直肠癌的放疗效益大部分基于局部复发减少和肠功能障碍增加之间的平衡。预测术后残疾有助于康复计划和早期干预。我们旨在开发和验证一个风险模型，通过术中特征改善新辅助放射治疗下保肛直肠癌切除术后主要肠功能障碍的预测。邀请在中国三家国家医院接受放射治疗后1年以上保肛切除术的合格患者完成低位前切除综合征（LARS）评分。使用机器学习算法评估临床特征和影像参数。在具有比例权重的关键因素基础上，通过 logistic 回归构建了后放射治疗 LARS 预测模型（PORTLARS）。验证了模型对主要 LARS 预测的准确性。共有868名患者自手术以来平均5.7年时报告的平均LARS评分为28.4。主要 LARS 的关键预测因子包括直肠远端长度、吻合口漏、新直肠近侧结肠和病理分期淋巴结。PORTLARS在内部数据集（0.835，95%置信区间（CI）0.800-0.870，n=521）和外部数据集（0.884，95% CI 0.848-0.921，n=347）预测主要 LARS 的曲线下面积良好。该模型在外部验证中的敏感性和特异性均超过0.83。此外，PORTLARS优于术前LARS评分预测主要事件。PORTLARS能够高精度而稳健地预测经放疗的直肠癌切除术后主要肠功能障碍。它可能作为一个有用的工具，用于早期阶段强调需要额外支持以长期处理功能障碍的患者。© 2023 AGA Institute。由Elsevier Inc.出版。版权所有。

The benefit of radiotherapy for rectal cancer is largely based on a balance between decrease in local recurrence and increase in bowel dysfunction. Predicting postoperative disability is helpful for recovery plans and early intervention. We aimed to develop and validate a risk model to improve the prediction of major bowel dysfunction after restorative rectal cancer resection with neoadjuvant radiotherapy using perioperative features.Eligible patients more than one year after restorative resection following radiotherapy were invited to complete the low anterior resection syndrome (LARS) score in three national hospitals of China. Clinical characteristics and imaging parameters were assessed with machine learning algorithms. The post-radiotherapy LARS prediction model (PORTLARS) was constructed by logistic regression on the basis of key factors with proportional weighs. The accuracy of model for major LARS prediction was internally and externally validated.A total of 868 patients reported mean LARS score of 28.4 after average time of 4.7 years since surgery. Key predictors for major LARS included the length of distal rectum, anastomotic leakage, proximal colon of neorectum, and pathological nodal-stage. PORTLARS had a favorable area under the curve for predicting major LARS in the internal dataset (0.835, 95% confidence interval (CI) 0.800-0.870, n=521) and external dataset (0.884, 95% CI 0.848-0.921, n=347). The model achieved both sensitivity and specificity over 0.83 in the external validation. Additionally, PORTLARS outperformed the pre-operative LARS score for prediction of major events.PORTLARS could predict major bowel dysfunction after rectal cancer resection following radiotherapy with high accuracy and robustness. It may serve as a useful tool to highlight patients who need additional support for long-term dysfunction in the early stage.Copyright © 2023 AGA Institute. Published by Elsevier Inc. All rights reserved.