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This study aims to screen NSCLC patients with PD-L1-positive expression and select effective biomarkers for ICI immunotherapy.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Methods<\/jats:title>\n                <jats:p>Collected tumor samples from the Affiliated Cancer Hospital of Xinjiang Medical University and 117 patients with stage III\u2013IV NSCLC were included in the study. All patients were on first- or second-line therapy and not on targeted therapy. Based on the molecular profiles and clinical features, we screened biomarkers for predicting the efficacy of immunotherapy in patients with PD-L1 overexpression.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Results<\/jats:title>\n                <jats:p>117 NSCLC patients receiving ICIs immunotherapy were enrolled. First, we found that immunotherapy was more effective in patients with positive PD-L1 expression. Second, we found that <jats:italic>ROS1<\/jats:italic> gene mutations, <jats:italic>KRAS<\/jats:italic> gene mutations, tumor stage, and the endocrine system diseases history are independent prognostic factors for PD-L1 positive patients. Then we combined independent risk factors and constructed a new Nomogram to predict the therapeutic efficacy of ICIs immunotherapy in PD-L1 positive patients. The Nomogram integrates these factors into a prediction model, and the predicted C-statistic of 3\u00a0months, 6\u00a0months and 12\u00a0months are 0.85, 0.84 and 0.85, which represents the high predictive accuracy of the model.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Conclusions<\/jats:title>\n                <jats:p>We have established a model that can predict the efficacy of ICIs immunotherapy in PD-L1 positive patients. The model consists of <jats:italic>ROS1<\/jats:italic> gene mutations, <jats:italic>KRAS<\/jats:italic> gene mutations, tumor staging, and endocrine system disease history, and has good predictive ability.<\/jats:p>\n              <\/jats:sec>","DOI":"10.1007\/s00432-023-05160-9","type":"journal-article","created":{"date-parts":[[2023,7,19]],"date-time":"2023-07-19T18:03:06Z","timestamp":1689789786000},"page":"12965-12976","update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Screening biomarkers for predicting the efficacy of immunotherapy in patients with PD-L1 overexpression"],"prefix":"10.1007","volume":"149","author":[{"given":"Xiaodan","family":"Zhu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bo","family":"Yu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yanli","family":"Shen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yan","family":"Zhao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiyujing","family":"Fu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yunji","family":"Zhu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Guomin","family":"Gu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chunling","family":"Liu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2023,7,19]]},"reference":[{"issue":"10","key":"5160_CR1","doi-asserted-by":"publisher","first-page":"1653","DOI":"10.1093\/annonc\/mdz288","volume":"30","author":"E Aguilar","year":"2019","unstructured":"Aguilar E, Ricciuti B, Gainor J, Kehl K, Kravets S, Dahlberg S, Nishino M, Sholl L, Adeni A, Subegdjo S et al (2019) Outcomes to first-line pembrolizumab in patients with non-small-cell lung cancer and very high PD-L1 expression. 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