The suboptimal clinical applicability of prognostic prediction models for severe postpartum hemorrhage: a meta-epidemiological study

• Published in: Journal of clinical epidemiology Vol. 173; p. 111424
• Main Authors: Liu, Chunrong, Xiong, Yiquan, Zhao, Peng, Chen, Meng, Wei, Wanqiang, Sun, Xin, Liu, Xinghui, Tan, Jing
• Format: Journal Article
• Language: English
• Published: United States Elsevier Inc 01.09.2024; Elsevier Limited
• Subjects: Bias; Biostatistics; Blood transfusions; Calibration; Classification; Clinical applicability; Clinical medicine; Clinical use scenarios; Epidemiology; Hemorrhage; Meta-epidemiology; Obstetrics; Performance prediction; Postpartum; Prediction models; Pregnancy; Prognostic prediction model; Questionnaires; Risk of bias; Severe postpartum hemorrhage; Time measurement; Clinical use scenarios; Prognostic prediction model; Clinical applicability; Meta-epidemiology; Risk of bias; Severe postpartum hemorrhage
• ISSN: 0895-4356; 1878-5921; 1878-5921
• DOI: 10.1016/j.jclinepi.2024.111424

To systematically investigate clinical applicability of the current prognostic prediction models for severe postpartum hemorrhage (SPPH). A meta-epidemiological study of prognostic prediction models was conducted for SPPH. A pre-designed structured questionnaire was adopted to extract the study characteristics, predictors and the outcome, modeling methods, predictive performance, the classification ability for high-risk individuals, and clinical use scenarios. The risk of bias among studies was assessed by the Prediction model Risk Of Bias ASsessment Tool (PROBAST). Twenty-two studies containing 27 prediction models were included. The number of predictors in the final models varied from 3 to 53. However, one-third of the models (11) did not clearly specify the timing of predictor measurement. Calibration was found to be lacking in 10 (37.0%) models. Among the 20 models with an incidence rate of predicted outcomes below 15.0%, none of the models estimated the area under the precision-recall curve, and all reported positive predictive values were below 40.0%. Only two (7.4%) models specified the target clinical setting, while seven (25.9%) models clarified the intended timing of model use. Lastly, all 22 studies were deemed to be at high risk of bias. Current SPPH prediction models have limited clinical applicability due to methodological flaws, including unclear predictor measurement, inadequate calibration assessment, and insufficient evaluation of classification ability. Additionally, there is a lack of clarity regarding the timing for model use, target users, and clinical settings. These limitations raise concerns about the reliability and usefulness of these models in real-world clinical practice. [Display omitted]