Risk prediction models for inadequate bowel preparation in colonoscopy: a systematic review and meta-analysis

BACKGROUND: The number of risk prediction models for inadequate bowel preparation (IBP) before colonoscopy has increased in recent years; however, their methodological quality and clinical applicability remain uncertain. OBJECTIVE: This systematic review and meta-analysis aimed to evaluate the performance, methodological rigor, and applicability of existing IBP prediction models. METHODS: A comprehensive search of PubMed, Web of Science, Embase, and the Cochrane Library was conducted from database inception to December 2025. Data were extracted using the CHARMS checklist. Risk of bias and applicability were assessed with PROBAST. A random-effects meta-analysis was performed to pool the area under the curve (AUC) of validated models, and publication bias was evaluated. RESULTS: Nineteen IBP prediction models were included. Most models (89.5%) were developed used logistic regression. The reported incidence of IBP ranged from 6.3% to 33.0%. Diabetes and constipation were the most frequently identified predictors, whereas behavioral factors related to bowel preparation were rarely incorporated. The AUCs of validated models ranged from 0.621 to 0.895. All studies were judged to have a high risk of bias, primarily due to inadequate reporting in the analysis domain. The pooled AUC of 17 validated models was 0.73 (95% CI: 0.70-0.77), indicating acceptable discrimination. CONCLUSION: Existing IBP prediction models demonstrate moderate discriminatory ability but are limited by substantial methodological bias. Future model development should emphasize stronger analytical rigor and incorporate behavioral factors to improve the identification of high-risk patients and enhance colonoscopy outcomes. REGISTRATION: This study protocol was registered with PROSPERO (registration number: CRD420250654134).