Yuan Xinyu, Xu Heli, Zhu Junkai, Yang Zixuan, Pan Boyue, Wu Lin, Chen Huanhuan
Department of Thoracic Surgery, Shengjing Hospital of China Medical University, Shenyang, China.
Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang, China.
NPJ Precis Oncol. 2025 Aug 26;9(1):300. doi: 10.1038/s41698-025-01095-1.
Lung cancer (LC) remains a leading global cause of cancer mortality, with current diagnostic and prognostic methods lacking precision. This meta-analysis evaluated the role of artificial intelligence (AI) in LC imaging-based diagnosis and prognostic prediction. We systematically reviewed 315 studies from major databases up to January 7, 2025. Among them, 209 studies on LC diagnosis yielded a combined sensitivity of 0.86 (0.84-0.87), specificity of 0.86 (0.84-0.87), and AUC of 0.92 (0.90-0.94). For LC prognosis, 106 studies were analyzed: 58 with diagnostic data showed a pooled sensitivity of 0.83 (0.81-0.86), specificity of 0.83 (0.80-0.86), and AUC of 0.90 (0.87-0.92). Additionally, 53 studies differentiated between low- and high-risk patients, with a pooled hazard ratio of 2.53 (2.22-2.89) for overall survival and 2.80 (2.42-3.23) for progression-free survival. Subgroup analyses revealed an acceptable performance. AI exhibits strong potential for LC management but requires prospective multicenter validation to address clinical implementation challenges.
肺癌（LC）仍然是全球癌症死亡的主要原因，目前的诊断和预后方法缺乏精准性。这项荟萃分析评估了人工智能（AI）在基于LC影像的诊断和预后预测中的作用。我们系统回顾了截至2025年1月7日来自主要数据库的315项研究。其中，209项关于LC诊断的研究得出的综合灵敏度为0.86（0.84 - 0.87），特异度为0.86（0.84 - 0.87），曲线下面积（AUC）为0.92（0.90 - 0.94）。对于LC预后，分析了106项研究：58项有诊断数据的研究显示合并灵敏度为0.83（0.81 - 0.86），特异度为0.83（0.80 - 0.86），AUC为0.90（0.87 - 0.92）。此外，53项研究区分了低风险和高风险患者，总生存的合并风险比为2.53（2.22 - 2.89），无进展生存的合并风险比为2.80（2.42 - 3.23）。亚组分析显示了可接受的性能。AI在LC管理方面展现出强大潜力，但需要前瞻性多中心验证以应对临床实施挑战。
