Document Type
Article
Publication Date
6-18-2026
Abstract
Background/Objectives: This study explored whether a multimodal artificial intelligence (MMAI) model integrating digitized histopathology and clinical features can identify prostate cancer patients who may benefit from neoadjuvant hormonal therapy (NHT) and whole-pelvic radiotherapy (WPRT). Methods: This secondary analysis of NRG/RTOG 9413 included NHT-treated patients with digitized biopsy slides and clinical data who were not part of the MMAI model optimization. A previously validated MMAI model estimated long-term risk, and Fine-Gray models evaluated interactions between MMAI-derived scores and the radiation field (WPRT vs. prostate-only RT [PORT]) for biochemical failure (BF), chosen over progression-free survival because of extended follow-up and distant metastasis (DM), with subgroup analyses by predefined MMAI strata. Results: Among 81 eligible patients, the MMAI-by-treatment interaction for BF did not confirm a differential effect (p = 0.30). Therefore, subgroup findings should be interpreted as descriptive and hypothesis-generating. Nevertheless, the magnitude effect of WPRT was numerically greater in the MMAI high-risk subgroup (5-yr: 41% vs. 79%; 10-yr: 47% vs. 79%; aHR 0.35 [0.14–0.86]) than in the low–intermediate group (5-yr: 18% vs. 33%; 10-yr: 44% vs. 57%; aHR 0.66 [0.29–1.48]). Conclusions: Although no statistically significant treatment-by-MMAI interaction was demonstrated, these findings are hypothesis-generating and support further investigation of MMAI approaches for guiding WPRT in NRG/RTOG 0534, 0924, GETUG-01, and POP-RT trials.
Recommended Citation
Sayan, Mutlay; Huang, Huei-Chung; Stewart, Erin L.; Showalter, Timothy N.; Dicker, Adam P.; Grass, George Daniel; Gore, Elizabeth M.; McDonald, Andrew Michael; Pennington, J. Daniel; Hallman, Mark A.; Barani, Igor J.; Hsu, I-Chow; Rooney, Michael; Pugh, Stephanie L.; Nguyen, Paul L.; Tran, Phuoc T.; and Roach Iii, Mack, "A Multimodal Artificial Intelligence Model to Guide Use of Whole-Pelvic Radiation Therapy in Patients with Localized Prostate Cancer: Exploratory Analysis of RTOG 9413" (2026). Department of Radiation Oncology Faculty Papers. Paper 237.
https://jdc.jefferson.edu/radoncfp/237
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
PubMed ID
42352513
Language
English
Comments
This article is the author’s final published version in Cancers, Volume 18, issue 12, 2026, Article number 1982.
The published version is available at https://doi.org/10.3390/cancers18121982. Copyright © 2026 by the authors.