Accuracy of body mass index in predicting pre-eclampsia: bivariate meta-analysis

Objective The objective of this study was to determine the accuracy of body mass index (BMI) (pre-pregnancy or at booking) in predicting pre-eclampsia and to explore its potential for clinical application. Design Systematic review and bivariate meta-analysis. Setting Medline, Embase, Cochrane Library, MEDION, manual searching of reference lists of review articles and eligible primary articles, and contact with experts. Population Pregnant women at any level of risk in any healthcare setting. Methods Reviewers independently selected studies and extracted data on study characteristics, quality, and accuracy. No language restrictions. Main outcome measures Pooled sensitivities and specificities (95% CI), a summary receiver operating characteristic curve, and corresponding likelihood ratios (LRs). The potential value of BMI was assessed by combining its predictive capacity for different prevalences of pre-eclampsia and the therapeutic effectiveness (relative risk 0.90) of aspirin. Results A total of 36 studies, testing 1 699 073 pregnant women (60 584 women with pre-eclampsia), met the selection criteria. The median incidence of pre-eclampsia was 3.9% (interquartile range 1.4-6.8). The area under the curve was 0.64 with 93% of heterogeneity explained by threshold differences. Pooled estimates (95% CI) for all studies with a BMI >= 25 were 47% (33-61) for sensitivity and 73% (64-83) for specificity; and 21% (12-31) and 92% (89-95) for a BMI >= 35. Corresponding LRs (95% CI) were 1.7 (0.3-11.9) for BMI >= 25 and 0.73 (0.22-2.45) for BMI < 25, and 2.7 (1.0-7.3) for BMI >= 35 and 0.86 (0.68-1.07) for BMI < 35. The number needed to treat with aspirin to prevent one case of pre-eclampsia ranges from 714 (no testing, low-risk women) to 37 (BMI >= 35, high-risk women). Conclusions BMI appears to be a fairly weak predictor for pre-eclampsia. Although BMI is virtually free of cost, noninvasive, and ubiquitously available, its usefulness as a stand-alone test for risk stratification must await formal cost-utility analysis. The findings of this review may serve as input for such analyses.