External validation of prognostic models to predict risk of gestational diabetes mellitus in one Dutch cohort: prospective multicentre cohort study

Abstract

ObjeCtiveTo perform an external validation and direct comparison of published prognostic models for early prediction of the risk of gestational diabetes mellitus, including predictors applicable in the first trimester of pregnancy. DesignExternal validation of all published prognostic models in large scale, prospective, multicentre cohort study. setting 31 independent midwifery practices and six hospitals in the Netherlands. PartiCiPantsWomen recruited in their first trimester (<14 weeks) of pregnancy between December 2012 and January 2014, at their initial prenatal visit. Women with pre-existing diabetes mellitus of any type were excluded. Main OutCOMe MeasuresDiscrimination of the prognostic models was assessed by the C statistic, and calibration assessed by calibration plots. results 3723 women were included for analysis, of whom 181 (4.9%) developed gestational diabetes mellitus in pregnancy. 12 prognostic models for the disorder could be validated in the cohort. C statistics ranged from 0.67 to 0.78. Calibration plots showed that eight of the 12 models were well calibrated.The four models with the highest C statistics included almost all of the following predictors: maternal age, maternal body mass index, history of gestational diabetes mellitus, ethnicity, and family history of diabetes. Prognostic models had a similar performance in a subgroup of nulliparous women only. Decision curve analysis showed that the use of these four models always had a positive net benefit. COnClusiOnsIn this external validation study, most of the published prognostic models for gestational diabetes mellitus show acceptable discrimination and calibration. The four models with the highest discriminative abilities in this study cohort, which also perform well in a subgroup of nulliparous women, are easy models to apply in clinical practice and therefore deserve further evaluation regarding their clinical impact. IntroductionIn the field of obstetrics, the number of publications on prognostic models has more than tripled in the past decade, 1 which reflects an increasing interest in risk based medicine. Risk based medicine aims to provide the most appropriate care to each patient, often guided by outcome risk estimates based on individual patient characteristics, test results, or even genetic information. 2 As a result of the obesity pandemic, the incidence of gestational diabetes mellitus, notably occurring in the second or third trimester, is rising and is increasingly contributing to perinatal complications such as macrosomia, shoulder dystocia, caesarean section, and neonatal hypoglycaemia. 3 4 Moreover, long term sequelae of gestational diabetes mellitus are type 2 diabetes in mothers and obesity in their offspring. 5 6 Early diagnosis and treatment of gestational diabetes mellitus have been proven to improve pregnancy outcomes. 7 8 Some guidelines propose a population strategy for diagnosing the disorder [9][10][11][12] (that is, an oral glucose tolerance test) in all pregnant women, whereas others opt for a high ri...

Prediction of gestational diabetes mellitus in the Born in Guangzhou Cohort Study, China

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