预测第一代TKI耐药后EGFR突变肺腺癌对免疫检查点抑制剂联合化疗的应答：一项多中心深度学习研究
Predicting response to immune checkpoint inhibitor plus chemotherapy in EGFR-mutant lung adenocarcinoma following first-generation TKI resistance: a multicenter deep learning study.
摘要(中文译文)
表皮生长因子受体（EGFR）突变型肺腺癌患者在一线酪氨酸激酶抑制剂（TKI）治疗后出现耐药且不伴T790M突变时，面临治疗选择有限且欠佳的治疗困境。在这项多中心回顾性研究中，最终可分析建模队列纳入490例具有完整合格CT影像及结局标签的患者，包括训练队列326例、验证队列1 70例和验证队列2 94例。采用AUC、决策曲线分析和PFS分层分析评估模型性能。基于锁定的源预测文件，2.5D轴位模型在训练队列、验证队列1和验证队列2中的AUC分别为0.885、0.819和0.863。基于CT的2.5D深度学习模型在EGFR-TKI耐药后治疗反应预测方面显示出良好性能，但在临床实施前仍需进行前瞻性验证并与临床变量基准进行比较。
Abstract
Patients with epidermal growth factor receptor (EGFR)-mutant lung adenocarcinoma who develop resistance to first-generation tyrosine kinase inhibitors (TKIs) without a T790M mutation face a therapeutic dilemma with limited and suboptimal options. In this multicenter retrospective study, the final analyzable modeling cohort included 490 patients with complete eligible CT imaging and outcome labels, comprising a training cohort of 326 patients, validation cohort 1 of 70 patients, and validation cohort 2 of 94 patients. Model performance was evaluated using AUC, decision curve analysis, and PFS stratification analyses. The 2.5D axial model achieved AUCs of 0.885, 0.819, and 0.863 in the training cohort, validation cohort 1, and validation cohort 2, respectively, based on the locked source prediction files. A CT-based 2.5D deep learning model showed promising performance for treatment-response prediction after EGFR-TKI resistance, but prospective validation and clinical-variable benchmarking remain necessary before clinical implementation.
如何引用
AMA
Shuai Qie, Yasong Shi, Jingyun Li, Sicong Jia, Xiaoping Yin. Predicting response to immune checkpoint inhibitor plus chemotherapy in EGFR-mutant lung adenocarcinoma following first-generation TKI resistance: a multicenter deep learning study.. Frontiers in immunology. 2026; doi:10.3389/fimmu.2026.1760264.
APA
Shuai Qie, Yasong Shi, Jingyun Li, Sicong Jia, Xiaoping Yin (2026). Predicting response to immune checkpoint inhibitor plus chemotherapy in EGFR-mutant lung adenocarcinoma following first-generation TKI resistance: a multicenter deep learning study.. Frontiers in immunology. https://doi.org/10.3389/fimmu.2026.1760264
GB/T 7714
Shuai Qie, Yasong Shi, Jingyun Li, Sicong Jia, Xiaoping Yin. Predicting response to immune checkpoint inhibitor plus chemotherapy in EGFR-mutant lung adenocarcinoma following first-generation TKI resistance: a multicenter deep learning study.[J]. Frontiers in immunology, 2026 doi:10.3389/fimmu.2026.1760264.
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