Umar Nosheen, Wambua Steven, Harvey Phil, Cusworth Samuel, Nirantharakumar Krish, Haroon Shamil, Trudgill Nigel, Adderley Nicola J
Department of Gastroenterology, Sandwell and West Birmingham NHS Trust, West Bromwich, United Kingdom.
Institute of Applied Health Research, University of Birmingham, Birmingham, United Kingdom.
J Crohns Colitis. 2025 Apr 4;19(4). doi: 10.1093/ecco-jcc/jjaf044.
Patients with inflammatory bowel disease (IBD) may experience delays in their diagnosis. This study aimed to develop and validate a risk prediction tool for IBD.
A retrospective cohort study was conducted using primary care data from 2010 to 2019, including symptomatic patients aged ≥18. UK-based primary care databases linked to hospital records were utilized for model development and validation. Cox proportional hazards models were used to derive risk equations for IBD, ulcerative colitis (UC), and Crohn's disease (CD) in men and women. Candidate predictors included demographics, comorbidities, symptoms, extraintestinal manifestations, and laboratory results. Model performance was evaluated using measures of fit, discrimination, and calibration at 1, 2, 3, and 5 years after symptom onset.
In total, 2 054 530 patients were included in the derivation cohort and 673 320 in the validation cohort. In the derivation cohort, 0.7% were diagnosed with IBD (66.3% UC and 33.7% CD). Predictors in the final IBD model included age, smoking, body mass index, gastrointestinal symptoms, extraintestinal manifestations, comorbidities, family history of IBD, and laboratory investigations. The model demonstrated good discrimination and calibration; C-statistic 0.78 (95% confidence interval [CI], 0.77-0.79) in men and 0.78 (95% CI, 0.77-0.79) in women. In the validation cohort, the model tended to slightly overestimate IBD risk at higher risk thresholds.
A risk model using patient demographics, symptoms, and laboratory results accurately predicted IBD, UC, and CD at 1, 2, 3, and 5 years after symptom onset, potentially aiding in prioritizing patients for a referral or fecal calprotectin testing in primary care.
炎症性肠病（IBD）患者的诊断可能会出现延迟。本研究旨在开发并验证一种IBD风险预测工具。
采用2010年至2019年的基层医疗数据进行回顾性队列研究，纳入年龄≥18岁的有症状患者。利用与医院记录相关联的英国基层医疗数据库进行模型开发和验证。采用Cox比例风险模型推导男性和女性IBD、溃疡性结肠炎（UC）及克罗恩病（CD）的风险方程。候选预测因素包括人口统计学特征、合并症、症状、肠外表现及实验室检查结果。在症状出现后1年、2年、3年和5年，使用拟合度、区分度和校准度指标评估模型性能。
推导队列共纳入2054530例患者，验证队列纳入673320例患者。在推导队列中，0.7%的患者被诊断为IBD（66.3%为UC，33.7%为CD）。最终IBD模型中的预测因素包括年龄、吸烟情况、体重指数、胃肠道症状、肠外表现、合并症、IBD家族史及实验室检查。该模型显示出良好的区分度和校准度；男性的C统计量为0.78（95%置信区间[CI]，0.77 - 0.79），女性为0.78（95%CI，0.77 - 0.79）。在验证队列中，该模型在较高风险阈值时往往会略微高估IBD风险。
一种利用患者人口统计学特征、症状和实验室检查结果的风险模型，能够在症状出现后1年、2年、3年和5年准确预测IBD、UC和CD，这可能有助于在基层医疗中对患者进行转诊或粪便钙卫蛋白检测的优先排序。
