AUTHOR=Pan Teng , Duan Rui , Xu Zihan , He Xiaohan , Luo Xiaojin , Zhou Guanglin , Song Yu , Deng Jinhai , Tan Xuerui , Wei Fengxiang TITLE=GDF-15 as a biomarker for diagnosis and prognosis of lung cancer: a meta-analysis JOURNAL=Frontiers in Oncology VOLUME=Volume 15 - 2025 YEAR=2025 URL=https://www.frontiersin.org/journals/oncology/articles/10.3389/fonc.2025.1447990 DOI=10.3389/fonc.2025.1447990 ISSN=2234-943X ABSTRACT=IntroductionDue to the tendency of lung cancer to be diagnosed at advanced stages, many patients are not eligible for curative surgery. Identifying early detection and prognosis biomarkers is crucial for improving outcomes. This study explores the potential of Growth Differentiation Factor 15 (GDF-15) as a biomarker for these purposes.MethodsA thorough review and meta-analysis of literature from PubMed, Embase, the CENTRAL, and the CNKI was performed. We analyzed the diagnostic accuracy of GDF-15, focusing on its sensitivity, specificity, and AUC. Additionally, we investigated the association between three-year overall survival and GDF-15 levels in lung cancer patients. Our analysis included nine studies, encompassing 1296 patients with lung cancer and 1182 healthy controls.ResultsGDF-15 showed high diagnostic performance with a sensitivity of 0.80 (95% Confidence Interval (CI): 0.71-0.87), specificity of 0.92 (95% CI: 0.85-0.96), diagnostic odds ratio of 45 (95% CI: 25-79), and an AUC of 0.93 (95% CI: 0.90-0.95). Moreover, the prognosis analysis revealed that the plasma GDF-15 levels were significantly higher in patients than controls (standardized mean difference: 2.91, CI 2.79-3.04 and P < 0.00001), and the odds ratio of 3-year overall survival rate was 4.05 (95% CI: 1.92-8.51 and P = 0.0002).DiscussionGDF-15 exhibits strong potential as both a diagnostic and prognostic biomarker in lung cancer, distinguishing effectively between patients and healthy individuals. These findings support its further exploration and potential integration into clinical practice.Systematic Review Registrationhttps://www.crd.york.ac.uk/PROSPERO/, identifier CRD42024519807.