A robust biomarker combining radiomic and CA19.9 information to predict distant relapse-free survival after radiochemotherapy in pancreatic cancer.

Authors

Martina Mori, Marco Fois, Monica Maria Vincenzi, Roberta Tummineri, Laura Giannini, Gabriele Palazzo, Gaia Parma, Miriam Torrisi, Emiliano Spezi, Carolina Bezzi, Catia Carconi, Nicole Liscia, Marina Macchini, Paola Mapelli, Giulia Orsi, Maria Picchio, Antonella Del Vecchio, Arturo Chiti, Michele Reni, Paolo Passoni, Claudio Fiorino, Nadia Gisella Di Muzio

Published in

Digestive and liver disease : official journal of the Italian Society of Gastroenterology and the Italian Association for the Study of the Liver. Oct 16, 2026. Epub Oct 16, 2026.

Abstract

The radiomic feature Statistical Percentile 10% (p10%), extracted from [¹⁸F]FDG-PET images, has been previously identified and validated as a robust predictor of distant progression-free survival (DPFS) in unresectable pancreatic cancer (LAPC). This study aimed to maximize its prognostic potential by combining p10% with CA19.9 serum levels and assessing its generalizability across distinct clinical settings.
We analyzed 287 LAPC patients treated with chemoradiotherapy (CRT) and a validation cohort of 72 patients enrolled in the CASSANDRA trial (resectable/borderline-resectable PDAC). Cox models combined p10% with CA19.9 levels measured before RT in LAPC patients, and before surgery for CASSANDRA patients.
p10% was independently prognostic in both cohorts and its integration with CA19.9 significantly improved the prediction. In the LAPC cohort, the combined model achieved C-index=0.71, with median DPFS of 4.0-vs-15.0 months (p<0.0001;HR=3.22). In the pre-surgery setting (CASSANDRA trial), the model showed good rank-order discrimination (C-index=0.65), with median survival of 11.6 months vs not-reached (p=0.0018). However, the calibration slope of 0.54 suggests that absolute risk prediction requires recalibration in the surgical cohort.
Integrating p10% with CA19.9 provides a broader representation of tumor aggressiveness. The combined biomarkers demonstrate consistent performance across different disease stages supporting their use for treatment personalization.

PMID:
42888071
Bibliographic data and abstract were imported from PubMed on 17 Oct 2026.

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