Evaluation of longitudinal image-derived AI prognostication as a predictor of overall survival (OS) in a phase 3 advanced non-small cell lung cancer (aNSCLC) trial.

Abstract

1552 Background: Confidently anticipating an overall survival (OS) benefit in cancer care and therapeutic research is a defining challenge. AI tools may offer longitudinal measurements that predict OS differences objectively from existing data. Longitudinal imaging-based prognostication (IPRO-Δ), a fully automated deep learning system, was independently trained on real-world imaging data to predict survival from pairs of longitudinal computed tomography (CT) scans. Methods: We retrospectively assessed and compared how IPRO-Δ and percent change in RECIST sum of longest diameters (ΔSLD) predicted OS from 165 pairs of baseline and week 13 CT scans acquired in NExUS (NCT00449033), a phase 3 randomized controlled trial evaluating chemotherapy in combination with either sorafenib or placebo for first-line treatment of subjects with aNSCLC. The two study arms did not show a difference in OS and were combined for this analysis. To examine the association of IPRO-Δ and ΔSLD with OS, we measured the concordance index (c-index) and the standardized hazard ratios (HRs, change in risk for a one-standard-deviation increase in the marker). We also report median OS (mOS) for patients with partial response (PR, n = 60), stable disease (SD, n = 83) and progressive disease (PD, n = 22) at week 13, as defined by RECIST 1.1 guidelines (zero patients had a complete response). To explore the stratification potential of IPRO-Δ, we also define equivalent strata by ordering patients by their IPRO-Δ score and maintaining the same proportions (e.g., the top 60 patients by IPRO-Δ would be IPRO-PR, while the bottom 22 patients would be IPRO-PD), and report the mOS for these strata. Results: For the combined trial arms, median OS was 10.9 months (95% CI: 8.6 – 13.6), 108 (65.4%) were male, and 145 (87.9%) were diagnosed as stage IV. Table 1 reports the c-index, HR and stratified mOS values for both survival markers. Conclusions: At week 13 in NExUS, IPRO-Δ predicted OS differences significantly better than ΔSLD. Future work will explore how IPRO-Δ could serve as the basis for a surrogate endpoint in aNSCLC trials. Summary of association of IPRO-Δ and ΔSLD with OS. IPRO-Δ @ Week 13 (95% CI) ΔSLD @ Week 13 (95% CI) p -value C-Index 0.654 (0.604 – 0.713) 0.543 (0.495 – 0.599) <0.01 HR (1SD) 1.72 (1.38 – 2.15) 1.14 (0.94 – 1.38) <0.01 OS (months, PR / SD / PD or IPRO equivalent) 16.5 / 10.9 / 5.7 12.5 / 12.3 / 4.6 -