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Background: Anastomotic stricture significantly impacts patients' quality of life and long-term prognosis. However, current clinical practice lacks accurate tools for predicting anastomotic stricture. This study aimed to develop a nomogram to predict anastomotic stricture in patients with rectal cancer who have undergone anterior resection.
Methods: 1542 eligible patients will be recruited for the study. Least absolute shrinkage selection operator (Lasso) analysis will be used to preliminarily select predictors. A prediction model will be constructed using multivariate logistic regression and presented as a nomogram. The performance of the nomogram will be evaluated using receiver operating characteristic (ROC) curves, calibration diagrams, and decision curve analysis (DCA). Internal validation will be conducted by assessing the model's performance on a validation cohort.
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1,542 participants in 2 patient groups
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Data sourced from clinicaltrials.gov
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