PMASD risk models show AUC 0.812 to 0.914 but high bias limits clinical use

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Frontiers in Medicine Published June 4, 2026 Medically reviewed June 4, 2026 DOI ↗ By Dr. Amelia Tan, PhD · Internal Medicine & Chronic Disease

Key Takeaway

Consider that PMASD prediction models have variable accuracy but high bias limits clinical application.

This is a systematic review and meta-analysis of risk prediction models for peristomal moisture-associated skin damage (PMASD) in patients with enterostomy. The review synthesized 11 models from 10 studies, finding that the incidence rate of PMASD ranged from 22.8% to 59.1% across the models. The area under the curve (AUC) for these models ranged from 0.812 to 0.914, indicating varying predictive performance. The strongest predictors identified were history of radiotherapy, type of stoma, stoma opening height, and surgical wound in the plate area.

The authors acknowledge that all included models exhibited a substantial risk of bias, which limits their clinical applicability. Methodological quality and generalizability of the existing models remain uncertain. The review does not establish causation and cautions against overstating predictive ability.

Practice relevance is limited by the high risk of bias, though the models may offer utility in directing prophylactic strategies for PMASD. Clinicians should interpret these findings cautiously given the methodological limitations.

Study Details

Study typeMeta analysis

EvidenceLevel 1

PublishedJun 2026

View Original Abstract ↓

BackgroundPeristomal Moisture-associated Skin Damage (PMASD) is a complication of enterostomy that significantly increases the healthcare burden and contributes to poorer patient prognoses. Risk prediction models for PMASD offer significant utility in directing prophylactic strategies. However, the methodological quality and applicability of existing models remain uncertain.ObjectiveThis study aims to systematically identify and critically evaluate currently available risk prediction models for PMASD.MethodsPubMed, the Cochrane Library, Embase, Web of Science, CINAHL, Scopus, China National Knowledge Infrastructure (CNKI), China Science and Technology Journal Database (VIP), Wanfang Database, and Chinese Biomedical literature Database (CBM) were systematically searched from inception to 1 January 2026. Two researchers independently screened the literature and extracted and evaluated information based on the Prediction Model Risk of Bias Assessment Tool (PROBAST) and Data Extraction for Systematic Reviews of Prediction Modeling Studies (CHARMS). R4.4.0 software was used to conduct meta-analysis.ResultsA total of 11 prediction models from 10 studies were included, with an incidence rate ranging from 22.8 to 59.1%. All studies indicated a substantial risk of bias, thus limiting their utility in clinical practice. The area under the curve (AUC) values of 11 models ranged from 0.812 to 0.914. The history of radiotherapy, type of stoma, stoma opening height, and surgical wound in the plate area were identified as the strongest predictors. In total, three studies validated the model externally, and six studies validated the model through an integration of internal and external methods, whereas one study did not undergo any validation after model development.ConclusionIn this systematic review, although most models performed well in terms of applicability, all models exhibited inherent limitations due to a high risk of bias. In the future, large-sample, multicenter, and high-quality prospective clinical studies should be carried out to optimize the predictive models, so as to improve their predictive ability and clinical application value.Systematic trial registrationidentifier: CRD420251089071.