ArticleZhong nan da xue xue bao. Yi xue ban = Journal of Central South University. Medical sciences2025
[Interpretable machine learning-based predictive model for assessing abdominal surgery risk and biologic therapy efficacy in CDAI 0 to 1 level Crohn disease patients].
Article in Zhong nan da xue xue bao. Yi xue ban = Journal of Central South University. Medical sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
objectivesCrohn disease (CD) patients face a clinically significant high risk of abdominal surgery. This study aims to develop a predictive model for estimating abdominal surgery in CD patients with Crohn Disease Activity Index (CDAI) 0-1.
methodsCD patients treated at the Second Xiangya Hospital of Central South University between 2016 and 2022 were retrospectively enrolled. Using a fixed random seed, the full cohort was randomly split into a training set and a validation set at a 5:5 ratio. Final predictors were selected using multivariable backward stepwise Cox regression, and hazard ratios (
resultsA total of 615 patients were included in the study, comprising 307 patients in the training set and 308 patients in the validation set. Multivariable backward stepwise Cox regression identified 4 key variables significantly associated with abdominal surgery risk in CD patients with CDAI 0-1, including C-reactive protein (CRP,
conclusionsThe CoxBoost model developed in this study effectively predicts abdominal surgery risk in CD patients with CDAI 0-1, and supports clinical decision-making regarding biologic therapy, providing evidence for personalized treatment planning.
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