Development and validation of a nomogram for predicting immune-related thyroid dysfunction during immunotherapy in non-small cell lung cancer: a prospective cohort study in China

Background Immune checkpoint inhibitors (ICIs) have improved survival for non-small cell lung cancer (NSCLC) patients, but immune-related adverse events (irAEs), like immune-mediated thyroid dysfunction (IMTD), have been reported. IMTD causes irreversible thyroid damage, affecting NSCLC patients’ quality of life. This study aims to explore IMTD risk factors and develop a Nomogram to predict IMTD risk at 6, 12, and 24 months. Methods Data from 1,917 NSCLC patients from Chongqing University Cancer Hospital treated with ICIs were randomly split into training (70%) and validation (30%) cohorts. After variable selection, a Nomogram with 11 common clinical variables was built from the training cohort. The validation cohort was used to assess the model comprehensively using the Time C-index, Time AUC, Delong test, calibration curves, and decision curve analysis (DCA) to ensure its clinical effectiveness. Results IMTD occurred in 343 (17.89%) patients. Among the 11 model factors, Age (OR = 1.02, 95% CI: 1.01 - 1.04), Female (OR = 1.78, 95% CI: 1.31 - 2.42), Mono (OR = 3.52, 95% CI: 1.72 - 7.17), and TCHO (OR = 1.13, 95% CI: 1.03 - 1.24) were significant IMTD risk factors. WBC and FT4 were protective factors (OR = 0.9, 95% CI: 0.83 - 0.98 and OR = 0.94, 95% CI: 0.90 - 0.97). The Nomogram showed good predictive accuracy and generalizability in both cohorts, with C - indices of 0.77 (95% CI: 0.74 - 0.80) and 0.72 (95% CI: 0.67 - 0.78), and AUC values above 0.7. Kaplan - Meier curves confirmed its effective IMTD risk stratification. Conclusion The developed Nomogram has good predictive performance and can identify high-risk IMTD patients. The web calculators are user-friendly, providing a basis for early clinical intervention to reduce IMTD incidence.