Pro-fibrotic Factors as Potential Biomarkers of Anti-fibrotic Drug Therapy in Patients With Idiopathic Pulmonary Fibrosis

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"Benito" "apellidos" => "Rodríguez" ] ] ] ] ] "idiomaDefecto" => "es" "Traduccion" => array:1 [ "en" => array:9 [ "pii" => "S1579212921000094" "doi" => "10.1016/j.arbr.2020.07.018" "estado" => "S300" "subdocumento" => "" "abierto" => array:3 [ "ES" => false "ES2" => false "LATM" => false ] "gratuito" => false "lecturas" => array:1 [ "total" => 0 ] "idiomaDefecto" => "en" "EPUB" => "https://multimedia.elsevier.es/PublicationsMultimediaV1/item/epub/S1579212921000094?idApp=UINPBA00003Z" ] ] "EPUB" => "https://multimedia.elsevier.es/PublicationsMultimediaV1/item/epub/S0300289620302702?idApp=UINPBA00003Z" "url" => "/03002896/0000005700000003/v2_202106060540/S0300289620302702/v2_202106060540/es/main.assets" ] "en" => array:14 [ "idiomaDefecto" => true "cabecera" => "Scientific Letter" "titulo" => "Pro-fibrotic Factors as Potential Biomarkers of Anti-fibrotic Drug Therapy in Patients With Idiopathic Pulmonary Fibrosis" "tieneTextoCompleto" => true "saludo" => "Dear Editor:" "paginas" => array:1 [ 0 => array:2 [ "paginaInicial" => "231" "paginaFinal" => "233" ] ] "autores" => array:1 [ 0 => array:4 [ "autoresLista" => "Lidia Lopez-Lopez, Eva Cabrera Cesar, Estrella Lara, M. Victoria Hidalgo-San Juan, Concepcion Parrado, Elisa Martín-Montañez, Maria Garcia-Fernandez" "autores" => array:7 [ 0 => array:3 [ "nombre" => "Lidia" "apellidos" => "Lopez-Lopez" "referencia" => array:2 [ 0 => array:2 [ "etiqueta" => "a" "identificador" => "aff0005" ] 1 => array:2 [ "etiqueta" => "b" "identificador" => "aff0010" ] ] ] 1 => array:3 [ "nombre" => "Eva" "apellidos" => "Cabrera Cesar" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "a" "identificador" => "aff0005" ] ] ] 2 => array:3 [ "nombre" => "Estrella" "apellidos" => "Lara" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "b" "identificador" => "aff0010" ] ] ] 3 => array:3 [ "nombre" => "M. Victoria" "apellidos" => "Hidalgo-San Juan" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "a" "identificador" => "aff0005" ] ] ] 4 => array:3 [ "nombre" => "Concepcion" "apellidos" => "Parrado" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "c" "identificador" => "aff0015" ] ] ] 5 => array:4 [ "nombre" => "Elisa" "apellidos" => "Martín-Montañez" "email" => array:1 [ 0 => "emartinm@uma.es" ] "referencia" => array:2 [ 0 => array:2 [ "etiqueta" => "d" "identificador" => "aff0020" ] 1 => array:2 [ "etiqueta" => "*" "identificador" => "cor0005" ] ] ] 6 => array:3 [ "nombre" => "Maria" "apellidos" => "Garcia-Fernandez" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "b" "identificador" => "aff0010" ] ] ] ] "afiliaciones" => array:4 [ 0 => array:3 [ "entidad" => "Servicio de Neumología, Hospital Universitario Virgen de la Victoria, Málaga, Spain" "etiqueta" => "a" "identificador" => "aff0005" ] 1 => array:3 [ "entidad" => "Departamento de Fisiología Humana, Facultad de Medicina, Universidad de Málaga, Instituto de Investigación Biomédica de Málaga, Málaga, Spain" "etiqueta" => "b" "identificador" => "aff0010" ] 2 => array:3 [ "entidad" => "Departamento de Histología Humana, Facultad de Medicina, Universidad de Málaga, Instituto de Investigación Biomédica de Málaga, Málaga, Spain" "etiqueta" => "c" "identificador" => "aff0015" ] 3 => array:3 [ "entidad" => "Departamento de Farmacología, Facultad de Medicina, Universidad de Málaga, Instituto de Investigación Biomédica de Málaga, Málaga, Spain" "etiqueta" => "d" "identificador" => "aff0020" ] ] "correspondencia" => array:1 [ 0 => array:3 [ "identificador" => "cor0005" "etiqueta" => "⁎" "correspondencia" => "Corresponding author." ] ] ] ] "titulosAlternativos" => array:1 [ "es" => array:1 [ "titulo" => "Factores profibróticos como potenciales biomarcadores de la terapia antifibrótica en pacientes con fibrosis pulmonar idiopática" ] ] "textoCompleto" => "Idiopathic pulmonary fibrosis (IPF) is a chronic and progressive fatal fibrotic interstitial lung disease of unknown etiology characterized by progressive deposition of extracellular matrix and destruction of alveolar architecture.<a class="elsevierStyleCrossRef" href="#bib0075">1</a> It results in respiratory failure and patients have a poor prognosis, the median survival being about 3–5 years following diagnosis.<a class="elsevierStyleCrossRef" href="#bib0080">2</a> Lung transplantation is the only curative treatment for IPF. However, notable advances have been made in its pharmacological therapy during the last 5 years with the development of new agents designed to inhibit the processes that drive fibrosis.<a class="elsevierStyleCrossRef" href="#bib0085">3</a> Promising results have recently been made public from phase I and II clinical trials with the novel targets of the autotaxin-lysophosphatidic acid (ATX/LPA) pathway,<a class="elsevierStyleCrossRefs" href="#bib0090">4,5</a> and the transforming growth factor-β (TGF-β) pathway<a class="elsevierStyleCrossRefs" href="#bib0100">6,7</a> that are hypothesized to be central in the development of IPF.<a class="elsevierStyleCrossRefs" href="#bib0110">8,9</a> Thus, the ATX inhibitor GLPG1690 was generally well tolerated and exhibited a safety profile similar to placebo, demonstrating favorable effects on mean change from baseline in forced vital capacity (FVC) at week 12 compared to placebo (25mL vs −70mL).<a class="elsevierStyleCrossRef" href="#bib0095">5</a> Two phase III trials are currently ongoing.<a class="elsevierStyleCrossRef" href="#bib0120">10</a> In the case of TGF-β suppression, GSK3008348 an αvβ6 integrin inhibitor administered as an inhaled solution, was also well tolerated with no reports of serious adverse events or clinically significant abnormalities that were attributable to study treatment.<a class="elsevierStyleCrossRef" href="#bib0100">6</a> Due to the increasing interest triggered by the new agents, reliable serum biomarkers would help to improve both diagnostic approach and monitoring of drug effects. Thus, serum levels of surfactant protein A (SP-A), a pulmonary collectin, have been shown to be useful in predicting prognosis or monitoring disease activity.<a class="elsevierStyleCrossRefs" href="#bib0125">11,12</a> Even changes in serum SP-A levels could reflect the outcomes of anti-fibrotic drug therapy with pirfenidone or nintedanib.<a class="elsevierStyleCrossRef" href="#bib0135">13</a> The usefulness of serum biomarkers in patients undergoing anti-fibrotic drug therapy based on (ATX/LPA) and TGF-β pathways is not well characterized. The purpose of this study is to assess whether the pro-fibrotic compounds ATX, LPA and TGF-β, together with SP-A, could serve as potential biomarkers to monitor the therapeutic response of these novel IPF treatments.We here report the results of a single-center study consisted of the measurement of serum levels of pro-fibrotic markers in 29 IPF confirmed patients recruited from the Interstitial Lung Diseases Unit at the Pneumology Service at University Hospital of Malaga ‘Virgen de la Victoria’ during 56 months. Thirty healthy individuals were included as comparison group and paired with sex, age, and smoking status with IPF patients. The local ethics committee approved this study. Prior to enrolment, participants were informed about the study, and provided written informed consent. A multidisciplinary group of Pneumologists, Radiologists and Pathologists established and discussed the diagnostics of IPF cases following the European Respiratory Society/American Thoracic Society/Japanese Respiratory Society/Latin American Thoracic Society criteria.<a class="elsevierStyleCrossRef" href="#bib0075">1</a>The serum levels markers in IPF patients were compared with the levels found in healthy volunteers. The study included a single visit of participants. After providing the informed consent, a pulmonary function test was performed and a whole blood sample was drawn from a vein (venipuncture), and collected after fasted for 8h in tubes containing EDTA (50mM). For plasma preparation, blood was centrifuged at 1200×g for 10min at 4°C and the supernatant was stored in siliconized tubes at −80°C until use. The IPF treatments at the time of venipunture were recorded. Thus, 11 (37.9%) patients were treated with N-acetylcysteine as monotherapy, 3 (10.3%) with systemic corticosteroids and 1 (3.4%) with monoclonal antibodies. In 8 (27.6%), these drugs were taken in combination, together with immunosuppressive drugs (azathioprine or cyclophosphamide) in 3 (10.3%) patients. Levels of ATX, LPA, SP-A and TGF-β1 in serum were measured by sandwich-type enzyme-linked immunosorbent assays, using commercially available ELISA kits (Autotaxin K-5600, LPA K-2800S, Echelon®; SP-A NBP2-76692, Novus Biologicals; TGF-β1 SEA124Hu, Cloud-Clone Corp) according to the manufacturer's instructions. To compare quantitative measures (mean±SD), t-test or Mann–Whitney U test were used, while chi-square test was used for qualitative (%). The receiver-operating characteristic (ROC) curves and Youden index were applied to determine the optimal cut-off of serum markers to distinguish IPF from healthy participants. A significance of 5% (P<.05) was required to consider a difference to be statistically significant. Statistical analysis was performed using SPSS software (version 24.0; IBM SPSS Statistics, Chicago, IL).These two populations showed similar demographics and smoking status (<a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a>) whereas the functional parameters (% predicted) FVC and FEV1 (forced expiratory volume in 1 second) in IPF patients were statistically significantly lower than those in comparison group (<a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a>, P<.001). However, the serum levels of the pro-fibrotic markers in IPF patients were all statistically significantly higher than those in healthy participants. The IPF patients showed a clear increase of 66.66% of TGF-β1 plasma levels (+7.05ng/mL), two-fold more abundant the values of ATX (+557.77ng/mL), and three-fold the LPA values (+257.91nM) (<a class="elsevierStyleCrossRef" href="#tbl0010">Table 2</a>). Similarly, a cohort study found two-fold more abundant lysophosphatidylcholine (a LPA precursor) in IPF patients compared to healthy participants, being proposed as biomarker.<a class="elsevierStyleCrossRef" href="#bib0140">14</a> According to the ROC curve analyses, the sensitivities and specificities estimated of each biomarker are shown in <a class="elsevierStyleCrossRef" href="#tbl0010">Table 2</a>. The serum biomarkers values in IPF patients were all higher than the optimal cut-off values of ATX, LPA and TGF-β1 (869.48ng/mL, 190.25nM and 12.43ng/mL, respectively); whereas the serum biomarkers values in healthy participants were lower (<a class="elsevierStyleCrossRef" href="#tbl0010">Table 2</a>). The areas under the ROC curves (AUC) for IPF patients in comparison with control participants were all ≥0.70 (P<.001), showing LPA and TGF-β1 better AUC profiles to distinguish IPF from healthy individuals (>0.90). Our study also demonstrated a statistically significant increase of SP-A serum levels in IPF patients of 37.58% compared to control (P<.001), being higher than the optimal cut-off values found (<a class="elsevierStyleCrossRef" href="#tbl0010">Table 2</a>). The SP-A AUC (0.74) was similar to ATX AUC, lower than LPA and TGF-β1 AUC profile, which showed the largest AUC for distinguishing IPF from healthy participants (0.96 and 0.94, respectively). Limitations: first, our work is a single-center study, which limits its external validity. Second, the small sample size does not allow studying the effect of different variables (tobacco with a high percentage of smokers, age or time since diagnosis) on the levels of these biomarkers. In conclusion, changes in these serum biomarkers may serve as useful tools for monitoring the novel IPF anti-fibrotic drugs, providing novel insights for further investigations to verify the clinical relevance of these serum biomarkers, mainly LPA and TGF-β, in the context of anti-fibrotic therapies for IPF.<elsevierMultimedia ident="tbl0005"></elsevierMultimedia><elsevierMultimedia ident="tbl0010"></elsevierMultimedia>FundingThe purchase of necessary laboratory reagents was supported in part by Almirall, S.A. The company had no role in the study design, the collection, analysis, or interpretation of data, the writing of the report, or the decision to submit the article for publication." "textoCompletoSecciones" => array:1 [ "secciones" => array:2 [ 0 => array:2 [ "identificador" => "sec0005" "titulo" => "Funding" ] 1 => array:1 [ "titulo" => "References" ] ] ] "pdfFichero" => "main.pdf" "tienePdf" => true "multimedia" => array:2 [ 0 => array:8 [ "identificador" => "tbl0005" "etiqueta" => "Table 1" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at1" "detalle" => "Table " "rol" => "short" ] ] "tabla" => array:3 [ "leyenda" => "Continuous variables are expressed as the mean (± SD). Categorical data are expressed as n (%). Abbreviations: IPF, idiopathic pulmonary fibrosis; FVC, forced vital capacity; FEV1, forced expiratory volume in 1 second; TLC, total lung capacity; DLCO, diffusing capacity for carbon monoxide; COPD, chronic obstructive pulmonary disease; PH, pulmonary hypertension; SAHS, sleep apnea-hypopnea syndrome; NS, non-significant; NE, not evaluated." "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">Characteristics \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">IPF<a class="elsevierStyleCrossRef" href="#tblfn0005">a</a> (n=29) \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">Healthy Individuals (n=30) \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" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="4" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Demographics</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, 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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">63.3±2.7 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">58.3±3.5 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">NS \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-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">Time since diagnosis, months \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">38.9±6.7 \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="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-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">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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">19 (65.5) \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">18 (60) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">NS \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-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">Caucasian \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">29 (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">30 (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">NS \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="4" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"></td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="4" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Smoking status</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 or former 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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">21 (72.4) \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">20 (66.7) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">NS \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-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">Pack/year \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">37.6±4.1 \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">34.23±6.2 \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">NS \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="4" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"></td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="4" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Pulmonary function</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">FVC, % predicted \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">62.6±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">101.8±20 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><.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">FEV1, % predicted \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">74±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">99±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"><.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">TLC, % predicted \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">65±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">NE \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-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">DLCO, % predicted \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">44.4±15.2 \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">NE \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="4" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t"></td></tr><tr title="table-row"><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " colspan="4" align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Comorbidities</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">Arterial hypertension \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">11 (37.9) \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">1 (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="" 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">Cardiomyopathy \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">7 (24.1) \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="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-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">Diabetes mellitus \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">8 (27.6) \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="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-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">Dyslipidemia \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">10 (34.5) \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">1 (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="" 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">Prior diagnosis of COPD \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">2 (6.9) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-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">PH secondary to IPF \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">3 (10.3) \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="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-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">SAHS \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">3 (10.3) \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="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="" valign="\n \t\t\t\t\ttop\n \t\t\t\t"> \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab2615541.png" ] ] ] "notaPie" => array:1 [ 0 => array:3 [ "identificador" => "tblfn0005" "etiqueta" => "a" "nota" => "IPF diagnosis: 27 patients were diagnosed by radiologic definite usual interstitial pneumonia pattern, 2 patients by histopathologic and radiologic pattern." ] ] ] "descripcion" => array:1 [ "en" => "Baseline Characteristics of the Patients in Terms of Demographics, Smoking Status, Pulmonary Function and Comorbidities." ] ] 1 => array:8 [ "identificador" => "tbl0010" "etiqueta" => "Table 2" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at2" "detalle" => "Table " "rol" => "short" ] ] "tabla" => array:3 [ "leyenda" => "ATX: autotaxin; LPA: lysophosphatidic acid; TGF-β1: transforming growth factor-β1; SP-A: surfactant protein A; AUC: area under the curve." "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">Parameter<a class="elsevierStyleCrossRef" href="#tblfn0010">a</a> \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">IPF (n=29) \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">Healthy Individuals (n=30) \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><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">Cut-off Value \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">Sensitivity (%) \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">Specificity (%) \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">AUC \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">ATX (ng/mL) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">1152.1±556.0 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">594.3±326.8 \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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">.037 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">869.48 \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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">72.22 \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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">71.42 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.70 \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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><.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">LPA (nM) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">380.9±171.2 \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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">122.9±48.2 \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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><.001 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">190.25 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">88.88 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">93.33 \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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.96 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><.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">TFGβ1 (ng/mL) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">17.5±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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">10.5±1.2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><.001 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">12.43 \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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">77.77 \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="char" 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 " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.94 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><.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">SP-A (ng/mL) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">20.5±0.3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">14.9±0.6 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><.001 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">19.22 \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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">88.9 \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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">66.7 \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="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t">0.74 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="char" valign="\n \t\t\t\t\ttop\n \t\t\t\t"><.001 \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab2615542.png" ] ] ] "notaPie" => array:1 [ 0 => array:3 [ "identificador" => "tblfn0010" "etiqueta" => "a" "nota" => "The values were detectable in all samples analyzed. ELISA kits, sensitivity limits: Autotaxin K-5600 (3.21ng/mL, Intra-Assay: CV 3%, Inter-Assay: CV 9%); LPA K-2800S (24nM, Intra-Assay: 6.5%–8.7%, Inter-Assay: 8.9%–15.33%); SP-A NBP2-76692 (9.375pg/mL, Intra-Assay: 5.03%, Inter-Assay: 4.83%); TGF-β1 SEA124Hu (6.3pg/mL, Intra-Assay: CV<10%, Inter-Assay: CV<12%)." ] ] ] "descripcion" => array:1 [ "en" => "Serum Levels Markers and ROC Curves Analysis to Distinguish IPF From Healthy Participants." ] ] ] "bibliografia" => array:2 [ "titulo" => "References" "seccion" => array:1 [ 0 => array:2 [ "identificador" => "bibs0015" "bibliografiaReferencia" => array:14 [ 0 => array:3 [ "identificador" => "bib0075" "etiqueta" => "1" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "An official ATS/ERS/JRS/ALAT statement: idiopathic pulmonary fibrosis: evidence-based guidelines for diagnosis and management" "autores" => array:1 [ 0 => array:2 [ "etal" => true "autores" => array:6 [ 0 => "G. 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Scientific Letter

Pro-fibrotic Factors as Potential Biomarkers of Anti-fibrotic Drug Therapy in Patients With Idiopathic Pulmonary Fibrosis

Factores profibróticos como potenciales biomarcadores de la terapia antifibrótica en pacientes con fibrosis pulmonar idiopática

Lidia Lopez-Lopeza,b, Eva Cabrera Cesara, Estrella Larab, M. Victoria Hidalgo-San Juana, Concepcion Parradoc, Elisa Martín-Montañezd,

Corresponding author

emartinm@uma.es

Corresponding author.

, Maria Garcia-Fernandezb

a Servicio de Neumología, Hospital Universitario Virgen de la Victoria, Málaga, Spain

b Departamento de Fisiología Humana, Facultad de Medicina, Universidad de Málaga, Instituto de Investigación Biomédica de Málaga, Málaga, Spain

c Departamento de Histología Humana, Facultad de Medicina, Universidad de Málaga, Instituto de Investigación Biomédica de Málaga, Málaga, Spain

d Departamento de Farmacología, Facultad de Medicina, Universidad de Málaga, Instituto de Investigación Biomédica de Málaga, Málaga, Spain

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    "textoCompleto" => "<span class="elsevierStyleSections"><p id="par0005" class="elsevierStylePara elsevierViewall">Idiopathic pulmonary fibrosis &#40;IPF&#41; is a chronic and progressive fatal fibrotic interstitial lung disease of unknown etiology characterized by progressive deposition of extracellular matrix and destruction of alveolar architecture&#46;<a class="elsevierStyleCrossRef" href="#bib0075"><span class="elsevierStyleSup">1</span></a> It results in respiratory failure and patients have a poor prognosis&#44; the median survival being about 3&#8211;5 years following diagnosis&#46;<a class="elsevierStyleCrossRef" href="#bib0080"><span class="elsevierStyleSup">2</span></a> Lung transplantation is the only curative treatment for IPF&#46; However&#44; notable advances have been made in its pharmacological therapy during the last 5 years with the development of new agents designed to inhibit the processes that drive fibrosis&#46;<a class="elsevierStyleCrossRef" href="#bib0085"><span class="elsevierStyleSup">3</span></a> Promising results have recently been made public from phase I and II clinical trials with the novel targets of the autotaxin-lysophosphatidic acid &#40;ATX&#47;LPA&#41; pathway&#44;<a class="elsevierStyleCrossRefs" href="#bib0090"><span class="elsevierStyleSup">4&#44;5</span></a> and the transforming growth factor-&#946; &#40;TGF-&#946;&#41; pathway<a class="elsevierStyleCrossRefs" href="#bib0100"><span class="elsevierStyleSup">6&#44;7</span></a> that are hypothesized to be central in the development of IPF&#46;<a class="elsevierStyleCrossRefs" href="#bib0110"><span class="elsevierStyleSup">8&#44;9</span></a> Thus&#44; the ATX inhibitor GLPG1690 was generally well tolerated and exhibited a safety profile similar to placebo&#44; demonstrating favorable effects on mean change from baseline in forced vital capacity &#40;FVC&#41; at week 12 compared to placebo &#40;25<span class="elsevierStyleHsp" style=""></span>mL vs &#8722;70<span class="elsevierStyleHsp" style=""></span>mL&#41;&#46;<a class="elsevierStyleCrossRef" href="#bib0095"><span class="elsevierStyleSup">5</span></a> Two phase III trials are currently ongoing&#46;<a class="elsevierStyleCrossRef" href="#bib0120"><span class="elsevierStyleSup">10</span></a> In the case of TGF-&#946; suppression&#44; GSK3008348 an &#945;v&#946;6 integrin inhibitor administered as an inhaled solution&#44; was also well tolerated with no reports of serious adverse events or clinically significant abnormalities that were attributable to study treatment&#46;<a class="elsevierStyleCrossRef" href="#bib0100"><span class="elsevierStyleSup">6</span></a> Due to the increasing interest triggered by the new agents&#44; reliable serum biomarkers would help to improve both diagnostic approach and monitoring of drug effects&#46; Thus&#44; serum levels of surfactant protein A &#40;SP-A&#41;&#44; a pulmonary collectin&#44; have been shown to be useful in predicting prognosis or monitoring disease activity&#46;<a class="elsevierStyleCrossRefs" href="#bib0125"><span class="elsevierStyleSup">11&#44;12</span></a> Even changes in serum SP-A levels could reflect the outcomes of anti-fibrotic drug therapy with pirfenidone or nintedanib&#46;<a class="elsevierStyleCrossRef" href="#bib0135"><span class="elsevierStyleSup">13</span></a> The usefulness of serum biomarkers in patients undergoing anti-fibrotic drug therapy based on &#40;ATX&#47;LPA&#41; and TGF-&#946; pathways is not well characterized&#46; The purpose of this study is to assess whether the pro-fibrotic compounds ATX&#44; LPA and TGF-&#946;&#44; together with SP-A&#44; could serve as potential biomarkers to monitor the therapeutic response of these novel IPF treatments&#46;</p><p id="par0010" class="elsevierStylePara elsevierViewall">We here report the results of a single-center study consisted of the measurement of serum levels of pro-fibrotic markers in 29 IPF confirmed patients recruited from the Interstitial Lung Diseases Unit at the Pneumology Service at University Hospital of Malaga &#8216;Virgen de la Victoria&#8217; during 56 months&#46; Thirty healthy individuals were included as comparison group and paired with sex&#44; age&#44; and smoking status with IPF patients&#46; The local ethics committee approved this study&#46; Prior to enrolment&#44; participants were informed about the study&#44; and provided written informed consent&#46; A multidisciplinary group of Pneumologists&#44; Radiologists and Pathologists established and discussed the diagnostics of IPF cases following the European Respiratory Society&#47;American Thoracic Society&#47;Japanese Respiratory Society&#47;Latin American Thoracic Society criteria&#46;<a class="elsevierStyleCrossRef" href="#bib0075"><span class="elsevierStyleSup">1</span></a></p><p id="par0015" class="elsevierStylePara elsevierViewall">The serum levels markers in IPF patients were compared with the levels found in healthy volunteers&#46; The study included a single visit of participants&#46; After providing the informed consent&#44; a pulmonary function test was performed and a whole blood sample was drawn from a vein &#40;venipuncture&#41;&#44; and collected after fasted for 8<span class="elsevierStyleHsp" style=""></span>h in tubes containing EDTA &#40;50<span class="elsevierStyleHsp" style=""></span>mM&#41;&#46; For plasma preparation&#44; blood was centrifuged at 1200<span class="elsevierStyleHsp" style=""></span>&#215;<span class="elsevierStyleHsp" style=""></span>g for 10<span class="elsevierStyleHsp" style=""></span>min at 4<span class="elsevierStyleHsp" style=""></span>&#176;C and the supernatant was stored in siliconized tubes at &#8722;80<span class="elsevierStyleHsp" style=""></span>&#176;C until use&#46; The IPF treatments at the time of venipunture were recorded&#46; Thus&#44; 11 &#40;37&#46;9&#37;&#41; patients were treated with N-acetylcysteine as monotherapy&#44; 3 &#40;10&#46;3&#37;&#41; with systemic corticosteroids and 1 &#40;3&#46;4&#37;&#41; with monoclonal antibodies&#46; In 8 &#40;27&#46;6&#37;&#41;&#44; these drugs were taken in combination&#44; together with immunosuppressive drugs &#40;azathioprine or cyclophosphamide&#41; in 3 &#40;10&#46;3&#37;&#41; patients&#46; Levels of ATX&#44; LPA&#44; SP-A and TGF-&#946;1 in serum were measured by sandwich-type enzyme-linked immunosorbent assays&#44; using commercially available ELISA kits &#40;Autotaxin K-5600&#44; LPA K-2800S&#44; Echelon&#174;&#59; SP-A NBP2-76692&#44; Novus Biologicals&#59; TGF-&#946;1 SEA124Hu&#44; Cloud-Clone Corp&#41; according to the manufacturer&#39;s instructions&#46; To compare quantitative measures &#40;mean<span class="elsevierStyleHsp" style=""></span>&#177;<span class="elsevierStyleHsp" style=""></span>SD&#41;&#44; <span class="elsevierStyleItalic">t</span>-test or Mann&#8211;Whitney <span class="elsevierStyleItalic">U</span> test were used&#44; while chi-square test was used for qualitative &#40;&#37;&#41;&#46; The receiver-operating characteristic &#40;ROC&#41; curves and Youden index were applied to determine the optimal cut-off of serum markers to distinguish IPF from healthy participants&#46; A significance of 5&#37; &#40;<span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span>&#60;<span class="elsevierStyleHsp" style=""></span>&#46;05&#41; was required to consider a difference to be statistically significant&#46; Statistical analysis was performed using SPSS software &#40;version 24&#46;0&#59; IBM SPSS Statistics&#44; Chicago&#44; IL&#41;&#46;</p><p id="par0020" class="elsevierStylePara elsevierViewall">These two populations showed similar demographics and smoking status &#40;<a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a>&#41; whereas the functional parameters &#40;&#37; predicted&#41; FVC and FEV1 &#40;forced expiratory volume in 1 second&#41; in IPF patients were statistically significantly lower than those in comparison group &#40;<a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a>&#44; <span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span>&#60;<span class="elsevierStyleHsp" style=""></span>&#46;001&#41;&#46; However&#44; the serum levels of the pro-fibrotic markers in IPF patients were all statistically significantly higher than those in healthy participants&#46; The IPF patients showed a clear increase of 66&#46;66&#37; of TGF-&#946;1 plasma levels &#40;&#43;7&#46;05<span class="elsevierStyleHsp" style=""></span>ng&#47;mL&#41;&#44; two-fold more abundant the values of ATX &#40;&#43;557&#46;77<span class="elsevierStyleHsp" style=""></span>ng&#47;mL&#41;&#44; and three-fold the LPA values &#40;&#43;257&#46;91<span class="elsevierStyleHsp" style=""></span>nM&#41; &#40;<a class="elsevierStyleCrossRef" href="#tbl0010">Table 2</a>&#41;&#46; Similarly&#44; a cohort study found two-fold more abundant lysophosphatidylcholine &#40;a LPA precursor&#41; in IPF patients compared to healthy participants&#44; being proposed as biomarker&#46;<a class="elsevierStyleCrossRef" href="#bib0140"><span class="elsevierStyleSup">14</span></a> According to the ROC curve analyses&#44; the sensitivities and specificities estimated of each biomarker are shown in <a class="elsevierStyleCrossRef" href="#tbl0010">Table 2</a>&#46; The serum biomarkers values in IPF patients were all higher than the optimal cut-off values of ATX&#44; LPA and TGF-&#946;1 &#40;869&#46;48<span class="elsevierStyleHsp" style=""></span>ng&#47;mL&#44; 190&#46;25<span class="elsevierStyleHsp" style=""></span>nM and 12&#46;43<span class="elsevierStyleHsp" style=""></span>ng&#47;mL&#44; respectively&#41;&#59; whereas the serum biomarkers values in healthy participants were lower &#40;<a class="elsevierStyleCrossRef" href="#tbl0010">Table 2</a>&#41;&#46; The areas under the ROC curves &#40;AUC&#41; for IPF patients in comparison with control participants were all &#8805;0&#46;70 &#40;<span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span>&#60;<span class="elsevierStyleHsp" style=""></span>&#46;001&#41;&#44; showing LPA and TGF-&#946;1 better AUC profiles to distinguish IPF from healthy individuals &#40;&#62;0&#46;90&#41;&#46; Our study also demonstrated a statistically significant increase of SP-A serum levels in IPF patients of 37&#46;58&#37; compared to control &#40;<span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span>&#60;<span class="elsevierStyleHsp" style=""></span>&#46;001&#41;&#44; being higher than the optimal cut-off values found &#40;<a class="elsevierStyleCrossRef" href="#tbl0010">Table 2</a>&#41;&#46; The SP-A AUC &#40;0&#46;74&#41; was similar to ATX AUC&#44; lower than LPA and TGF-&#946;1 AUC profile&#44; which showed the largest AUC for distinguishing IPF from healthy participants &#40;0&#46;96 and 0&#46;94&#44; respectively&#41;&#46; Limitations&#58; first&#44; our work is a single-center study&#44; which limits its external validity&#46; Second&#44; the small sample size does not allow studying the effect of different variables &#40;tobacco with a high percentage of smokers&#44; age or time since diagnosis&#41; on the levels of these biomarkers&#46; In conclusion&#44; changes in these serum biomarkers may serve as useful tools for monitoring the novel IPF anti-fibrotic drugs&#44; providing novel insights for further investigations to verify the clinical relevance of these serum biomarkers&#44; mainly LPA and TGF-&#946;&#44; in the context of anti-fibrotic therapies for IPF&#46;</p><elsevierMultimedia ident="tbl0005"></elsevierMultimedia><elsevierMultimedia ident="tbl0010"></elsevierMultimedia><span id="sec0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0005">Funding</span><p id="par0025" class="elsevierStylePara elsevierViewall">The purchase of necessary laboratory reagents was supported in part by Almirall&#44; S&#46;A&#46; The company had no role in the study design&#44; the collection&#44; analysis&#44; or interpretation of data&#44; the writing of the report&#44; or the decision to submit the article for publication&#46;</p></span></span>"
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          "leyenda" => "<p id="spar0010" class="elsevierStyleSimplePara elsevierViewall">Continuous variables are expressed as the mean &#40;&#177; SD&#41;&#46; Categorical data are expressed as <span class="elsevierStyleItalic">n</span> &#40;&#37;&#41;&#46; Abbreviations&#58; IPF&#44; idiopathic pulmonary fibrosis&#59; FVC&#44; forced vital capacity&#59; FEV1&#44; forced expiratory volume in 1 second&#59; TLC&#44; total lung capacity&#59; DLCO&#44; diffusing capacity for carbon monoxide&#59; COPD&#44; chronic obstructive pulmonary disease&#59; PH&#44; pulmonary hypertension&#59; SAHS&#44; sleep apnea-hypopnea syndrome&#59; NS&#44; non-significant&#59; NE&#44; not evaluated&#46;</p>"
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                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Characteristics&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">IPF<a class="elsevierStyleCrossRef" href="#tblfn0005"><span class="elsevierStyleSup">a</span></a> &#40;<span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>29&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t">63&#46;3<span class="elsevierStyleHsp" style=""></span>&#177;<span class="elsevierStyleHsp" style=""></span>2&#46;7&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t">58&#46;3<span class="elsevierStyleHsp" style=""></span>&#177;<span class="elsevierStyleHsp" style=""></span>3&#46;5&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t">NS&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t">21 &#40;72&#46;4&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t  " align="left" valign="\n
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                  \t\t\t\t">NS&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>FVC&#44; &#37; predicted&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">62&#46;6<span class="elsevierStyleHsp" style=""></span>&#177;<span class="elsevierStyleHsp" style=""></span>15&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">101&#46;8<span class="elsevierStyleHsp" style=""></span>&#177;<span class="elsevierStyleHsp" style=""></span>20&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#60;&#46;001&nbsp;\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"><span class="elsevierStyleHsp" style=""></span>FEV1&#44; &#37; predicted&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">74<span class="elsevierStyleHsp" style=""></span>&#177;<span class="elsevierStyleHsp" style=""></span>4&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">99<span class="elsevierStyleHsp" style=""></span>&#177;<span class="elsevierStyleHsp" style=""></span>5&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&#60;&#46;001&nbsp;\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"><span class="elsevierStyleHsp" style=""></span>TLC&#44; &#37; predicted&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">65<span class="elsevierStyleHsp" style=""></span>&#177;<span class="elsevierStyleHsp" style=""></span>3&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
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                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">NE&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
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                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
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                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>DLCO&#44; &#37; predicted&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">NE&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="\n
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                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " colspan="4" align="left" valign="\n
                  \t\t\t\t\ttop\n
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                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " colspan="4" align="left" valign="\n
                  \t\t\t\t\ttop\n
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                  \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>Arterial hypertension&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">11 &#40;37&#46;9&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">1 &#40;3&#46;3&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
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                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">7 &#40;24&#46;1&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></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>Diabetes mellitus&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">8 &#40;27&#46;6&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></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>Dyslipidemia&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
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                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">10 &#40;34&#46;5&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">1 &#40;3&#46;3&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-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>Prior diagnosis of COPD&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">2 &#40;6&#46;9&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-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>PH secondary to IPF&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="char" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">3 &#40;10&#46;3&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
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                  \t\t\t\t"><span class="elsevierStyleHsp" style=""></span>SAHS&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t  " align="char" valign="\n
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                  \t\t\t\t">3 &#40;10&#46;3&#41;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="" valign="\n
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                  \t\t\t\t">&nbsp;\t\t\t\t\t\t\n
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                  """
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                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Parameter<a class="elsevierStyleCrossRef" href="#tblfn0010"><span class="elsevierStyleSup">a</span></a>&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-head\n
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                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">IPF &#40;<span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>29&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-head\n
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                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Healthy Individuals &#40;<span class="elsevierStyleItalic">n</span><span class="elsevierStyleHsp" style=""></span>&#61;<span class="elsevierStyleHsp" style=""></span>30&#41;&nbsp;\t\t\t\t\t\t\n
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                  \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">Cut-off Value&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-head\n
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                  \t\t\t\t\ttable-head\n
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                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Specificity &#40;&#37;&#41;&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t\ttable-head\n
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                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">AUC&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t">1152&#46;1<span class="elsevierStyleHsp" style=""></span>&#177;<span class="elsevierStyleHsp" style=""></span>556&#46;0&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t">594&#46;3<span class="elsevierStyleHsp" style=""></span>&#177;<span class="elsevierStyleHsp" style=""></span>326&#46;8&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t  " align="char" valign="\n
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                  \t\t\t\t">&#46;037&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
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                  \t\t\t\t">869&#46;48&nbsp;\t\t\t\t\t\t\n
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                  \t\t\t\t">72&#46;22&nbsp;\t\t\t\t\t\t\n
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Article information

ISSN: 03002896
Original language: English

DOI:10.1016/j.arbres.2020.08.005

The statistics are updated each day

Year/Month	Html	Pdf	Total

2024 October	52	27	79
2024 September	92	22	114
2024 August	116	52	168
2024 July	81	17	98
2024 June	99	22	121
2024 May	122	31	153
2024 April	67	22	89
2024 March	64	22	86
2024 February	66	41	107
2024 January	62	25	87
2023 December	39	26	65
2023 November	63	33	96
2023 October	61	46	107
2023 September	64	39	103
2023 August	68	33	101
2023 July	63	26	89
2023 June	56	15	71
2023 May	53	31	84
2023 April	45	26	71
2023 March	62	21	83
2023 February	68	26	94
2023 January	48	44	92
2022 December	91	20	111
2022 November	102	36	138
2022 October	79	32	111
2022 September	69	29	98
2022 August	67	41	108
2022 July	47	39	86
2022 June	68	40	108
2022 May	56	35	91
2022 April	54	33	87
2022 March	67	38	105
2022 February	21	19	40
2021 June	21	8	29
2021 May	4	2	6
2021 April	9	0	9
2021 March	45	6	51
2021 February	2	2	4
2020 November	1	2	3
2020 October	4	4	8
2020 September	1	2	3

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