Multinational cohort study of artificial intelligence-based assessment of pathologic response to neoadjuvant chemoimmunotherapy in NSCLC

Pathologic response (PR), expressed as the percentage of residual viable tumor (%RVT), has emerged as a surrogate endpoint after neoadjuvant chemoimmunotherapy in non-small cell lung cancer. However, PR assessment is subject to interobserver variability and is insufficiently standardized across institutions and clinical trials. Pooled analysis of four retrospective NSCLC cohorts treated with neoadjuvant chemoimmunotherapy and surgery investigated whether artificial intelligence (AI)-based %RVT scoring would be concordant with expert manual assessment and consistent across cohorts. Overall. 135 patients and 1344 primary-tumor H&E slides were evaluable. Concordance between AI-based and manual assessment was at least moderate across all cohorts. For major pathologic response classicification, the AI algorithm achieved a pooled accuracy of 91% (95% CI 85-95), sensitivity of 90% (82-95), specificity of 93% (81-99), and an AUC ≥ 0.95 in all cohorts. Discordant classifications occurred in 8.9% of cases and were mainly attributable to stromal underrepresentation and misclassification of non-neoplastic elements. The authors conclude that AI-based %RVT scoring was concordant with expert pathologist consensus and consistent across real-world cohorts.