Prognostic models versus single risk factor approach in first trimester selective screening for gestational diabetes mellitus: a prospective population-based multicentre cohort study.

Objectives To evaluate whether I) first trimester prognostic models for gestational diabetes mellitus (GDM) outperform the currently used single risk factor approach, and II) a first trimester random venous glucose measurement improves model performance. Design Prospective population-based multicentre cohort. Setting 31 independent midwifery practices and six hospitals in the Netherlands. Population Women recruited before 14 weeks of gestation without pre-existing diabetes. Methods The single risk factor approach (presence of ≥1 risk factors: BMI ≥30 kg/m2, previous macrosomia, history of GDM, positive first degree family history of diabetes, non-western ethnicity) was compared to the four best performing models in our previously published external validation study (Gabbay-Benziv 2014, Nanda 2011, Teede 2011, van Leeuwen 2010) with and without the addition of glucose. Main outcome measures Discrimination was assessed by c-statistics, calibration by calibration plots, added value of glucose by the likelihood ratio chi-squared test, net benefit by decision curve analysis, and reclassification by reclassification plots. Results Of the 3,723 included women, a total of 181 (4.9%) developed GDM. The c-statistics of the prognostic models were higher, ranging from 0.74 to 0.78 without and 0.77 to 0.80 with glucose, compared to the single risk factor approach (0.72). Models showed adequate calibration, and yielded a higher net benefit than the single risk factor approach for most threshold probabilities. Teede 2011 performed best in the reclassification analysis. Conclusions First trimester prognostic models seem to outperform the currently used single risk factor approach in screening for GDM, particularly when glucose was added as a predictor.