For PCA3, “optimal” cut-off was set at 65 with a S of 51.16 (95%CI 35.46–66.69), Sp 74.42 (95%CI 58.83–86.48), NPV 60.38 (95%CI 46.00–73.55) and PPV of 66.67 (95%CI 48.17–82.04). <a class="elsevierStyleCrossRef" href="#fig0010">Fig. 2</a>a and b shows differences in PPFS based in a SelectMDx >5 and PCA3 > 65 cut-offs respectively. In both cases differences were found using the Log-rank test (p < 0.001 and p = 0.03 respectively). Estimated PPFS at 5 years for a patient with a SelectMDx >5 would be 27.57% (95%CI 16.33%–46.54%) obtaining a HR of 3.30 (95%CI 1.75–6.24) (p < 0.001). For another SelectMDx score cut-off such as 10, the estimated PPFS at 5 years would had been 16.30% (95%CI 5.95–44.71) with a HR of 3.10 (95%CI 1.32–4.36) (p < 0.001).</p><elsevierMultimedia ident="tbl0015"></elsevierMultimedia><elsevierMultimedia ident="fig0010"></elsevierMultimedia><p id="par0075" class="elsevierStylePara elsevierViewall">When we considered both biomarkers as a combined variable, we proposed a Cox regression model and then used Youden index for study PP based on obtained survival estimates, and then two groups were created, low and high risk. <a class="elsevierStyleCrossRef" href="#fig0010">Fig. 2</a>c shows differences in PPFS based in two groups. <a class="elsevierStyleCrossRef" href="#tbl0015">Table 3</a> show differences in PP based in the two groups. Estimated PPFS at 5 years for the high group was 34.82 (95%CI 23.71%–51.15%), somewhat similar to that obtained just with SelectMDx, with a HR of 2.93 (95%CI 1.31–6.59) (p < 0.01). On the other hand, the comparison of the AUC for PCA3, SelectMDx, PSA, PSAd and two known risk calculators (ERSPC and PBCG), built to detect high grade PCa in the setting of PCa diagnosis<a class="elsevierStyleCrossRefs" href="#bib0085"><span class="elsevierStyleSup">17,18</span></a>, shows that SelectMDx reported the best AUC, quite similar to the ERSPC-RC (<a class="elsevierStyleCrossRef" href="#fig0015">Fig. 3</a>a) to predict PP at 5 years. Finally, <a class="elsevierStyleCrossRef" href="#fig0015">Fig. 3</a>b shows the comparison of the Harrel’s C-index for PCA3, SelectMDx, PSA, PSAd, ERSPC, PBCG and model with SelectMDx and PCA3.</p><elsevierMultimedia ident="fig0015"></elsevierMultimedia></span><span id="sec0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0085">Discussion</span><p id="par0080" class="elsevierStylePara elsevierViewall">Active surveillance is the preferred approach for the clinical management of low and very low risk PCa, as stated in the contemporary guidelines<a class="elsevierStyleCrossRef" href="#bib0030"><span class="elsevierStyleSup">6</span></a>. Despite thorough selection criteria, Gleason upgrading rates of 29–34% in radical prostatectomy specimen have been reported<a class="elsevierStyleCrossRef" href="#bib0095"><span class="elsevierStyleSup">19</span></a>. In our own institution over the whole AS cohort (542 men) and with the above-mentioned criteria we observed a 44.42% PP rate over 5 years (data not shown).</p><p id="par0085" class="elsevierStylePara elsevierViewall">Therefore, there is still room for improvement to reduce reclassification, especially during the crucial patient selection and confirmation period, in order to reduce patient uncertainty, oncological risk and optimize number of follow-up re-biopsies which are unpleasant<a class="elsevierStyleCrossRef" href="#bib0100"><span class="elsevierStyleSup">20</span></a> and not exempt of complications<a class="elsevierStyleCrossRef" href="#bib0105"><span class="elsevierStyleSup">21</span></a>.</p><p id="par0090" class="elsevierStylePara elsevierViewall">Urinary and serum biomarkers have focused on PCa diagnosis, and lately on identifying high grade PCa<a class="elsevierStyleCrossRef" href="#bib0110"><span class="elsevierStyleSup">22</span></a>. However, to the best of our knowledge, none of them has been validated in the context of AS. 4KScore® test has been evaluated as a predictive variable for PP on confirmatory biopsy, showing that it could avoid 27% of biopsies setting at 7.5% cut-off<a class="elsevierStyleCrossRef" href="#bib0045"><span class="elsevierStyleSup">9</span></a>. Tissue biomarkers evaluate gene expression panels on the most representative biopsy core, predicting unfavourable features on radical prostatectomy specimen<a class="elsevierStyleCrossRef" href="#bib0115"><span class="elsevierStyleSup">23</span></a> and cancer specific mortality at ten years<a class="elsevierStyleCrossRefs" href="#bib0050"><span class="elsevierStyleSup">10,24</span></a>. Nevertheless, given the heterogeneity and multifocal nature of PCa, some authors argue that evaluating a single biopsy core might inadequately represent the whole cancerous burden<a class="elsevierStyleCrossRefs" href="#bib0125"><span class="elsevierStyleSup">25,26</span></a>.</p><p id="par0095" class="elsevierStylePara elsevierViewall">We have recently performed an external validation of SelectMDx for high grade PCa (HGPCa) diagnosis, showing more modest results compared to original publications (AUC for ≥ Grade Group 2 PCa of 0.749 (95%CI 0.690–0.807)<a class="elsevierStyleCrossRefs" href="#bib0020"><span class="elsevierStyleSup">4,14</span></a>. We had also evaluated PCA3 integrated in a clinical nomogram to detect HGPCa, showing an adequate discrimination ability, AUC 0.786 (95%CI 0.71–0.87)<a class="elsevierStyleCrossRef" href="#bib0135"><span class="elsevierStyleSup">27</span></a>.</p><p id="par0100" class="elsevierStylePara elsevierViewall">These 86 patients are representative of the AS population in our country as in a published Spanish AS registry, 98% men did not receive a pre-biopsy mpMRI<a class="elsevierStyleCrossRef" href="#bib0140"><span class="elsevierStyleSup">28</span></a>. The growing number of men candidate to AS together with a limited access to mpMRI results in many men being included in AS following a 12-core TRUS biopsy. Our results show that SelectMDx score was almost double in patients who experience PP (<a class="elsevierStyleCrossRef" href="#tbl0010">Table 2</a>), which concurs with previously published data<a class="elsevierStyleCrossRef" href="#bib0145"><span class="elsevierStyleSup">29</span></a>, albeit with a modest Harrel’s C-index of 0.670 (95%CI 0.529−0.810) (<a class="elsevierStyleCrossRef" href="#fig0015">Fig. 3</a>b). In our opinion SelectMDx is not to be considered an independent tool to decide shift to active treatment, however it can help to individualize follow up according to progression risk. Unlike mpMRI, SelectMDx lack the need for training, learning curve or interpretation errors which represent a clear advantage.</p><p id="par0105" class="elsevierStylePara elsevierViewall">These results highlight the importance of obtaining the precise SelectMDx score rather than the risk group categorization. Furthermore, internal validation of biomarkers is advised given that the performance and optimal cut-off values might differ from the original recommendations<a class="elsevierStyleCrossRefs" href="#bib0020"><span class="elsevierStyleSup">4,30</span></a>. For instance, the best value for PCA3 discrimination was 65, away from the originally proposed for diagnostic purposes (35).</p><p id="par0110" class="elsevierStylePara elsevierViewall">As expected, a combination of two-gene panel with 5 clinical variables in a model such as SelectMDx has a discriminatory ability frankly superior to a single urine biomarker such as PCA3, despite similar 5 years PPFS 27.97% (95%CI 14.84%–52.74%) and 27.57% (95%CI 16.33%–46.54%) respectively. So, the combination of biomarkers did not improve discrimination.</p><p id="par0115" class="elsevierStylePara elsevierViewall">Our research has some limitations. Namely, it is a retrospective cohort, a minority of patients underwent pre-biopsy mpMRI given the inclusion period, which might underestimate the added value of imaging. This in turn is not an accurate of the current AS scenario where all patients receive not only pre-biopsy but also follow up mpMRI plus systematic and targeted biopsies. However, we do think that these results can be useful for centres where mpMRI is not readily available or performance is not comparable to high volume centres.</p></span><span id="sec0030" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0090">Conclusions</span><p id="par0120" class="elsevierStylePara elsevierViewall">In the context of a low or very low risk PCa risk, SelectMDx > 5 predicts 5-years PPFS with a moderate discrimination ability outperforming PCA3. The combination of both did not improved results.</p></span><span id="sec0035" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0095">Financial disclosure</span><p id="par0125" class="elsevierStylePara elsevierViewall">This work has been supported by the PROMETEO 2016/103 grants from the Conselleria de Educación, Cultura y Deporte de la Generalitat Valenciana (Spain) and by the Asociación Contra el Cáncer de Algemesí (Spain).</p></span><span id="sec0040" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0100">Conflicts of interest</span><p id="par0130" class="elsevierStylePara elsevierViewall">MDxHealth provided SelectMDx score for the original validation study. No significant contribution was made to this current study.</p></span></span>" "textoCompletoSecciones" => array:1 [ "secciones" => array:13 [ 0 => array:3 [ "identificador" => "xres1592249" "titulo" => "Abstract" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0005" "titulo" => "Introduction & objectives" ] 1 => array:2 [ "identificador" => "abst0010" "titulo" => "Materials & methods" ] 2 => array:2 [ "identificador" => "abst0015" "titulo" => "Results" ] 3 => array:2 [ "identificador" => "abst0020" "titulo" => "Conclusions" ] ] ] 1 => array:2 [ "identificador" => "xpalclavsec1430491" "titulo" => "Keywords" ] 2 => array:3 [ "identificador" => "xres1592248" "titulo" => "Resumen" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0025" "titulo" => "Introducción y objetivos" ] 1 => array:2 [ "identificador" => "abst0030" "titulo" => "Materiales y métodos" ] 2 => array:2 [ "identificador" => "abst0035" "titulo" => "Resultados" ] 3 => array:2 [ "identificador" => "abst0040" "titulo" => "Conclusiones" ] ] ] 3 => array:2 [ "identificador" => "xpalclavsec1430492" "titulo" => "Palabras clave" ] 4 => array:2 [ "identificador" => "sec0005" "titulo" => "Introduction" ] 5 => array:3 [ "identificador" => "sec0010" "titulo" => "Material and methods" "secciones" => array:1 [ 0 => array:2 [ "identificador" => "sec0015" "titulo" => "Statistical analysis" ] ] ] 6 => array:2 [ "identificador" => "sec0020" "titulo" => "Results" ] 7 => array:2 [ "identificador" => "sec0025" "titulo" => "Discussion" ] 8 => array:2 [ "identificador" => "sec0030" "titulo" => "Conclusions" ] 9 => array:2 [ "identificador" => "sec0035" "titulo" => "Financial disclosure" ] 10 => array:2 [ "identificador" => "sec0040" "titulo" => "Conflicts of interest" ] 11 => array:2 [ "identificador" => "xack562746" "titulo" => "Acknowledgements" ] 12 => array:1 [ "titulo" => "References" ] ] ] "pdfFichero" => "main.pdf" "tienePdf" => true "fechaRecibido" => "2020-08-27" "fechaAceptado" => "2020-10-26" "PalabrasClave" => array:2 [ "en" => array:1 [ 0 => array:4 [ "clase" => "keyword" "titulo" => "Keywords" "identificador" => "xpalclavsec1430491" "palabras" => array:5 [ 0 => "Active surveillance" 1 => "Biomarkers" 2 => "PCA3" 3 => "Prostate cancer" 4 => "SelectMDx" ] ] ] "es" => array:1 [ 0 => array:4 [ "clase" => "keyword" "titulo" => "Palabras clave" "identificador" => "xpalclavsec1430492" "palabras" => array:5 [ 0 => "Vigilancia activa" 1 => "Biomarcadores" 2 => "PCA3" 3 => "Cáncer de próstata" 4 => "SelectMDx" ] ] ] ] "tieneResumen" => true "resumen" => array:2 [ "en" => array:3 [ "titulo" => "Abstract" "resumen" => "<span id="abst0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0010">Introduction & objectives</span><p id="spar0045" class="elsevierStyleSimplePara elsevierViewall">A not negligible percentage of patients included in active surveillance (AS) for low and very low risk prostate cancer (PCa) are reclassified in the confirmatory biopsy or have disease progression during follow-up. Our aim is to evaluate the role of PCA3 and SelectMDx, in an individual and combined way, in the prediction of pathological progression (PP) in a standard AS program.</p></span> <span id="abst0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0015">Materials & methods</span><p id="spar0050" class="elsevierStyleSimplePara elsevierViewall">Prospective and observational study comprised of 86 patients enrolled in an AS program from 2009 to 2019, with results for PCA3 and SelectMDx previous to PCa diagnosis or during their confirmatory period. Univariate and multivariate analysis were performed to correlate PCA3 and SelectMDx scores as well as clinical and pathological variables with PP-free survival (PPFS). The most reliable cut-offs for both biomarkers in the context of AS were defined.</p></span> <span id="abst0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0020">Results</span><p id="spar0055" class="elsevierStyleSimplePara elsevierViewall">SelectMDx showed statistically significant differences related to PPFS (HR 1.035, 95%CI: 1.012−1.057) (p = 0.002) with a C-index of 0.670 (95%CI: 0.529−0.810) and AUC of 0.714 (95%CI: 0.603−0.825) at 5 years. In our series, the most reliable cut-off point for SelectMDx was 5, with a sensitivity and specificity for PP of 69.8% and 67.4%, respectively. Same figure for PCA3 was 65, with a sensitivity and specificity for PP of 51.16% and 74.42%, respectively. The combination of both biomarkers did not improve the prediction of PP, C-index 0.630 (95%CI: 0.455−0.805).</p></span> <span id="abst0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0025">Conclusions</span><p id="spar0060" class="elsevierStyleSimplePara elsevierViewall">In the context of low or very low risk PCa, SelectMDx > 5 predicted 5 years PP free survival with a moderate discrimination ability outperforming PCA3. The combination of both tests did not improved outcomes.</p></span>" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0005" "titulo" => "Introduction & objectives" ] 1 => array:2 [ "identificador" => "abst0010" "titulo" => "Materials & methods" ] 2 => array:2 [ "identificador" => "abst0015" "titulo" => "Results" ] 3 => array:2 [ "identificador" => "abst0020" "titulo" => "Conclusions" ] ] ] "es" => array:3 [ "titulo" => "Resumen" "resumen" => "<span id="abst0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0035">Introducción y objetivos</span><p id="spar0065" class="elsevierStyleSimplePara elsevierViewall">Un porcentaje no despreciable de pacientes incluidos en programas de vigilancia activa (VA) para el cáncer de próstata (CaP) de bajo y muy bajo riesgo son reclasificados en la biopsia confirmatoria o desarrollan progresión de la enfermedad durante el seguimiento. Nuestro objetivo es evaluar el papel del PCA3 y el SelectMDx, de manera individual y combinada, para predecir la progresión patológica (PP) en un programa habitual de VA.</p></span> <span id="abst0030" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0040">Materiales y métodos</span><p id="spar0070" class="elsevierStyleSimplePara elsevierViewall">Estudio prospectivo y observacional que incluyó 86 pacientes inscritos en un protocolo de VA desde 2009 hasta 2019, con resultados de PCA3 y SelectMDx previos al diagnóstico de CaP o durante su periodo de confirmación. Se realizaron análisis univariantes y multivariantes para la correlación de las puntuaciones de PCA3 y SelectMDx, así como de las variables clínico-patológicas con la supervivencia libre de progresión patológica (SLPP). Se definieron los puntos de corte más fiables para ambos biomarcadores en el contexto de VA.</p></span> <span id="abst0035" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0045">Resultados</span><p id="spar0075" class="elsevierStyleSimplePara elsevierViewall">SelectMDx mostró diferencias estadísticamente significativas en relación con la SLPP (HR 1,035; IC del 95%: 1,012-1,057) (p = 0,002) con un índice C de 0,670 (IC del 95%: 0,529-0,810) y un AUC de 0,714 (IC del 95%: 0,603-0,825) a 5 años. En nuestra serie, el punto de corte más fiable para el SelectMDx fue 5, con una sensibilidad y especificidad para la PP del 69,8% y 67,4% respectivamente. El punto de corte del test PCA3 fue de 65, con una sensibilidad y especificidad para la PP del 51,16% y 74,42%, respectivamente. La combinación de ambos biomarcadores no mejoró la predicción de la PP, con un índice C de 0,630 (IC del 95%: 0,455-0,805).</p></span> <span id="abst0040" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0050">Conclusiones</span><p id="spar0080" class="elsevierStyleSimplePara elsevierViewall">En el contexto del CaP de bajo o muy bajo riesgo, SelectMDx > 5 predijo una supervivencia libre de PP de 5 años con una capacidad de discriminación moderada superando al PCA3. La combinación de ambos no mejoró los resultados.</p></span>" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0025" "titulo" => "Introducción y objetivos" ] 1 => array:2 [ "identificador" => "abst0030" "titulo" => "Materiales y métodos" ] 2 => array:2 [ "identificador" => "abst0035" "titulo" => "Resultados" ] 3 => array:2 [ "identificador" => "abst0040" "titulo" => "Conclusiones" ] ] ] ] "NotaPie" => array:2 [ 0 => array:2 [ "etiqueta" => "☆" "nota" => "<p class="elsevierStyleNotepara" id="npar0005">Please cite this article as: Fiorella D, Marenco JL, Mascarós JM, Borque-Fernando Á, Esteban LM, Calatrava A, et al. Papel de PCA3 y SelectMDx en la optimización de la vigilancia activa en el cáncer de próstata. Actas Urol Esp. 2021;45:439–446.</p>" ] 1 => array:3 [ "etiqueta" => "♢" "nota" => "<p class="elsevierStyleNotepara" id="npar0010">José Rubio‐Briones and Diego Fiorella contributed equally to this study and are co-authors.</p>" "identificador" => "fn0005" ] ] "multimedia" => array:6 [ 0 => array:8 [ "identificador" => "fig0005" "etiqueta" => "Figure 1" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr1.jpeg" "Alto" => 899 "Ancho" => 1508 "Tamanyo" => 51367 ] ] "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at0005" "detalle" => "Figure " "rol" => "short" ] ] "descripcion" => array:1 [ "en" => "<p id="spar0005" class="elsevierStyleSimplePara elsevierViewall">Box plot diagram for SelectMDx values regarding pathological progression.</p>" ] ] 1 => array:8 [ "identificador" => "fig0010" "etiqueta" => "Figure 2" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr2.jpeg" "Alto" => 4175 "Ancho" => 2280 "Tamanyo" => 519328 ] ] "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at0010" "detalle" => "Figure " "rol" => "short" ] ] "descripcion" => array:1 [ "en" => "<p id="spar0010" class="elsevierStyleSimplePara elsevierViewall">(a) Kaplan–Meyer curves for pathological progression free survival based in a SelectMDx cut-off of 5; (b) PCA3 cut-off of 65; (c) Kaplan–Meyer curves for pathological progression free survival based in a low and high risk.</p>" ] ] 2 => array:8 [ "identificador" => "fig0015" "etiqueta" => "Figure 3" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr3.jpeg" "Alto" => 760 "Ancho" => 2508 "Tamanyo" => 146315 ] ] "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at0015" "detalle" => "Figure " "rol" => "short" ] ] "descripcion" => array:1 [ "en" => "<p id="spar0015" class="elsevierStyleSimplePara elsevierViewall">(a) ROC curves for SelectMDx, PCA3, PSA, PSAd, ERSPC-RC and PBCG for pathological progression; (b) Harrel’s C-index for for SelectMDx, PCA3, PSA, PSAd, ERSPC-RC, PBCG and model with SelectMDx and PCA3.</p>" ] ] 3 => array:8 [ "identificador" => "tbl0005" "etiqueta" => "Table 1" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at0020" "detalle" => "Table " "rol" => "short" ] ] "tabla" => array:2 [ "leyenda" => "<p id="spar0025" class="elsevierStyleSimplePara elsevierViewall">SD, standard deviation; IQR, interquartile range; mpMRI multiparametric magnetic resonance image.</p>" "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"> \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">Total 86 (100%) \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-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Age \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Mean (SD) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">65.30 (6.90) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" 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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Median (IQR) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">65.82 (60.28−70.89) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">PSA \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Mean (SD) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">5.33 (3.55) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" 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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Median (IQR) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">4.40 (3.70−5.49) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">PSA density \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Mean (SD) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.14 (0.11) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" 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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Median (IQR) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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 (0.09−0.16) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Gleason score \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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">82 (95.35%) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" 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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">≥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">4 (4.65%) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Initial biopsy \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Transrectal \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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 (98.80%) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" 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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Transperineal \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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 (1.20%) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Number of cores obtained \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Mean (SD) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">12.16 (2.99) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" 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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Median (IQR) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">12.00 (11.00−12.00) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Number of positive cores \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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 (67.40%) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" 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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">>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">28 (32.60%) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">mpMRI \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Performed \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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 (69.80%) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" 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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Not performed \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">26 (30.20%) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Performed mpMRI \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">PIRADs ≤ 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">31 (51.67%) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" 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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">PIRADs ≥ 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">11 (18.33%) \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" 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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Not available \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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 (30.00%) \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab2724606.png" ] ] ] ] "descripcion" => array:1 [ "en" => "<p id="spar0020" class="elsevierStyleSimplePara elsevierViewall">Patient characteristics.</p>" ] ] 4 => array:8 [ "identificador" => "tbl0010" "etiqueta" => "Table 2" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at0025" "detalle" => "Table " "rol" => "short" ] ] "tabla" => array:2 [ "leyenda" => "<p id="spar0035" class="elsevierStyleSimplePara elsevierViewall">PP, pathological progression; HR, Hazard ratio; CI, confidence interval; SD, standard deviation; IQR, interquartile range; DRE, digital rectal examination; mpMRI multiparametric magnetic resonance image.</p>" "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">Total \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">PP No \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">PP Yes \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">HR \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 \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 \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-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" 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="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">86 (100 %) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">41 (47.67 %) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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 (52.33 %) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Age at diagnoses \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.036 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.989−1.086 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.132 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Mean (SD) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">65.30 (6.90) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">63.65 (6.76) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">66.81 (6.76) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Median (IQR) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">65.82 (60.28−70.89) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">63.22 (59.60−68.55) \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">67.83 (61.82−71.83) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">PSA density \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">5.794 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.823−40.763 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.078 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Mean (SD) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.14 (0.11) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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 (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">0.16 (0.14) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Median (IQR) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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 (0.09−0.16) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.11 (0.09−0.16) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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 (0.09−0.16) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">PSA density \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">≤0.15 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">61 (70.90 %) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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 (47.54 %) \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">32 (52.46 %) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">(base line) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">>0.15 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">25 (29.10 %) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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 (48.00 %) \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">13 (52.00 %) \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">1.111 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.581−2.12 \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">0.751 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">DRE \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Normal \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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 (95.30 %) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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 (48.78 %) \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">42 (51.22 %) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">(base line) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Suspicious \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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 (4.70 %) \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">1 (25.00 %) \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">3 (75.00 %) \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">1.412 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.436−4.57 \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">0.565 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">SelectMDx \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.035 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.012−1.057 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.002 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Mean (SD) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">7.52 (8.40) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">4.51 (3.34) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">10.27 (10.49) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Median (IQR) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">6.00 (2.25−10.00) \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">4.00 (2.00−6.00) \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">8.00 (4.00−13.00) \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"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">PCA3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.006 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.001−1.011 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.022 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Mean (SD) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">64.51 (53.62) \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">53.49 (38.48) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">74.56 (63.18) \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"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Median (IQR) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">53.50 (35.50−73.75) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">50.00 (30.00−64.00) \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">67.00 (43.00−77.00) \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"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Gleason at diagnoses \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">≤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">82 (95.30 %) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">38 (46.34 %) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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 (53.66 %) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">(base line) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">>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">4 (4.70 %) \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">3 (75.00 %) \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">1 (25.00 %) \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">0.334 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.046−2.43 \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">0.279 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">mpMRI \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><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">31 (73.80 %) \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">16 (51.61 %) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">15 (48.39 %) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">(base line) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">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">8 (19.00 %) \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">4 (50.00 %) \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">4 (50.00 %) \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">0.884 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.293- 2.67 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.827 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">>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">3 (7.10 %) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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 (0.00 %) \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">3 (100.00 %) \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">8.052 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">2.025−32.01 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.003 \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab2724605.png" ] ] ] ] "descripcion" => array:1 [ "en" => "<p id="spar0030" class="elsevierStyleSimplePara elsevierViewall">Univariate analysis with regard to pathological progression.</p>" ] ] 5 => array:8 [ "identificador" => "tbl0015" "etiqueta" => "Table 3" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at0030" "detalle" => "Table " "rol" => "short" ] ] "tabla" => array:1 [ "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"> \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 " colspan="2" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Pathological progression before 5 years</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"> \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"> \t\t\t\t\t\t\n \t\t\t\t\t\t</th></tr><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"> \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">No \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">Yes \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">Total \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 \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-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Total \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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 (50.00%) \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">43 (50.00%) \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">86 (100.00%) \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"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">SelectMDx \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.001 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">≤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 (69.05%) \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">13 (30.95%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">42 (48.84%) \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"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">>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">14 (31.82%) \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">30 (68.18%) \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">44 (51.16%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">PCA3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " 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">32 (60.38%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">21 (39.62%) \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">53 (61.63%) \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"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " 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">11 (33.33%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">22 (66.67%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">33 (38.37%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Risk \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.01 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Low \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">19 (73.08%) \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">7 (26.92%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">26 (30.23%) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">High \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">24 (40.00%) \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">36 (60.00%) \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">60 (69.77%) \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"> \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab2724607.png" ] ] ] ] "descripcion" => array:1 [ "en" => "<p id="spar0040" class="elsevierStyleSimplePara elsevierViewall">Pathological progression at five years of follow-up based in our obtained best SelectMDx and PCA3 cut-offs; and groups risk by multivariate analysis.</p>" ] ] ] "bibliografia" => array:2 [ "titulo" => "References" "seccion" => array:1 [ 0 => array:2 [ "identificador" => "bibs0005" "bibliografiaReferencia" => array:30 [ 0 => array:3 [ "identificador" => "bib0005" "etiqueta" => "1" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "A 16-yr follow-up of the European randomized study of screening for prostate cancer" "autores" => array:1 [ 0 => array:2 [ "etal" => true "autores" => array:6 [ 0 => "J. Hugosson" 1 => "M.J. Roobol" 2 => "M. Månsson" 3 => "T.L.J. Tammela" 4 => "M. Zappa" 5 => "V. Nelen" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1016/j.eururo.2019.02.009" "Revista" => array:6 [ "tituloSerie" => "Eur Urol" "fecha" => "2019" "volumen" => "76" "paginaInicial" => "43" "paginaFinal" => "51" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/30824296" "web" => "Medline" ] ] ] ] ] ] ] ] 1 => array:3 [ "identificador" => "bib0010" "etiqueta" => "2" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "The prostate health index, its utility in prostate cancer detection" "autores" => array:1 [ 0 => array:2 [ "etal" => false "autores" => array:3 [ 0 => "A. Lepor" 1 => "W.J. Catalona" 2 => "S. Loeb" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1016/j.ucl.2015.08.001" "Revista" => array:6 [ "tituloSerie" => "Urol Clin North Am" "fecha" => "2016" "volumen" => "43" "paginaInicial" => "1" "paginaFinal" => "6" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/26614024" "web" => "Medline" ] ] ] ] ] ] ] ] 2 => array:3 [ "identificador" => "bib0015" "etiqueta" => "3" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Predicting high-grade cancer at ten-core prostate biopsy using four kallikrein markers measured in blood in the ProtecT Study" "autores" => array:1 [ 0 => array:2 [ "etal" => true "autores" => array:6 [ 0 => "R.J. Bryant" 1 => "D.D. Sjoberg" 2 => "A.J. Vickers" 3 => "M.C. Robinson" 4 => "R. Kumar" 5 => "L. Marsden" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1093/jnci/djv095" "Revista" => array:3 [ "tituloSerie" => "J Natl Cancer Inst" "fecha" => "2015" "volumen" => "107" ] ] ] ] ] ] 3 => array:3 [ "identificador" => "bib0020" "etiqueta" => "4" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Validation of a 2-gene mRNA urine test for the detection of ≥GG2 prostate cancer in an opportunistic screening population" "autores" => array:1 [ 0 => array:2 [ "etal" => true "autores" => array:6 [ 0 => "J. Rubio-Briones" 1 => "A. Borque-Fernando" 2 => "L.M. Esteban" 3 => "J.M. Mascarós" 4 => "M. Ramírez-Backhaus" 5 => "J. Casanova" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1002/pros.23964" "Revista" => array:6 [ "tituloSerie" => "Prostate" "fecha" => "2020" "volumen" => "80" "paginaInicial" => "500" "paginaFinal" => "507" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/32077525" "web" => "Medline" ] ] ] ] ] ] ] ] 4 => array:3 [ "identificador" => "bib0025" "etiqueta" => "5" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Multiparametric MRI for prostate cancer diagnosis: current status and future directions" "autores" => array:1 [ 0 => array:2 [ "etal" => true "autores" => array:6 [ 0 => "A. Stabile" 1 => "F. Giganti" 2 => "A.B. Rosenkrantz" 3 => "S.S. Taneja" 4 => "G. Villeirs" 5 => "I.S. Gill" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1038/s41585-019-0212-4" "Revista" => array:2 [ "tituloSerie" => "Nat Rev Urol" "fecha" => "2019" ] ] ] ] ] ] 5 => array:3 [ "identificador" => "bib0030" "etiqueta" => "6" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Active surveillance for prostate cancer: a narrative review of clinical guidelines" "autores" => array:1 [ 0 => array:2 [ "etal" => true "autores" => array:6 [ 0 => "S.M. Bruinsma" 1 => "C.H. Bangma" 2 => "P.R. Carroll" 3 => "M.S. Leapman" 4 => "A. Rannikko" 5 => "N. Petrides" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1038/nrurol.2015.313" "Revista" => array:6 [ "tituloSerie" => "Nat Rev Urol" "fecha" => "2016" "volumen" => "13" "paginaInicial" => "151" "paginaFinal" => "167" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/26813955" "web" => "Medline" ] ] ] ] ] ] ] ] 6 => array:3 [ "identificador" => "bib0035" "etiqueta" => "7" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Active surveillance of grade group 1 prostate cancer: long-term outcomes from a large prospective cohort" "autores" => array:1 [ 0 => array:2 [ "etal" => true "autores" => array:6 [ 0 => "J.J. Tosoian" 1 => "M. Mamawala" 2 => "J.I. Epstein" 3 => "P Landis" 4 => "KJ Macura" 5 => "DN Simopoulos" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1016/j.eururo.2019.12.017" "Revista" => array:2 [ "tituloSerie" => "Eur Urol" "fecha" => "2020" ] ] ] ] ] ] 7 => array:3 [ "identificador" => "bib0040" "etiqueta" => "8" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Reporting magnetic resonance imaging in men on active surveillance for prostate cancer: the PRECISE Recommendations—a report of a European School of Oncology Task Force" "autores" => array:1 [ 0 => array:2 [ "etal" => true "autores" => array:6 [ 0 => "C.M. Moore" 1 => "F. Giganti" 2 => "P. Albertsen" 3 => "C. Allen" 4 => "C. Bangma" 5 => "A. Briganti" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1016/j.eururo.2016.06.011" "Revista" => array:7 [ "tituloSerie" => "Eur Urol" "fecha" => "2017" "volumen" => "71" "paginaInicial" => "648" "paginaFinal" => "655" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/27349615" "web" => "Medline" ] ] "itemHostRev" => array:3 [ "pii" => "S0140673618331325" "estado" => "S300" "issn" => "01406736" ] ] ] ] ] ] ] 8 => array:3 [ "identificador" => "bib0045" "etiqueta" => "9" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Role of the 4Kscore test as a predictor of reclassification in prostate cancer active surveillance" "autores" => array:1 [ 0 => array:2 [ "etal" => true "autores" => array:6 [ 0 => "Á Borque-Fernando" 1 => "J. Rubio-Briones" 2 => "L.M. Esteban" 3 => "Y. Dong" 4 => "A. Calatrava" 5 => "A. Gómez-Ferrer" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1038/s41391-018-0074-5" "Revista" => array:6 [ "tituloSerie" => "Prostate Cancer Prostatic Dis" "fecha" => "2019" "volumen" => "22" "paginaInicial" => "84" "paginaFinal" => "90" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/30108375" "web" => "Medline" ] ] ] ] ] ] ] ] 9 => array:3 [ "identificador" => "bib0050" "etiqueta" => "10" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "17-Gene genomic prostate score test results in the Canary Prostate Active Surveillance Study (PASS) Cohort" "autores" => array:1 [ 0 => array:2 [ "etal" => true "autores" => array:6 [ 0 => "D.W. Lin" 1 => "Y. Zheng" 2 => "J.K. McKenney" 3 => "M.D. Brown" 4 => "R. Lu" 5 => "M. Crager" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1200/jco.19.02267" "Revista" => array:4 [ "tituloSerie" => "J Clin Oncol" "fecha" => "2020" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/23897962" "web" => "Medline" ] ] "itemHostRev" => array:3 [ "pii" => "S0140673616326174" "estado" => "S300" "issn" => "01406736" ] ] ] ] ] ] ] 10 => array:3 [ "identificador" => "bib0055" "etiqueta" => "11" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Accuracy of PCA3 measurement in predicting short-term biopsy progression in an active surveillance program" "autores" => array:1 [ 0 => array:2 [ "etal" => true "autores" => array:6 [ 0 => "J.J. Tosoian" 1 => "S. Loeb" 2 => "A. Kettermann" 3 => "P. Landis" 4 => "D.J. Elliot" 5 => "J.I. Epstein" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1016/j.juro.2009.10.003" "Revista" => array:6 [ "tituloSerie" => "J Urol" "fecha" => "2010" "volumen" => "183" "paginaInicial" => "534" "paginaFinal" => "538" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/20006883" "web" => "Medline" ] ] ] ] ] ] ] ] 11 => array:3 [ "identificador" => "bib0060" "etiqueta" => "12" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Circulating biomarkers for discriminating indolent from aggressive disease in prostate cancer active surveillance" "autores" => array:1 [ 0 => array:2 [ "etal" => false "autores" => array:1 [ 0 => "B.J. Trock" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1097/MOU.0000000000000050" "Revista" => array:6 [ "tituloSerie" => "Curr Opin Urol" "fecha" => "2014" "volumen" => "24" "paginaInicial" => "293" "paginaFinal" => "302" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/24710054" "web" => "Medline" ] ] ] ] ] ] ] ] 12 => array:3 [ "identificador" => "bib0065" "etiqueta" => "13" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Combining urinary DNA methylation and cell-free microRNA biomarkers for improved monitoring of prostate cancer patients on active surveillance" "autores" => array:1 [ 0 => array:2 [ "etal" => true "autores" => array:6 [ 0 => "F. Zhao" 1 => "D. Vesprini" 2 => "R.S.C. Liu" 3 => "E. Olkhov-Mitsel" 4 => "L.H. Klotz" 5 => "A. Loblaw" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1016/j.urolonc.2019.01.031" "Revista" => array:5 [ "tituloSerie" => "Urol Oncol Semin Orig Investig" "fecha" => "2019" "volumen" => "37" "paginaInicial" => "297.e9" "paginaFinal" => "297.e17" ] ] ] ] ] ] 13 => array:3 [ "identificador" => "bib0070" "etiqueta" => "14" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Detection of high-grade prostate cancer using a urinary molecular biomarker–based risk score" "autores" => array:1 [ 0 => array:2 [ "etal" => true "autores" => array:6 [ 0 => "L. Van Neste" 1 => "R.J. Hendriks" 2 => "S. Dijkstra" 3 => "G. Trooskens" 4 => "E.B. Cornel" 5 => "S.A. Jannink" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1016/j.eururo.2016.04.012" "Revista" => array:6 [ "tituloSerie" => "Eur Urol" "fecha" => "2016" "volumen" => "70" "paginaInicial" => "740" "paginaFinal" => "748" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/27108162" "web" => "Medline" ] ] ] ] ] ] ] ] 14 => array:3 [ "identificador" => "bib0075" "etiqueta" => "15" "referencia" => array:1 [ 0 => array:1 [ "referenciaCompleta" => "CRAN-Package pROC. [Accessed 20 April 2020]. <a target="_blank" href="https://cran.r-project.org/web/packages/pROC/index.html">https://cran.r-project.org/web/packages/pROC/index.html</a>." ] ] ] 15 => array:3 [ "identificador" => "bib0080" "etiqueta" => "16" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "R: a language and environment for statistical computing, 3.2.1" "autores" => array:1 [ 0 => array:2 [ "etal" => false "autores" => array:1 [ 0 => "R Core Development Team" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1017/CBO9781107415324.004" "Libro" => array:1 [ "fecha" => "2015" ] ] ] ] ] ] 16 => array:3 [ "identificador" => "bib0085" "etiqueta" => "17" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Reeuwijk" "autores" => array:1 [ 0 => array:2 [ "etal" => false "autores" => array:1 [ 0 => "SWOP – The Prostate Cancer Research Foundation" ] ] ] ] ] "host" => array:1 [ 0 => array:1 [ "WWW" => array:1 [ "link" => "http://www.prostatecancer-riskcalculator.com/" ] ] ] ] ] ] 17 => array:3 [ "identificador" => "bib0090" "etiqueta" => "18" "referencia" => array:1 [ 0 => array:1 [ "referenciaCompleta" => "PBCG Risk Calculator. [Accessed 20 April 2020]. Available from: <a target="_blank" href="https://riskcalc.org/PBCG/">https://riskcalc.org/PBCG/</a>." ] ] ] 18 => array:3 [ "identificador" => "bib0095" "etiqueta" => "19" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Pathologic findings in radical prostatectomy specimens from patients eligible for active surveillance with highly selective criteria: a multicenter study" "autores" => array:1 [ 0 => array:2 [ "etal" => true "autores" => array:3 [ 0 => "J.B. Beauval" 1 => "G. Ploussard" 2 => "M. Soulié" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1016/j.urology.2012.04.051" "Revista" => array:6 [ "tituloSerie" => "Urology" "fecha" => "2012" "volumen" => "80" "paginaInicial" => "656" "paginaFinal" => "660" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/22770616" "web" => "Medline" ] ] ] ] ] ] ] ] 19 => array:3 [ "identificador" => "bib0100" "etiqueta" => "20" "referencia" => array:1 [ 0 => array:1 [ "referenciaCompleta" => "Klotz L. Platinum Priority-Editorial and Reply from Authors Active Surveillance, Quality of life, and cancer-related anxiety. 30–6. <a target="_blank" href="https://doi.org/10.1016/j.eururo.2013.01.009">https://doi.org/10.1016/j.eururo.2013.01.009</a>." ] ] ] 20 => array:3 [ "identificador" => "bib0105" "etiqueta" => "21" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Systematic review of complications of prostate biopsy" "autores" => array:1 [ 0 => array:2 [ "etal" => true "autores" => array:6 [ 0 => "S. Loeb" 1 => "A. Vellekoop" 2 => "H.U. Ahmed" 3 => "J. Catto" 4 => "M. Emberton" 5 => "R. Nam" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1016/j.eururo.2013.05.049" "Revista" => array:5 [ "tituloSerie" => "Eur Urol" "fecha" => "2013" "volumen" => "64" "paginaInicial" => "876" "paginaFinal" => "892" ] ] ] ] ] ] 21 => array:3 [ "identificador" => "bib0110" "etiqueta" => "22" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Serum and urinary biomarkers for detection and active surveillance of prostate cancer" "autores" => array:1 [ 0 => array:2 [ "etal" => false "autores" => array:5 [ 0 => "M.F. Becerra" 1 => "A. Bhat" 2 => "A. Mouzannar" 3 => "V.S. Atluri" 4 => "S. Punnen" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1097/MOU.0000000000000670" "Revista" => array:7 [ "tituloSerie" => "Curr Opin Urol" "fecha" => "2019" "volumen" => "29" "paginaInicial" => "593" "paginaFinal" => "597" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/31436568" "web" => "Medline" ] ] "itemHostRev" => array:3 [ "pii" => "S1201971218344576" "estado" => "S300" "issn" => "12019712" ] ] ] ] ] ] ] 22 => array:3 [ "identificador" => "bib0115" "etiqueta" => "23" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "A 17-gene panel for prediction of adverse prostate cancer pathologic features: prospective clinical validation and utility" "autores" => array:1 [ 0 => array:2 [ "etal" => true "autores" => array:6 [ 0 => "S. Eggener" 1 => "L.I. Karsh" 2 => "T. Richardson" 3 => "A.W. Shindel" 4 => "R. Lu" 5 => "S. Rosenberg" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1016/j.urology.2018.11.050" "Revista" => array:6 [ "tituloSerie" => "Urology" "fecha" => "2019" "volumen" => "126" "paginaInicial" => "76" "paginaFinal" => "82" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/30611659" "web" => "Medline" ] ] ] ] ] ] ] ] 23 => array:3 [ "identificador" => "bib0120" "etiqueta" => "24" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "A biopsy-based 17-gene genomic prostate score as a predictor of metastases and prostate cancer death in surgically treated men with clinically localized disease" "autores" => array:1 [ 0 => array:2 [ "etal" => true "autores" => array:6 [ 0 => "S.K. Van Den Eeden" 1 => "R. Lu" 2 => "N. Zhang" 3 => "C.P. Quesenberry" 4 => "J. Shan" 5 => "J.S. Han" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1016/j.eururo.2017.09.013" "Revista" => array:6 [ "tituloSerie" => "Eur Urol" "fecha" => "2018" "volumen" => "73" "paginaInicial" => "129" "paginaFinal" => "138" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/28988753" "web" => "Medline" ] ] ] ] ] ] ] ] 24 => array:3 [ "identificador" => "bib0125" "etiqueta" => "25" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Intratumoral and intertumoral genomic heterogeneity of multifocal localized prostate cancer impacts molecular classifications and genomic prognosticators" "autores" => array:1 [ 0 => array:2 [ "etal" => true "autores" => array:6 [ 0 => "L. Wei" 1 => "J. Wang" 2 => "E. Lampert" 3 => "S. Schlanger" 4 => "A.D. DePriest" 5 => "Q. Hu" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1016/j.eururo.2016.07.008" "Revista" => array:7 [ "tituloSerie" => "Eur Urol" "fecha" => "2017" "volumen" => "71" "paginaInicial" => "183" "paginaFinal" => "192" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/27451135" "web" => "Medline" ] ] "itemHostRev" => array:3 [ "pii" => "S0140673615605530" "estado" => "S300" "issn" => "01406736" ] ] ] ] ] ] ] 25 => array:3 [ "identificador" => "bib0130" "etiqueta" => "26" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Transcriptomic heterogeneity in multifocal prostate cancer" "autores" => array:1 [ 0 => array:2 [ "etal" => true "autores" => array:6 [ 0 => "S.S. Salami" 1 => "D.H. Hovelson" 2 => "J.B. Kaplan" 3 => "R. Mathieu" 4 => "A.M. Udager" 5 => "N.E. Curci" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1172/jci.insight.123468" "Revista" => array:4 [ "tituloSerie" => "JCI insight" "fecha" => "2018" "volumen" => "3" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/30385715" "web" => "Medline" ] ] ] ] ] ] ] ] 26 => array:3 [ "identificador" => "bib0135" "etiqueta" => "27" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Optimizing the clinical utility of PCA3 to diagnose prostate cancer in initial prostate biopsy" "autores" => array:1 [ 0 => array:2 [ "etal" => true "autores" => array:6 [ 0 => "J. Rubio-Briones" 1 => "A. Borque" 2 => "L.M. Esteban" 3 => "J. Casanova" 4 => "A. Fernandez-Serra" 5 => "L. Rubio" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1186/s12885-015-1623-0" "Revista" => array:5 [ "tituloSerie" => "BMC Cancer" "fecha" => "2015" "volumen" => "15" "paginaInicial" => "633" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/26362197" "web" => "Medline" ] ] ] ] ] ] ] ] 27 => array:3 [ "identificador" => "bib0140" "etiqueta" => "28" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Variability in the multicentre National Registry in Active Surveillance; a questionnaire for urologists" "autores" => array:1 [ 0 => array:2 [ "etal" => false "autores" => array:6 [ 0 => "J. Rubio-Briones" 1 => "A. Borque-Fernando" 2 => "L.M. Esteban-Escaño" 3 => "S. Martínez-Breijo" 4 => "R. Medina-López" 5 => "V. Hernández" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1016/j.acuro.2018.01.007" "Revista" => array:7 [ "tituloSerie" => "Actas Urol Esp" "fecha" => "2018" "volumen" => "42" "paginaInicial" => "442" "paginaFinal" => "449" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/29661508" "web" => "Medline" ] ] "itemHostRev" => array:3 [ "pii" => "S0140673616326216" "estado" => "S300" "issn" => "01406736" ] ] ] ] ] ] ] 28 => array:3 [ "identificador" => "bib0145" "etiqueta" => "29" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Multiparametric MRI versus SelectMDx accuracy in the diagnosis of clinically significant PCA in men enrolled in active surveillance" "autores" => array:1 [ 0 => array:2 [ "etal" => false "autores" => array:4 [ 0 => "P. Pepe" 1 => "G. Dibenedetto" 2 => "L. Pepe" 3 => "M. Pennisi" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.21873/invivo.11786" "Revista" => array:5 [ "tituloSerie" => "In Vivo (Brooklyn)" "fecha" => "2020" "volumen" => "34" "paginaInicial" => "393" "paginaFinal" => "396" ] ] ] ] ] ] 29 => array:3 [ "identificador" => "bib0150" "etiqueta" => "30" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Concordance and performance of 4Kscore® and SelectMDx® for informing decision to perform prostate biopsy and detection of prostate cancer" "autores" => array:1 [ 0 => array:2 [ "etal" => false "autores" => array:5 [ 0 => "J.S. Wysock" 1 => "E. Becher" 2 => "J. Persily" 3 => "S. Loeb" 4 => "H. Lepor" ] ] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1016/j.urology.2020.02.032" "Revista" => array:3 [ "tituloSerie" => "Urology" "fecha" => "2020" "link" => array:1 [ 0 => array:2 [ "url" => "https://www.ncbi.nlm.nih.gov/pubmed/12385922" "web" => "Medline" ] ] ] ] ] ] ] ] ] ] ] ] "agradecimientos" => array:1 [ 0 => array:4 [ "identificador" => "xack562746" "titulo" => "Acknowledgements" "texto" => "<p id="par0135" class="elsevierStylePara elsevierViewall">The authors would like to thank Tania Mazcuñán Vitiello, Marta Ramírez Calvo, and Patricia Carretero Hinojosa for their technical collaboration. We also thank the Biobank of the Fundación Instituto Valenciano de Oncología for providing the biological samples for analysis.</p>" "vista" => "all" ] ] ] "idiomaDefecto" => "en" "url" => "/21735786/0000004500000006/v2_202110210828/S2173578621000767/v2_202110210828/en/main.assets" "Apartado" => array:4 [ "identificador" => "6274" "tipo" => "SECCION" "en" => array:2 [ "titulo" => "Original articles" "idiomaDefecto" => true ] "idiomaDefecto" => "en" ] "PDF" => "https://static.elsevier.es/multimedia/21735786/0000004500000006/v2_202110210828/S2173578621000767/v2_202110210828/en/main.pdf?idApp=UINPBA00004N&text.app=https://www.elsevier.es/" "EPUB" => "https://multimedia.elsevier.es/PublicationsMultimediaV1/item/epub/S2173578621000767?idApp=UINPBA00004N" ]
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