<HashMap><database>biostudies-literature</database><scores/><additional><omics_type>Unknown</omics_type><volume>13(11)</volume><submitter>Song R</submitter><pubmed_abstract>&lt;h4>Background&lt;/h4>Cachexia is observed in around 60% of patients with extensive-stage small cell lung cancer (ES-SCLC) and may play an important role in the development of resistance to immunotherapy. This study aims to evaluate the influence of cachexia on the effectiveness of immunotherapy, develop and assess a deep learning (DL)-based prediction model for cachexia, as well as its prognostic value.&lt;h4>Methods&lt;/h4>The analysis encompassed ES-SCLC patients who received the combination of first-line immunotherapy and chemotherapy from Shandong Cancer Hospital and Institute, Qilu Hospital, and Jining First People's Hospital. Survival analysis was conducted to examine the correlation between cachexia and the efficacy of immunotherapy. Medical records and computed tomography (CT) images of th</pubmed_abstract><journal>Translational lung cancer research</journal><pagination>2958-2971</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC11632437</full_dataset_link><repository>biostudies-literature</repository><pubmed_title>Construction and validation of deep learning model for cachexia in extensive-stage small cell lung cancer patients treated with immune checkpoint inhibitors: a multicenter study.</pubmed_title><pmcid>PMC11632437</pmcid><pubmed_authors>Zheng Z</pubmed_authors><pubmed_authors>Zheng Y</pubmed_authors><pubmed_authors>Fan X</pubmed_authors><pubmed_authors>He J</pubmed_authors><pubmed_authors>Song R</pubmed_authors><pubmed_authors>Wang C</pubmed_authors><pubmed_authors>Li B</pubmed_authors><pubmed_authors>Wang X</pubmed_authors><pubmed_authors>Wang L</pubmed_authors></additional><is_claimable>false</is_claimable><name>Construction and validation of deep learning model for cachexia in extensive-stage small cell lung cancer patients treated with immune checkpoint inhibitors: a multicenter study.</name><description>&lt;h4>Background&lt;/h4>Cachexia is observed in around 60% of patients with extensive-stage small cell lung cancer (ES-SCLC) and may play an important role in the development of resistance to immunotherapy. This study aims to evaluate the influence of cachexia on the effectiveness of immunotherapy, develop and assess a deep learning (DL)-based prediction model for cachexia, as well as its prognostic value.&lt;h4>Methods&lt;/h4>The analysis encompassed ES-SCLC patients who received the combination of first-line immunotherapy and chemotherapy from Shandong Cancer Hospital and Institute, Qilu Hospital, and Jining First People's Hospital. Survival analysis was conducted to examine the correlation between cachexia and the efficacy of immunotherapy. Medical records and computed tomography (CT) images of th</description><dates><release>2024-01-01T00:00:00Z</release><publication>2024 Nov</publication><modification>2025-04-04T02:33:14.789Z</modification><creation>2025-04-04T02:33:14.789Z</creation></dates><accession>S-EPMC11632437</accession><cross_references><pubmed>39670020</pubmed><doi>10.21037/tlcr-24-543</doi></cross_references></HashMap>