Prediction Models for Bronchopulmonary Dysplasia in Preterm Infants: A Systematic Review - Peng, Hai-Bo; Zhan, Yuan-Li; Chen, You; Jin, Zhen-Chao; Liu, Fang; Wang, Bo; Yu, Zhang-Bin (Frontiers in Pediatrics, 2022)
Objective: To provide an overview and critical appraisal of prediction models for bronchopulmonary dysplasia (BPD) in preterm infants. Methods: We searched PubMed, Embase, and the Cochrane Library to identify relevant studies (up to November 2021). We included studies that reported prediction model development and/or validation of BPD in preterm infants born at ≤32 weeks and/or ≤1500 g birth weight. We extracted the data independently based on the CHecklist for critical Appraisal and data extraction for systematic Reviews of prediction Modelling Studies (CHARMS). We assessed risk of bias and applicability independently using the Prediction model Risk Of Bias ASsessment Tool (PROBAST). Results: Twenty-one prediction models from 13 studies reporting on model development and 21 models from 10 studies reporting on external validation were included. Oxygen dependency at 36 weeks’ postmenstrual age was the most frequently reported outcome in both development studies (71%) and validation studies (81%). The most frequently used predictors in the models were birth weight (67%), gestational age (62%), and sex (52%). Nearly all included studies had high risk of bias, most often due to inadequate analysis. Small sample sizes and insufficient event patients were common in both study types. Missing data were often not reported or were discarded. Most studies reported on the models’ discrimination, while calibration was seldom assessed (development, 19%; validation, 10%). Internal validation was lacking in 69% of development studies. Conclusions: The included studies had many methodological shortcomings. Future work should focus on following the recommended approaches for developing and validating BPD prediction models.