Abstract Introduction: A phase II trial at Memorial Sloan Kettering Cancer Center (MSK), IRB #12-045 evaluated cisplatin/gemcitabine +/- PARP inhibitor veliparib in patients with gBRCA1/2 and PALB2 (core homologous repair deficiency; cHRD) and advanced pancreas cancer (PDAC). Although the study found no significant difference in overall survival (OS) between treatment arms, patients receiving veliparib had higher rates of stable disease (SD) or partial response (PR), suggesting heterogeneous treatment benefit within this population (RR 74.1% vs. 65.2%; P = 0.55). Leveraging this trial cohort, the present study aimed to identify CT radiomic signatures predictive of OS and to assess whether changes in radiomic features over time provide additional prognostic value. Methods: We retrospectively analyzed contrast-enhanced CT scans of patients with cHRD and PDAC that were enrolled in the trial. A trained machine learning specialist processed baseline, 6-week, and 3-month scans using an automated pancreas segmentation workflow, and 134 radiomic features were extracted from each scan. Highly correlated features (r 0.9) were removed. We performed univariate Cox proportional hazards method to identify features associated with OS. Significant top two features were integrated into multivariate Cox models to investigate their predictability using repeated 3-fold cross-validation to avoid overfitting. Kaplan-Meier analysis compared OS between radiomics-defined high- and low-risk groups. Results: Among the 26 patients enrolled at MSK, baseline (pre-treatment) CT scans were available for 23 (88%), 6-week scans for 25, and 3-month scans for 24 (92%). Twenty-five patients received cisplatin and gemcitabine, and 16 also receiving veliparib. Radiologist-assessed treatment responses were PR (n = 21), SD (n = 2), and progressive disease (n = 3). Several radiomic features were significantly associated with OS across all three time points, with the top 2 features selected for optimal prognostic stratification. Lower gray-level non-uniformity in the baseline pancreas was associated with worse OS, indicating that increased pancreatic textural homogeneity correlates with poorer outcomes. Delta-radiomics analyses demonstrated that longitudinal changes in pancreatic texture also correlated with OS. Conclusions: CT radiomic features demonstrate prognostic value for overall survival in patients with cHRD and advanced PDAC, supporting radiomics as a promising tool for patient stratification in future trials. Ongoing work is evaluating correlations between radiomic signatures and genomic profiles to further refine predictive models. Citation Format: Sonal Gandhi, Jayasree Chakraborty, Hadi Ghahremannezhad, Richard Do, Natally Horvat, Kenneth H. Yu, Wungki Park, Eileen M. O'Reilly. Prognostic value of CT radiomics in patients with gBRCA1/2 and PALB2 and advanced pancreas cancer abstract. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 2776.
Gandhi et al. (2026) studied this question.