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Non-small-cell lung carcinoma (NSCLC) represents 80% of all cases of BC, and its five-year survival rate is of approximately 15%.<a class="elsevierStyleCrossRef" href="#bib0005"><span class="elsevierStyleSup">1</span></a> In 2017, tracheal, bronchial, and lung cancer had a global incidence of approximately 2.2 million cases (affecting 1,468,000 men and 695,000 women) and caused 1.9 million deaths worldwide.<a class="elsevierStyleCrossRef" href="#bib0010"><span class="elsevierStyleSup">2</span></a></p><p id="par0010" class="elsevierStylePara elsevierViewall">Mining is, and continues to be, an activity of enormous importance in the economic growth of Spain.<a class="elsevierStyleCrossRef" href="#bib0015"><span class="elsevierStyleSup">3</span></a> However, its negative impact on general health and, especially, in the field of respiratory diseases, was widely demonstrated and documented in countless studies carried out in the 1970s and 1980s, in which its relationship with silicosis, tuberculosis, and chronic obstructive pulmonary disease (COPD), among others, was made clear.<a class="elsevierStyleCrossRefs" href="#bib0020"><span class="elsevierStyleSup">4,5</span></a> Although the interaction between mining (silica exposure) and lung cancer has been a controversial issue for decades,<a class="elsevierStyleCrossRef" href="#bib0030"><span class="elsevierStyleSup">6</span></a> a positive association between occupational silica exposure and lung cancer has recently been demonstrated.<a class="elsevierStyleCrossRef" href="#bib0035"><span class="elsevierStyleSup">7</span></a></p><p id="par0015" class="elsevierStylePara elsevierViewall">In recent decades there have also been important changes in the field of lung cancer diagnosis and staging. The most important advances achieved in this field can be summarized in the following points: (1) improvements in imaging techniques, including the use of multislice computed tomography (CT) with a higher image resolution capable of detecting smaller nodules<a class="elsevierStyleCrossRef" href="#bib0040"><span class="elsevierStyleSup">8</span></a>; (2) the development of diagnostic and staging techniques with a minimally invasive approach, especially aspiration puncture guided by endoscopic ultrasound (EUS) and endobronchial ultrasound (EBUS)<a class="elsevierStyleCrossRefs" href="#bib0045"><span class="elsevierStyleSup">9–12</span></a>; and, (3) the use of positron emission tomography (PET) and PET combined with computed tomography (PET/CT), which have generally been considered positive for malignancy when the standardized uptake value (SUV) is greater than 2.5 (SUV<span class="elsevierStyleInf">max</span> > 2.5),<a class="elsevierStyleCrossRefs" href="#bib0065"><span class="elsevierStyleSup">13,14</span></a> although other values, such as the mean SUV, the dual-time SUV<span class="elsevierStyleInf">max</span>, or the tumor SUV/adenopathy SUV ratio, can also be used.<a class="elsevierStyleCrossRef" href="#bib0075"><span class="elsevierStyleSup">15</span></a> As is the case with any diagnostic test, its accuracy is determined by the balance between false positives and false negatives. False positives can be explained by increased fluorodeoxyglucose (FDG) uptake due to the increased glycolysis in leukocytes, lymphocytes, and macrophages, as in the case of infections or inflammatory processes, such as pneumonias, caseating granulomas, sarcoidosis, amyloidosis, pleurodesis, round atelectasis, etc.<a class="elsevierStyleCrossRef" href="#bib0080"><span class="elsevierStyleSup">16</span></a></p><p id="par0020" class="elsevierStylePara elsevierViewall">In the case of the population with prolonged exposure to inflammatory agents, such as miners, the likelihood of false positives in PET/CT scans is higher, as demonstrated in previous studies performed on subjects with a history of coal exposure and exhibiting hypermetabolic pulmonary nodules in PET/CT scans, but whose final histology results were negative for malignancy.<a class="elsevierStyleCrossRef" href="#bib0085"><span class="elsevierStyleSup">17</span></a></p><p id="par0025" class="elsevierStylePara elsevierViewall">Our work will focus on analyzing the SUV<span class="elsevierStyleInf">max</span> as a determinant of malignancy in populations both with and without a history of mining exposure. These PET/CT data have been decisive for the indication of invasive EBUS staging, as well as for the selection of adenopathies during the diagnostic procedure carried out with the aid of this test.</p><p id="par0030" class="elsevierStylePara elsevierViewall">We hypothesize that the mining population should not have the same SUV<span class="elsevierStyleInf">max</span> limits as the general population, and that a higher SUV<span class="elsevierStyleInf">max</span> would probably be necessary to suggest the presence of malignancy in this population.</p><p id="par0035" class="elsevierStylePara elsevierViewall">Considering a potentially higher likelihood of error of PET/CT in terms of lung cancer diagnosis in the mining population, the aim of our work focuses on determining whether an SUV<span class="elsevierStyleInf">max</span> > 2.5 in mediastinal adenopathies can be considered an independent risk factor for malignancy in both the population with a history of mining exposure and that without it.</p><p id="par0040" class="elsevierStylePara elsevierViewall">As for secondary objectives, we also analyzed other factors such as age, adenopathy size greater than 1 cm, and history of smoking.</p></span><span id="sec0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0070">Patients and methods</span><span id="sec0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0075">Study design</span><span id="sec0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0080">Population</span><p id="par0045" class="elsevierStylePara elsevierViewall">Between May 2014 and December 2019, we retrospectively selected all patients who had undergone an EBUS for lung cancer diagnosis and/or staging and had previously undergone a PET/CT scan with <span class="elsevierStyleSup">18</span>F-FDG from a prospective database. In the case of patients who had undergone an EBUS for staging purposes, this procedure had been carried out systematically and, therefore, the PET values were only used as an orientation. However, in those patients who had undergone an EBUS for lung cancer diagnosis purposes, the PET scan findings were used as indicators of the areas to be punctured. The PET/CT scan was always performed prior to the EBUS, and the maximum time elapsed between both tests was 15 days.</p><p id="par0050" class="elsevierStylePara elsevierViewall">Because of its location, the Salamanca Healthcare Complex (<span class="elsevierStyleItalic">Complejo Asistencial de Salamanca</span>) attends patients from a wide geographical region of the province of Salamanca (Spain), but also from the northern part of the country, specifically from the town of Ponferrada and its surrounding area, whose population is characterized by exposure to mining, particularly of silica and coal. For this reason, we divided the patients into two groups: a first group (group 1) including patients who had not been exposed to mining, and a second one (group 2) formed by patients who had been exposed to this activity.</p><p id="par0055" class="elsevierStylePara elsevierViewall">The variables analyzed in both groups were sex, age, smoking history, occupational exposure to mining, adenopathy size measured during an EBUS, PET/CT SUV, and pathology exam results.</p><p id="par0060" class="elsevierStylePara elsevierViewall">A PET/CT scan was considered positive when the SUV<span class="elsevierStyleInf">max</span> was greater than 2.5, as suggested by some authors in the paper published by Pak et al. and according to the indications of our center’s Nuclear Medicine Department.<a class="elsevierStyleCrossRef" href="#bib0090"><span class="elsevierStyleSup">18</span></a></p><p id="par0065" class="elsevierStylePara elsevierViewall">An adenopathy was considered to be suggestive of malignancy (and consequently punctured under EBUS guidance) when its size was greater than 5 mm or the PET scan was positive. The pathology exam results were classified as positive if the sample contained malignant cells, negative if it contained lymphocytes, and invalid when none of these criteria were met and it was insufficient to reach a diagnosis. The gold-standard for the EBUS was a histopathological analysis of the adenopathy excised through a mediastinoscopy or surgical resection.</p></span></span><span id="sec0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0085">Statistical analysis</span><p id="par0070" class="elsevierStylePara elsevierViewall">For our statistical model, the observation unit was not the subject, but rather the punctured adenopathy.</p><p id="par0075" class="elsevierStylePara elsevierViewall">Our study sample was divided into two groups based on the subjects’ occupational history: group 1 included adenopathies obtained from subjects without a previous exposure to mining activities, and group 2 included those obtained from subjects who had been exposed to mining. In the binomial logistic regression model, the dependent variable was considered to be the pathology exam result in terms of malignancy (neoplastic cells in the final histopathology report) or non-malignancy (valid sample without neoplastic cells).</p><p id="par0080" class="elsevierStylePara elsevierViewall">The independent variables (risk factors for malignancy) were an age older than 65 years, an adenopathy size greater than 1 cm (measured during the EBUS), and a PET/CT SUV<span class="elsevierStyleInf">max</span> greater than 2.5. The subjects’ sex was excluded as a variable in the logistic regression models due to the existence of a high collinearity phenomenon (Pearson’s correlation coefficient of 0.78 and typified residuals of 10.1) with the smoking variable. The smoking variable was also excluded in the model applied on the mining population owing to the fact that all miners were ex-smokers. In the non-mining population, non-smokers were retained because of the importance of this variable and its strengthening of the mathematical model. The statistical analysis was carried out using software SPSS 20, through the license granted to the University of Salamanca.</p><p id="par0085" class="elsevierStylePara elsevierViewall">The study was reviewed and approved by the Ethics Committee of the Salamanca Healthcare Complex.</p></span></span><span id="sec0030" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0090">Results</span><p id="par0090" class="elsevierStylePara elsevierViewall">A total of 583 adenopathies punctured from 339 subjects (40 of whom were miners) under EBUS guidance were analyzed. On average, 1.7 adenopathies were punctured per subject.</p><p id="par0095" class="elsevierStylePara elsevierViewall">The number of punctured adenopathies was 514 in the group of subjects without a previous exposure to mining (299 subjects) and 69 in those with a history of exposure to mining (40 miners). The male sex predominated in both groups (87.2%), with 100% of the group of exposed subjects being men owing to the occupational characteristics inherent to mining. A history of smoking also predominated in both groups, to such an extent that the entire mining group were either current or ex-smokers. The age of the subjects of both groups was similar, with a mean of 66.2 years, and no statistically significant differences were observed between both groups in the characteristics of the adenopathies in terms of their size and PET/CT SUV. As for the presence of neoplasms, a higher frequency was detected in the unexposed group, with this difference being statistically significant. <a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a> shows the characteristics of both groups according to the variables under study and the statistical bivariate comparison.</p><elsevierMultimedia ident="tbl0005"></elsevierMultimedia><p id="par0100" class="elsevierStylePara elsevierViewall">As shown in <a class="elsevierStyleCrossRef" href="#tbl0010">Table 2</a>, the logistic regression model showed that in the population without a history of exposure to mining, an age older than 65 years (odds ratio [OR] = 2.6), an adenopathy size greater than 1 cm measured during the EBUS (OR = 7.2), a PET/CT SUV<span class="elsevierStyleInf">max</span> greater than 2.5 (OR = 5.5), and a history of smoking (OR = 6.1) behaved as independent factors capable of predicting malignancy in the histopathology study of the sample obtained under EBUS guidance. Whereas in adenopathies punctured from the population exposed to mining, none of the above variables could predict malignancy, i.e., an age over 65 years (OR = 1.3), an adenopathy greater than 1 cm measured during the EBUS (OR = 1.6), a PET/CT SUV<span class="elsevierStyleInf">max</span> greater than 2.5 (OR = 0.7), and a history of smoking.</p><elsevierMultimedia ident="tbl0010"></elsevierMultimedia><p id="par0105" class="elsevierStylePara elsevierViewall">It is important to emphasize that multiple logistic regression models were performed with different adenopathy sizes and SUV<span class="elsevierStyleInf">max</span> cut-off points. Because none of the tested models was powerful enough, we maintained an adenopathy size of 1 cm and an SUV<span class="elsevierStyleInf">max</span> of 2.5 as a risk factor for malignancy.</p><p id="par0110" class="elsevierStylePara elsevierViewall">Finally, we set an SUV<span class="elsevierStyleInf">max</span> cut-off point defining the highest likelihood of malignancy in each of the populations under study; that is, 3.7 for the unexposed population (81% sensitivity and 75% specificity) and 4.8 for the mining population (71% sensitivity and 42% specificity).</p></span><span id="sec0035" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0095">Discussion</span><p id="par0115" class="elsevierStylePara elsevierViewall">The accuracy with which we are able to predict mediastinal lymph node malignancy is critical in lung cancer diagnosis, prognosis, and management.<a class="elsevierStyleCrossRefs" href="#bib0060"><span class="elsevierStyleSup">12,19</span></a> In this context, PET/CT has proven to be useful in distinguishing between benign and malignant adenopathies, with a high negative predictive value that aids in mediastinal staging through EBUS or mediastinoscopy.<a class="elsevierStyleCrossRef" href="#bib0100"><span class="elsevierStyleSup">20</span></a></p><p id="par0120" class="elsevierStylePara elsevierViewall">There is also a positive relationship between the size of the mediastinal adenopathy, as measured by a tomography or EBUS, and its degree of malignancy, such that the larger the size the greater the likelihood of malignancy.<a class="elsevierStyleCrossRef" href="#bib0105"><span class="elsevierStyleSup">21</span></a> Studies such as that of Mattes et al. proposed mathematical models capable of predicting the likelihood of malignancy of an adenopathy based on variables such as its size (the larger the lymph node’s short axis the greater the likelihood of malignancy), PET/CT SUV, and histological type.<a class="elsevierStyleCrossRef" href="#bib0095"><span class="elsevierStyleSup">19</span></a> Although these two criteria determined through imaging tests are widely accepted and based on available scientific literature, there is insufficient evidence to extrapolate these concepts to specific populations. The power of this study is based on several facts, including the reliability of its results considering that it is based on a systematized database meeting quality criteria, that it incorporates a considerably large sample of lymph nodes punctured under EBUS guidance, and that it includes a particular population that is hard to access. In addition, the diagnosis of all negative adenopathies was confirmed through a mediastinoscopy and/or surgery. Positive adenopathies were considered true positives and histological confirmation was not required given the low incidence of false positives yielded by EBUS (2%), as reported in the literature.<a class="elsevierStyleCrossRefs" href="#bib0110"><span class="elsevierStyleSup">22,23</span></a></p><p id="par0125" class="elsevierStylePara elsevierViewall">Therefore, the presented mathematical model can be a useful tool in the decision-making process in patients with a suspected pulmonary neoplasm and no history of occupational exposure to mining. However, it is completely worthless for the exposed population, as none of the analyzed variables is capable of predicting malignancy.</p><p id="par0130" class="elsevierStylePara elsevierViewall">The first logistic model obtained in the unexposed population is consistent with most models and publications arguing that the likelihood of malignancy of a mediastinal adenopathy in subjects with suspected lung cancer is related to the size of the adenopathy and the PET/CT SUV<span class="elsevierStyleInf">max</span>. That is, the larger the short transverse diameter with an uptake value greater than 2.5, the greater the likelihood of malignancy.<a class="elsevierStyleCrossRefs" href="#bib0090"><span class="elsevierStyleSup">18,19,24,25</span></a> In this first mathematical model, the two variables behave as independent risk factors for malignancy with an OR of 7.2 when the size of the adenopathy is greater than 1 cm, as measured during an EBUS, and of 5.2 when the PET/CT SUV is greater than 2.5 (<a class="elsevierStyleCrossRef" href="#tbl0010">Table 2</a>).</p><p id="par0135" class="elsevierStylePara elsevierViewall">However, when we applied a similar logistic model, but in a population exposed to mining, the results differed, as none of the independent risk factors for lung cancer described above (adenopathy size and PET/CT SUV) behaved as predictors of malignancy. The diagnostic problems associated with PET/CT have previously been studied in the context of extrathoracic neoplastic diseases, in which case false positives have been detected in patients with inflammatory diseases, granulomatous diseases, chronic pancreatitis, fibrosis, or salivary gland tumors,<a class="elsevierStyleCrossRef" href="#bib0130"><span class="elsevierStyleSup">26</span></a> as well as in intrathoracic diseases, such as infections (bacterial, fungal, or tuberculosis), sarcoidosis, post-radiation pneumonitis, and post-surgical changes.<a class="elsevierStyleCrossRef" href="#bib0135"><span class="elsevierStyleSup">27</span></a></p><p id="par0140" class="elsevierStylePara elsevierViewall">In clinical practice there is very little information available about the usefulness of PET/CT in lung cancer diagnosis and staging in patients exposed to mining. In these patients, chronic inflammation due to structural changes in the lymph nodes secondary to coal or silica exposure can trigger an increase in their metabolism with a consequent increase in the adenopathy size and PET/CT SUV.<a class="elsevierStyleCrossRef" href="#bib0140"><span class="elsevierStyleSup">28</span></a></p><p id="par0145" class="elsevierStylePara elsevierViewall">As shown in <a class="elsevierStyleCrossRef" href="#fig0005">Fig. 1</a>, the samples obtained from the adenopathies of subjects exposed to mining were anthracotic, which conditions an inflammatory state and a pathological PET/CT SUV leading to an erroneous interpretation in terms of the malignancy diagnosis. Similar results, although from small case series, have previously been published by Reichert et al. and Saydam et al., who concluded that PET/CT is an imaging technique with limitations in patients with mining exposure.<a class="elsevierStyleCrossRefs" href="#bib0085"><span class="elsevierStyleSup">17,29</span></a></p><elsevierMultimedia ident="fig0005"></elsevierMultimedia><p id="par0150" class="elsevierStylePara elsevierViewall">A limitation of our study is the use of an SUV<span class="elsevierStyleInf">max</span> cut-off point of 2.5 to predict malignancy as the only PET/CT value. Other authors, such as Shimizu et al.,<a class="elsevierStyleCrossRef" href="#bib0150"><span class="elsevierStyleSup">30</span></a> use the dual-time SUV<span class="elsevierStyleInf">max</span>, although mainly for studying the tumor lesion rather than for evaluating all potentially affected lymph node structures. This is based on the idea that a significant uptake is maintained for several hours in malignant lesions, whereas the uptake decreases markedly over time in benign lesions. However, we were unable to determine the dual-time SUV<span class="elsevierStyleInf">max</span> in our study because a delayed image that would allow such comparison was not obtained.</p><p id="par0155" class="elsevierStylePara elsevierViewall">There are currently authors who use the metabolic tumor volume (MTV) and total lesion glycolysis (TLG), as these values have been proposed for risk stratification in lung cancer patients. In fact, in a study carried out by Pellegrino et al.,<a class="elsevierStyleCrossRef" href="#bib0155"><span class="elsevierStyleSup">31</span></a> these volumetric imaging values were valid for determining the clinical evolution of these subjects, even allowing for predicting the disease-free period.</p><p id="par0160" class="elsevierStylePara elsevierViewall">In conclusion, while in the population without a history of mining exposure an adenopathy size greater than 1 cm and a PET/CT SUV<span class="elsevierStyleInf">max</span> greater than 2.5 can be considered independent risk factors for malignancy, in the population with a history of mining exposure there is no valid predictive model based on complementary imaging techniques that meets these conditions. This is explained by the existence of a greater number of false positives in these subjects compared with the general unexposed population, which limits the usefulness of these techniques in the diagnosis of lung cancer and further supports the need to confirm these findings by cytohistological testing.</p><p id="par0165" class="elsevierStylePara elsevierViewall">It would be advisable to perform prospective studies on this population with a view to adjust the validity of PET/CT in the decision-making process in lung cancer diagnosis.</p></span><span id="sec0040" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0100">Conflicts of interest</span><p id="par0170" class="elsevierStylePara elsevierViewall">The authors of this paper declare no conflicts of interest.</p></span></span>" "textoCompletoSecciones" => array:1 [ "secciones" => array:10 [ 0 => array:3 [ "identificador" => "xres1653108" "titulo" => "Abstract" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0005" "titulo" => "Introduction" ] 1 => array:2 [ "identificador" => "abst0010" "titulo" => "Patients and methods" ] 2 => array:2 [ "identificador" => "abst0015" "titulo" => "Results" ] 3 => array:2 [ "identificador" => "abst0020" "titulo" => "Discussion" ] ] ] 1 => array:2 [ "identificador" => "xpalclavsec1469639" "titulo" => "Keywords" ] 2 => array:3 [ "identificador" => "xres1653109" "titulo" => "Resumen" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0025" "titulo" => "Introducción" ] 1 => array:2 [ "identificador" => "abst0030" "titulo" => "Pacientes y métodos" ] 2 => array:2 [ "identificador" => "abst0035" "titulo" => "Resultados" ] 3 => array:2 [ "identificador" => "abst0040" "titulo" => "Discusión" ] ] ] 3 => array:2 [ "identificador" => "xpalclavsec1469640" "titulo" => "Palabras clave" ] 4 => array:2 [ "identificador" => "sec0005" "titulo" => "Introduction" ] 5 => array:3 [ "identificador" => "sec0010" "titulo" => "Patients and methods" "secciones" => array:2 [ 0 => array:3 [ "identificador" => "sec0015" "titulo" => "Study design" "secciones" => array:1 [ 0 => array:2 [ "identificador" => "sec0020" "titulo" => "Population" ] ] ] 1 => array:2 [ "identificador" => "sec0025" "titulo" => "Statistical analysis" ] ] ] 6 => array:2 [ "identificador" => "sec0030" "titulo" => "Results" ] 7 => array:2 [ "identificador" => "sec0035" "titulo" => "Discussion" ] 8 => array:2 [ "identificador" => "sec0040" "titulo" => "Conflicts of interest" ] 9 => array:1 [ "titulo" => "References" ] ] ] "pdfFichero" => "main.pdf" "tienePdf" => true "fechaRecibido" => "2020-06-15" "fechaAceptado" => "2020-11-11" "PalabrasClave" => array:2 [ "en" => array:1 [ 0 => array:4 [ "clase" => "keyword" "titulo" => "Keywords" "identificador" => "xpalclavsec1469639" "palabras" => array:4 [ 0 => "Lung cancer" 1 => "Positron emission tomography" 2 => "Ecobronchoscopy" 3 => "Mining exposure" ] ] ] "es" => array:1 [ 0 => array:4 [ "clase" => "keyword" "titulo" => "Palabras clave" "identificador" => "xpalclavsec1469640" "palabras" => array:4 [ 0 => "Cáncer de pulmón" 1 => "Tomografía por emisión de positrones" 2 => "Ecobroncoscopia" 3 => "Exposición a la minería" ] ] ] ] "tieneResumen" => true "resumen" => array:2 [ "en" => array:3 [ "titulo" => "Abstract" "resumen" => "<span id="abst0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0010">Introduction</span><p id="spar0030" class="elsevierStyleSimplePara elsevierViewall">Positron emission tomography (PET) with computerized axial tomography (CT) in a single device is known as PET/CT. It has been widely documented and validated, and it is currently a core part of the diagnosis and staging of lung cancer. However, its reliability has not been analysed in specific populations. The objective of this study is to determine the usefulness of PET/CT in patients exposed to mining activities in which an endobronchial ultrasound (EBUS) has been performed for the diagnosis and/or staging of lung cancer.</p></span> <span id="abst0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0015">Patients and methods</span><p id="spar0035" class="elsevierStyleSimplePara elsevierViewall">With a prospective and real-time database, all the patients who had undergone an EBUS with suspicion of lung cancer and who had previously undergone a PET/CT were selected. The observation unit was the lymph node and, based on their history of exposure to mining activities, the sample was divided into two categories, group 1: not exposed; and group 2: exposed. In each group, and with the results from anatomical pathology as a dependent variable, logistic models were established to look for independent risk factors for malignancy.</p></span> <span id="abst0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0020">Results</span><p id="spar0040" class="elsevierStyleSimplePara elsevierViewall">In group 1, lymph nodes larger than 1 cm and PET/CT uptake with maximum standardized uptake value (SUV<span class="elsevierStyleInf">max</span>) over 2.5 were independent risk factors for malignancy. However, in group 2 (exposed patients), none of those factors were predictors for malignancy.</p></span> <span id="abst0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0025">Discussion</span><p id="spar0045" class="elsevierStyleSimplePara elsevierViewall">In the population of individuals with occupational exposure to mining, PET/CT is an imaging technique with diagnostic limitations for lung cancer.</p></span>" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0005" "titulo" => "Introduction" ] 1 => array:2 [ "identificador" => "abst0010" "titulo" => "Patients and methods" ] 2 => array:2 [ "identificador" => "abst0015" "titulo" => "Results" ] 3 => array:2 [ "identificador" => "abst0020" "titulo" => "Discussion" ] ] ] "es" => array:3 [ "titulo" => "Resumen" "resumen" => "<span id="abst0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0035">Introducción</span><p id="spar0050" class="elsevierStyleSimplePara elsevierViewall">La tomografía por emisión de positrones (PET) en un único equipo junto a la tomografía axial computarizada (TC) es comúnmente denominada PET/TC. Ha sido ampliamente documentada y validada, de tal manera que hoy día forma parte del eje central en el diagnóstico y la estadificación del cáncer de pulmón. Sin embargo, su fiabilidad no ha sido estudiada en poblaciones específicas. El objetivo de esta investigación se centra en determinar la utilidad de la PET/TC en pacientes expuestos a la minería en los que se ha realizado una ecobroncoscopia (EBUS) para diagnóstico y/o estadificación de cáncer de pulmón.</p></span> <span id="abst0030" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0040">Pacientes y métodos</span><p id="spar0055" class="elsevierStyleSimplePara elsevierViewall">Sobre una base de datos prospectiva y en tiempo real, se seleccionaron todos los individuos sometidos a EBUS por sospecha de cáncer de pulmón y que previamente se habían realizado una PET/TC. La unidad de observación fue la adenopatía y, en función del antecedente de exposición a la minería, se dividió la muestra en dos grupos, grupo 1: no expuestos, grupo 2: expuestos. En cada grupo y tomando como variable dependiente los resultados de anatomía patológica, se realizaron modelos logísticos en busca de factores de riesgo independientes de malignidad.</p></span> <span id="abst0035" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0045">Resultados</span><p id="spar0060" class="elsevierStyleSimplePara elsevierViewall">En el grupo 1, el tamaño mayor a 1 cm de las adenopatías y la captación en la PET/TC con valor de captación estándar máximo (SUV<span class="elsevierStyleInf">máx</span>) superior a 2,5, son factores de riesgo independientes de malignidad. Sin embargo, en el grupo 2 (paciente con exposición) ninguno de los factores anteriormente mencionados predice malignidad.</p></span> <span id="abst0040" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0050">Discusión</span><p id="spar0065" class="elsevierStyleSimplePara elsevierViewall">En la población de individuos con exposición laboral a la minería, la PET/TC es una técnica de imagen con limitaciones diagnósticas en el cáncer de pulmón.</p></span>" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "abst0025" "titulo" => "Introducción" ] 1 => array:2 [ "identificador" => "abst0030" "titulo" => "Pacientes y métodos" ] 2 => array:2 [ "identificador" => "abst0035" "titulo" => "Resultados" ] 3 => array:2 [ "identificador" => "abst0040" "titulo" => "Discusión" ] ] ] ] "NotaPie" => array:1 [ 0 => array:2 [ "etiqueta" => "☆" "nota" => "<p class="elsevierStyleNotepara" id="npar0005">Please cite this article as: López Zubizarreta M, Cordovilla Pérez R, Mateo Torracchi A, Guevara Velázquez V. Utilidad de la PET/TC en el diagnóstico y estadificación del cáncer de pulmón tras ecobroncoscopia en población minera. Med Clin (Barc). 2022;158:65–69.</p>" ] ] "multimedia" => array:3 [ 0 => array:8 [ "identificador" => "fig0005" "etiqueta" => "Fig. 1" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr1.jpeg" "Alto" => 1583 "Ancho" => 1583 "Tamanyo" => 148732 ] ] "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at0005" "detalle" => "Fig. " "rol" => "short" ] ] "descripcion" => array:1 [ "en" => "<p id="spar0005" class="elsevierStyleSimplePara elsevierViewall">Anthracotic sample obtained under EBUS guidance.</p>" ] ] 1 => array:8 [ "identificador" => "tbl0005" "etiqueta" => "Table 1" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at0010" "detalle" => "Table " "rol" => "short" ] ] "tabla" => array:2 [ "leyenda" => "<p id="spar0015" class="elsevierStyleSimplePara elsevierViewall">EBUS: endobronchial ultrasound. PET/CT: positron emission tomography with fused computed tomography images. SD: standard deviation. SUV<span class="elsevierStyleInf">max</span>: maximum standardized uptake value.</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 " colspan="2" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Variable</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">Group 1 Non-miners (n = 299) \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">Group 2 Miners (n = 40) \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"><span class="elsevierStyleItalic">p</span> \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 rowgroup " rowspan="2" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Sex</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Male \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">87.2% \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">86.3% \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">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 " rowspan="2" align="left" valign="\n \t\t\t\t\ttop\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">Female \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">12.8% \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">13.7% \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0% \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 rowgroup " rowspan="3" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Age</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleHsp" style=""></span><65 years \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">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">46.4% \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">43.3% \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 " rowspan="2" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.751</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"><span class="elsevierStyleHsp" style=""></span>>65 years \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">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">53.6% \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">56.7% \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">66.2 (±9.5) \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">65.9 (±9.7) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">67.4 (±7.8) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.651 \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 rowgroup " rowspan="3" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Smoking</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">No \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">10.7% \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">12% \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\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% \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " rowspan="3" align="left" valign="\n \t\t\t\t\ttop\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">Active smokers \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">35.1% \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">32.6% \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">53.3% \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">Ex-smokers \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">54.1% \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">55.4% \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">46.7% \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 rowgroup " rowspan="4" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Adenopathy punctured under EBUS guidance</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">4R \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">31.5% \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">34.4% \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">13.3% \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 " rowspan="4" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.026</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">4L \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">16.4% \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">15.8% \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">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">7 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">23.9% \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">22.4% \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">33.3% \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">Other \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">28.2% \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">27.4% \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">33.4% \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 rowgroup " rowspan="3" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Adenopathy size</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleHsp" style=""></span><1 cm \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">55.2% \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">54.9% \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">56.7% \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " rowspan="2" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.861</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"><span class="elsevierStyleHsp" style=""></span>>1 cm \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">44.8% \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">45.1% \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">43.3% \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">10.7 (±4.6) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">10.8 (±4.7) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">10.3 (±3.1) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.723 \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 rowgroup " rowspan="3" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">PET/CT SUV<span class="elsevierStyleInf">max</span></td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><span class="elsevierStyleHsp" style=""></span><2.5 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">36.2% \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">37.2% \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">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 " rowspan="2" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.449</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"><span class="elsevierStyleHsp" style=""></span>>2.5 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">63.8% \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">62.8% \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">70% \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">3.4 (±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">3.4 (±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">3.3 (±2.4) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.991 \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 rowgroup " rowspan="2" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Neoplasm</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">No \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">73.1% \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">70.4% \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">85.2% \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 " rowspan="2" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.000</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">Yes \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">26.9% \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">29.6% \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">14.8% \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab2809555.png" ] ] ] ] "descripcion" => array:1 [ "en" => "<p id="spar0010" class="elsevierStyleSimplePara elsevierViewall">Clinical characteristics of the patients according to their mining exposure.</p>" ] ] 2 => array:8 [ "identificador" => "tbl0010" "etiqueta" => "Table 2" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at0015" "detalle" => "Table " "rol" => "short" ] ] "tabla" => array:2 [ "leyenda" => "<p id="spar0025" class="elsevierStyleSimplePara elsevierViewall">CI: confidence interval. EBUS: endobronchial ultrasound. NA: not applicable. OR: odds ratio. PET/CT: positron emission tomography with fused computed tomography images. SD: standard deviation. SUV<span class="elsevierStyleInf">max</span>: maximum standardized uptake value.</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">Risk factor \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">Mining exposure \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">OR (95% IC) \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 rowgroup " rowspan="2" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Age</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " rowspan="2" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Over 65 years old</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Yes \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">2.577 (1.178–5.641) \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">No \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.320 (0.65–9.12) \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 rowgroup " rowspan="2" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Adenopathy size measured by EBUS</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " rowspan="2" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Greater than 1 cm</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Yes \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">7.224 (3.134–16.651) \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">No \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1.661 (0.245–11.244) \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 rowgroup " rowspan="2" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Adenopathy SUV<span class="elsevierStyleInf">max</span></td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " rowspan="2" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Greater than 2.5</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Yes \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">5.527 (1.979–15.441) \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">No \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.7 (0.095–5.165) \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 rowgroup " rowspan="2" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Tobacco</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " rowspan="2" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Exposure</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Yes \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">6.139 (1.803–20.9) \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">No \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">N/A \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab2809556.png" ] ] ] ] "descripcion" => array:1 [ "en" => "<p id="spar0020" class="elsevierStyleSimplePara elsevierViewall">Malignancy predictors in mediastinal adenopathies according go the subjects’ history of exposure to mining (results of the regression models).</p>" ] ] ] "bibliografia" => array:2 [ "titulo" => "References" "seccion" => array:1 [ 0 => array:2 [ "identificador" => "bibs0005" "bibliografiaReferencia" => array:31 [ 0 => array:3 [ "identificador" => "bib0005" "etiqueta" => "1" "referencia" => array:1 [ 0 => array:1 [ "referenciaCompleta" => "Cancer of the Lung and Bronchus - Cancer Stat Facts. 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