Prediction Models for Bronchopulmonary Dysplasia in Preterm Infants: A Systematic Review and Meta-Analysis.
Romijn M., Dhiman P., Finken MJJ., van Kaam AH., Katz TA., Rotteveel J., Schuit E., Collins GS., Onland W., Torchin H.
ObjectiveTo review systematically and assess the accuracy of prediction models for bronchopulmonary dysplasia (BPD) at 36 weeks' postmenstrual age.Study designSearches were conducted in MEDLINE and EMBASE. Studies published between 1990 and 2022 were included if they developed or validated a prediction model for BPD or the combined outcome death/BPD at 36 weeks in the first 14 days of life in preterm infants. Data were extracted independently by two authors following the Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies (CHARMS) and Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Risk of bias was assessed using the Prediction model Risk Of Bias ASsessment Tool (PROBAST).ResultsSixty-five studies were reviewed, including 158 development and 108 externally validated models. Median c-statistic of 0.84 [range 0.43-1.00] was reported at model development, and 0.77 [range 0.41-0.97] at external validation. All models were rated at high risk of bias, due to limitations in the analysis part. Meta-analysis of the validated models revealed increased c-statistics after the first week of life for both the BPD and death/BPD outcome.ConclusionsAlthough BPD prediction models perform satisfactorily, they were all at high risk of bias. Methodological improvement and complete reporting are needed before they can be considered for use in clinical practice. Future research should aim to validate and update existing models.