Predicting Mucosal Healing in Crohn's Disease: A Nomogram Model Developed from a Retrospective Cohort

预测克罗恩病黏膜愈合:基于回顾性队列研究建立的列线图模型

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Abstract

PURPOSE: Mucosal healing (MH) has become a therapeutic end point for Crohn's disease (CD). The purpose of this study was to identify potential risk factors responsible for a lower probability of mucosal healing in CD. It also aimed to create and validate a noninvasive tool for predicting mucosal healing in CD to aid clinical decision-making. PATIENTS AND METHODS: We established a derivation cohort diagnosed with CD, in which endoscopic examination was performed before and after treatment at the First Affiliated Hospital of Nanjing Medical University between January 2010 and June 2021. Patient data including demographic and clinical characteristics and treatment details were collected. The achievement of mucosal healing (without ulceration on endoscopic examination) after treatment was the endpoint observed during follow-up. We performed logistic regression analysis to identify factors associated with mucosal healing. These factors were used to develop a model (CD mucosal healing prediction nomogram) to predict mucosal healing in CD. External validation was performed using a new cohort of 60 patients from the Second Affiliated Hospital of Soochow University between January 2012 and June 2021. RESULTS: A total of 331 patients were included in the derivation cohort. We found the following factors to be independently associated with mucosal healing after treatment: disease course <11 months, ulcer size <0.5 cm, Harvey-Bradshaw Index score <9, infliximab treatment, and non-exclusive use of 5-aminosalicylic acid. The model incorporating these factors achieved good discrimination, calibration, and clinical decision curve analysis results on internal validation (C-index: 0.788, 95% confidence interval [CI]: 0.74-0.84). The external validation cohort also demonstrated good discrimination (C-index: 0.785, 95% CI: 0.68-0.90) and calibration. CONCLUSION: The CD mucosal healing prediction nomogram model demonstrated good reliability and validated. It can potentially be developed into a simple and clinically useful tool for predicting mucosal healing in CD.

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