Abstract
Background: The development of risk prediction models for chemotherapy-related nausea and vomiting (CINV) in cancer patients has been increasing, while the quality and applicability of these models in clinical practice and future research remain unknown.
Objective: To systematically review published studies on risk prediction models for CINV in patients with cancer.
Design: Systematic review and meta-analysis of observational studies and clinical trials.
Methods: We searched nine electronic databases, including SinoMed, PubMed, Web of Science, The Cochrane Library, Cumulative Index to Nursing and Allied Health Literature (CINAHL), Embase, China National Knowledge Infrastructure (CNKI), Wanfang Database, China Science and Technology Journal Database (VIP), from inception to January 30, 2024. Data from selected studies were extracted, including study design, data source, sample size, predictors, model development, and performance. The Prediction Model Risk of Bias Assessment Tool (PROBAST) checklist was used to assess the risk of bias and applicability.
Results: Twelve studies involving 2215 patients were included. The incidence of CINV in patients with cancer ranged from 17.7 % to 69 %. The most frequently used predictors were age and gender. The reported AUC ranged from 0.66 to 0.85. Twelve studies were found to have a high risk of bias, primarily due to inappropriate reporting of the analysis domain. The pooled AUC value of the six validated models was 0.73 (95 % confidence interval: 0.68–0.79), indicating a fair level of discrimination.
Conclusion: Although the included studies reported a certain level of discrimination in the prediction models of CINV in patients with cancer, all of them were found to have a high risk of bias according to the PROBAST checklist. Future studies should focus on developing new models with larger samples, rigorous study designs, and multicenter external validation.
Registration: The protocol for this study is registered with PROSPERO (registration number: CRD42024507899).