Development and validation of a prediction model using molecular marker for long-term survival in unresectable stage III non-small cell lung cancer treated with chemoradiotherapy

Abstract

Background: This study aimed to establish a predictive nomogram integrating epidermal growth factor receptor (EGFR) mutation status for 3- and 5-year overall survival (OS) in unresectable/inoperable stage III non-small cell lung cancer (NSCLC) treated with definitive chemoradiotherapy. Methods: A total of 533 stage III NSCLC patients receiving chemoradiotherapy from 2013 to 2017 in our institution were included and divided into training and testing sets (2:1). Significant factors impacting OS were identified in the training set and integrated into the nomogram based on Cox proportional hazards regression. The model was subject to bootstrap internal validation and external validation within the testing set and an independent cohort from a phase III trial. The accuracy and discriminative capacity of the model were examined by calibration plots, C-indexes and risk stratifications. Results: The final multivariate model incorporated sex, smoking history, histology (including EGFR mutation status), TNM stage, planning target volume, chemotherapy sequence and radiation pneumonitis grade. The bootstrapped C-indexes in the training set were 0.688, 0.710 for the 3- and 5-year OS. For external validation, C-indexes for 3- and 5-year OS were 0.717, 0.720 in the testing set and 0.744, 0.699 in the external testing cohort, respectively. The calibration plots presented satisfying accuracy. The derivative risk stratification strategy classified patients into distinct survival subgroups successfully and performed better than the traditional TNM staging. Conclusions: The nomogram incorporating EGFR mutation status could facilitate survival prediction and risk stratification for individual stage III NSCLC, providing information for enhanced immunotherapy decision and future trial design.