Zhang, Y., Brand, D., Shen, Z. et al. (13 more authors) (2025) Predicting acute diarrhoea in rectal cancer chemoradiotherapy: Secondary analysis of the phase III ARISTOTLE trial. Radiotherapy & Oncology, 210. 111032. ISSN 0167-8140
Abstract
Background Neoadjuvant chemoradiotherapy is a standard treatment for locally advanced rectal cancer, but acute diarrhoea remains a significant side effect, affecting the completion of chemoradiotherapy treatment. Purpose This study aimed to predict acute diarrhoea after neoadjuvant chemoradiotherapy for rectal cancer and further develop a strategic tool to individualise rectal cancer treatment. Materials and methods The ARISTOTLE trial is a phase III trial comparing capecitabine chemo-radiotherapy (CRT) versus capecitabine-irinotecan CRT as a pre-operative treatment for locally advanced rectal cancer. We included 589 trial patients across 73 institutions. The volume of the AI-segmented small bowel receiving at least 10 Gy (V10Gy) was used alongside the treatment arm, patient age, and performance status in a logistic regression model to predict a more than 2-grade increase in acute diarrhoea toxicity from baseline (ΔG ≥ 2). Finally, based on the prediction, we identified a sub-cohort of patients for whom a viable dose decrease would result in a reduction of toxicity, and conversely, we also identified individuals for whom adding irinotecan may not cause toxicity. Results The average mean receiver operating characteristic curve (AUROC) for predicting ΔG ≥ 2 is 0.71 [95 % CI 0.58–0.82] on the independent test dataset. Based on the prediction, we identified 71 patients (14 %) who could potentially benefit from irinotecan addition without a dose decrease to maintain ΔG < 2, and 77 patients (15 %) who could potentially benefit from irinotecan addition but need a dose decrease to maintain ΔG < 2. Conclusion The multi-institutional cohort of 73 centres strengthens the reliability of these findings, demonstrating the model’s potential as a strategic tool to individualise rectal cancer treatment while mitigating severe diarrhoea.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2025 The Authors. This is an open access article under the terms of the Creative Commons Attribution License (CC-BY 4.0), which permits unrestricted use, distribution and reproduction in any medium, provided the original work is properly cited. |
Keywords: | Rectal cancer, Radiotherapy, Acute diarrhoea, Predictive model, Clinical application, Machine learning |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Medicine and Health (Leeds) > School of Medicine (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 17 Jul 2025 14:32 |
Last Modified: | 17 Jul 2025 14:32 |
Status: | Published |
Publisher: | Elsevier |
Identification Number: | 10.1016/j.radonc.2025.111032 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:229241 |