P331 Risk Factors and Prediction Model for Fecal Incontinence in Patients with Crohn’s Disease: A Multicenter Study
Wang, C.(1)*;Yang, F.(2);Qiao, L.(1);Chen, Q.(1);Chen, H.(1);Li, Y.(3);Zhang, X.(4);Liao, X.(5);Cao, L.(3,6);Xu, H.(1);Xiang, Y.(1);Wang, X.(7);Yang, B.(1);
(1)Affiliated Hospital of Nanjing University of Chinese Medicine- Jiangsu Province Hospital of Chinese Medicine, Department of Colorectal Surgery, Nanjing, China;(2)University of New South Wales, Faculty of Science, Sydney, Australia;(3)Jinling Hospital- Medical School of Nanjing University, Department of General Surgery, Nanjing, China;(4)Nanjing Drum Tower Hospital- The Affiliated Hospital of Nanjing University Medical School, Department of Gastroenterology, Nanjing, China;(5)Key Laboratory of Cancer Prevention- Ministry of Education- The Second Affiliated Hospital, Department of Colorectal Surgery and Oncology, Zhejiang, China;(6)The Second Hospital of Nanjing- Nanjing Hospital Affiliated to Nanjing University of Traditional Chinese Medicine, Department of Gastroenterology, Nanjing, China;(7)Affiliated Hospital of Nanjing University of Chinese Medicine- Jiangsu Province Hospital of Chinese Medicine, Department of GCP Research Center, Nanjing, China; Department of Colorectal Surgery Affiliated Hospital of Nanjing University of Chinese Medicine Jiangsu Province Hospital of Chinese Medicine Nanjing China
Background
Fecal incontinence (FI) is a common complaint that seriously affects the quality of life in patients with Crohn’s disease (CD). We aimed to identify risk factors related to FI and construct a risk prediction model for FI in patients with CD.
Methods
Four hundred and sixty-one patients diagnosed with CD between June 2016 and April 2021 in Jiangsu Province Hospital of Chinese Medicine were retrospectively enrolled in this study and randomly divided into the development (n=368) and internal validation cohort (n=93). FI-related risk factors were selected from the development cohort using the random forest procedure and included in a logistic regression model from which the prediction model was elaborated. The discrimination, calibration and clinical benefit of the model were evaluated by examining the area under the receiver operating characteristic curves, calibration curves and decision curve analysis in internal validation and external validation (using 225 patients from four tertiary hospitals), respectively.
Results
Four independent variables were selected and included in the logistic regression model: body mass index, history of non-fistulizing perianal lesions surgery, the number of loose stools in the last week and perianal disease activity index. A nomogram was developed to facilitate risk score calculation. The model showed good discrimination ability with AUC was 0.798 and 0.780 in the internal and external cohorts, respectively. The calibration curves demonstrated good agreement with the model using the Hosmer-Lemeshow test in both cohorts (internal validation, P = 0.562; external validation, P = 0.383). DCA confirmed the clinical validity of the predictive model.
Conclusion
This study recognized four risk factors related to the prevalence of FI and developed a new model to effectively predict risk scores of FI in CD patients, helping to provide early risk stratification and timely intervention.