{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,31]],"date-time":"2026-01-31T08:14:24Z","timestamp":1769847264672,"version":"3.49.0"},"reference-count":29,"publisher":"Wiley","issue":"4","license":[{"start":{"date-parts":[[2021,12,30]],"date-time":"2021-12-30T00:00:00Z","timestamp":1640822400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Thoracic Cancer"],"published-print":{"date-parts":[[2022,2]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec><jats:title>Background<\/jats:title><jats:p>Small cell lung cancer (SCLC) is a highly aggressive neuroendocrine tumor with a short replication time and a rapid growth rate. Prognostic factors for SCLC in clinical practice are scarce. Retrospective analysis of 8\u2010year extensive\u2010stage SCLC data from the Department Respiratory and Intensive Care Unit, Peking Union Medical College Hospital (Beijing, China) was performed to develop a risk prediction model that can facilitate the identification of extensive\u2010stage SCLC with differing prognosis in clinical practice.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>A retrospective analysis of data from patients with extensive\u2010stage SCLC at a single\u2010center from January 2013 to January 2021, including age, sex, ECOG physical score, immunohistochemistry (CgA, Syn, CD56, TTF1, and Ki67), staging, treatment regimen, laboratory examinations, and survival period, was performed. Clinical variables with potential prognostic significance were screened by univariate Cox analysis. Next, multifactor Cox risk prediction regression analysis was performed to establish an extensive\u2010stage SCLC risk prognostic model. Survival curves and ROC curves for high and low risk groups were plotted according to risk scores. Nomogram and calibration curves were developed to assess the accuracy of the risk prediction model.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>This study included 300 patients who were diagnosed with extensive\u2010stage SCLC at our center from January 2013 to January 2021. The most common first presentation was respiratory symptoms, especially cough (162, 54%). The most common extra\u2010thoracic metastatic organs were bone (36.3%), liver (24.7%), brain (15.7%), and adrenal glands (15.7%). A total of 99% of patients received first\u2010line systemic therapy, with 86.3% of patients treated with platinum\u2010etoposide and 10.7% of patients treated with immune checkpoint inhibitor combined with platinum\u2010etoposide backbone. First\u2010line progression\u2010free survival was up to 198\u2009days, and the median OS was 439\u2009days. After Cox regression screening and backward stepwise selection, \u201ctime from initial therapy to relapse or progression (PFS1), liver metastases, adrenal metastases, M stage and first\u2010line treatment pattern\u201d were retained to establish a prognostic model with an AUC value of 0.763. The prognostic model was shown as a nomogram with good agreement between predicted and observed outcomes.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusions<\/jats:title><jats:p>The first\u2010line treatment of SCLC patients admitted to our hospital in the past 8\u2009years was relatively standardized, and the progression\u2010free survival and OS were slightly longer than those reported in the literature. We developed a prognostic risk score model for extensive\u2010stage SCLC to calculate individual survival in clinical practice.<\/jats:p><\/jats:sec>","DOI":"10.1111\/1759-7714.14289","type":"journal-article","created":{"date-parts":[[2021,12,31]],"date-time":"2021-12-31T05:10:08Z","timestamp":1640927408000},"page":"539-548","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["Clinical characteristics and prognostic model for extensive\u2010stage small cell lung cancer: A retrospective study over an 8\u2010year period"],"prefix":"10.1111","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5939-8856","authenticated-orcid":false,"given":"Jun","family":"Ni","sequence":"first","affiliation":[{"name":"Department of Pulmonary and Critical Care Medicine, Peking Union Medical Hospital Chinese Academy of Medical Science &amp; Peking Union Medical College  Beijing 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Chinese Academy of Medical Science &amp; Peking Union Medical College  Beijing China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2832-2664","authenticated-orcid":false,"given":"Yan","family":"Xu","sequence":"additional","affiliation":[{"name":"Department of Pulmonary and Critical Care Medicine, Peking Union Medical Hospital Chinese Academy of Medical Science &amp; Peking Union Medical College  Beijing China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jing","family":"Zhao","sequence":"additional","affiliation":[{"name":"Department of Pulmonary and Critical Care Medicine, Peking Union Medical Hospital Chinese Academy of Medical Science &amp; Peking Union Medical College  Beijing China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4040-6115","authenticated-orcid":false,"given":"Minjiang","family":"Chen","sequence":"additional","affiliation":[{"name":"Department of 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