A prognostic and predictive computational pathology image signature for added benefit of adjuvant chemotherapy in early stage non-small-cell lung cancer

BACKGROUND: We developed and validated a prognostic and predictive computational pathology risk score (CoRiS) using H&E stained tissue images from patients with early-stage non-small cell lung cancer (ES-NSCLC). METHODS: 1330 patients with ES-NSCLC were acquired from 3 independent sources and divided into four cohorts D(1-4). D(1) comprised 100 surgery treated patients and was used to identify prognostic features via an elastic-net Cox model to predict overall and disease-free survival. CoRiS was constructed using the Cox model coefficients for the top features. The prognostic performance of CoRiS was evaluated on D(2) (N=331), D(3) (N=657) and D(4) (N=242). Patients from D(2) and D(3) which comprised surgery + chemotherapy were used to validate CoRiS as predictive of added benefit to adjuvant chemotherapy (ACT) by comparing survival between different CoRiS defined risk groups. FINDINGS: CoRiS was found to be prognostic on univariable analysis, D(2) (hazard ratio (HR) = 1.41, adjusted (adj.) P = .01) and D(3) (HR = 1.35, adj. P < .001). Multivariable analysis showed CoRiS was independently prognostic, D(2) (HR = 1.41, adj. P < .001) and D(3) (HR = 1.35, adj. P < .001), after adjusting for clinico-pathologic factors. CoRiS was also able to identify high-risk patients who derived survival benefit from ACT D(2) (HR = 0.42, adj. P = .006) and D(3) (HR = 0.46, adj. P = .08). INTERPRETATION: CoRiS is a tissue non-destructive, quantitative and low-cost tool that could potentially help guide management of ES-NSCLC patients.