Development and external validation of a prognostic nomogram for event-free survival in resectable non-small cell lung cancer after neoadjuvant chemoimmunotherapy - Qu, Linlin; Sun, Wei; Liu, Xinying; Di, Jiting; Wang, Suxia; Xiong, Yan (Frontiers in Oncology, 2025)
BackgroundCombining multiple prognostic factors can enhance risk assessment for resected non-small cell lung cancer (NSCLC). Our aim was to evaluate the prognostic significance of ypT staging, ypN staging, major pathologic response (MPR) and pathology response in lymph node, and to develop a combined prognostic model to predicting event-free survival in resectable NSCLC patients after neoadjuvant chemoimmunotherapy (NCI).Methods and resultsTwo independent cohorts (derivation, n=208; external validation, n=91) were utilized. Pathologic assessment and ypTNM staging followed recommendations from the International Association for the Study of Lung Cancer (IASLC) and the 8th edition AJCC TNM classification. The evaluation of lymph node is documented according to IASLC recommendations, and the mean metastatic tumor size (MTS) in lymph node was evaluated in each case. MPR was defined as ≤10% residual visible tumor in the tumor bed. The survival endpoint was event-free survival (EFS). Univariate and multivariate survival analyses identified nonMPR (HR, 2.860; 95% CI, 1.245-6.567, p=0.013), ypT3/4 (HR, 3.987; 95% CI, 1.496-10.629, p=0.006), and MTS (MTS ≤ 4.5mm vs negative; HR, 4.059; 95% CI, 1.558-10.571, p=0.004; MTS>4.5mm vs negative; HR, 6.871; 95% CI, 1.713-27.564, p=0.007) were independent adverse prognostic factors in the derivation cohort. We built a nomogram model including ypT stage, MPR and pathology response in lymph node to predict EFS, demonstrating high efficacy in both derivation (the Area Under Curve, AUC = 0.77) and external validation cohorts (AUC = 0.72). The Risk Stratification System showed that the EFS of low-risk patients was considerably better than that of high-risk patients (P < 0.0001).ConclusionsPrognostic model integrating ypT staging, MPR and the mean MTS improves EFS prediction for NSCLC following NCI.