Can Wang, Fan Yang, Lichao Qiao, Xiaoxiao Wang, Qi Chen, Hongjin Chen, Yi Li, Xiaoqi Zhang, Xiujun Liao, Lei Cao, Haixia Xu, Yu Xiang, Bolin Yang
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The discriminatory ability and accuracy of the nomograms were evaluated using the receiver operating characteristic (ROC) curves and the area under the ROC curves (AUCs). Additionally, the Kaplan-Meier survival curve was also used further to validate the clinical efficacy of the Cox regression model.</p><p><strong>Results: </strong>The overall prevalence of FI was 22.3% (n = 134 of 600). In the logistic regression model, age at diagnosis (odds ratio [OR], 1.032; P = .033), penetrating behavior of disease (OR, 3.529; P = .008) and Perianal Disease Activity Index score >4 (OR, 3.068; P < .001) were independent risk factors for FI. In the Cox regression model, age at diagnosis (hazard ratio [HR], 1.027; P = .018), Montreal P classification (HR, 2.608; P = .011), and Perianal Disease Activity Index score >4 (HR, 2.190; P = .001) were independent predictors of the prevalence of FI over time. 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引用次数: 0
摘要
背景和目的：大便失禁（FI）是一种常见的主诉，极大地影响了克罗恩病患者（CD）的生活质量，并且与CD的临床特征有关。我们的目的是确定与大便失禁相关的风险因素，并构建一个 CD 患者大便失禁的风险预测模型：这项回顾性研究纳入了 2016 年 6 月至 2021 年 10 月间来自 4 个 IBD 中心的 600 名中国 CD 患者。患者被分配到训练组（480 人）和测试组（120 人）。根据逻辑回归模型和 Cox 回归模型建立了两个提名图，用于预测 CD 患者 FI 的风险因素。使用接收者操作特征曲线（ROC）和 ROC 曲线下面积（AUC）评估了提名图的判别能力和准确性。此外，还使用 Kaplan-Meier 生存曲线进一步验证了 Cox 回归模型的临床疗效：FI的总发病率为22.3%（600人中有134人）。在逻辑回归模型中，诊断时的年龄（比值比 [OR]，1.032；P = .033）、疾病的穿透行为（OR，3.529；P = .008）和肛周疾病活动指数评分大于 4（OR，3.068；P 4，HR，2.190；P = .001）是随着时间推移 FI 患病率的独立预测因素。为了方便风险评分的计算，我们绘制了两个提名图，根据AUCs，它们显示出良好的区分能力：本研究发现了与 FI 患病率相关的 4 个风险因素，并建立了 2 个模型来有效预测 CD 患者的 FI 风险评分，有助于延缓 FI 病程，并通过及时干预改善预后。
Monitoring-Based Model for Personalizing Fecal Incontinence in Patients With Crohn's Disease: A Multicenter Inception Cohort Study.
Background and aims: Fecal incontinence (FI) is a common complaint that greatly affects the quality of life of patients with Crohn's disease (CD) and is associated with the clinical characteristics of CD. We aimed to identify risk factors related to FI and construct a risk prediction model for FI in patients with CD.
Methods: This retrospective study included 600 Chinese patients with CD from 4 IBD centers between June 2016 and October 2021. The patients were assigned to the training (n = 480) and testing cohorts (n = 120). Two nomograms were developed based on the logistic regression and Cox regression models to predict the risk factors for FI in patients with CD. The discriminatory ability and accuracy of the nomograms were evaluated using the receiver operating characteristic (ROC) curves and the area under the ROC curves (AUCs). Additionally, the Kaplan-Meier survival curve was also used further to validate the clinical efficacy of the Cox regression model.
Results: The overall prevalence of FI was 22.3% (n = 134 of 600). In the logistic regression model, age at diagnosis (odds ratio [OR], 1.032; P = .033), penetrating behavior of disease (OR, 3.529; P = .008) and Perianal Disease Activity Index score >4 (OR, 3.068; P < .001) were independent risk factors for FI. In the Cox regression model, age at diagnosis (hazard ratio [HR], 1.027; P = .018), Montreal P classification (HR, 2.608; P = .011), and Perianal Disease Activity Index score >4 (HR, 2.190; P = .001) were independent predictors of the prevalence of FI over time. Two nomograms were developed to facilitate risk score calculation, and they showed good discrimination ability according to AUCs.
Conclusions: In this study, we identified 4 risk factors related to the prevalence of FI and developed 2 models to effectively predict the risk scores of FI in CD patients, helping to delay the course of FI and improve the prognosis with timely intervention.
期刊介绍：
Inflammatory Bowel Diseases® supports the mission of the Crohn''s & Colitis Foundation by bringing the most impactful and cutting edge clinical topics and research findings related to inflammatory bowel diseases to clinicians and researchers working in IBD and related fields. The Journal is committed to publishing on innovative topics that influence the future of clinical care, treatment, and research.
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