Linda J E Meertens1, Hubertina C J Scheepers2, Sander M J van Kuijk3, Nel Roeleveld4, Robert Aardenburg5, Ivo M A van Dooren6, Josje Langenveld5, Iris M Zwaan7, Marc E A Spaanderman2, Marleen M H J van Gelder4, Luc J M Smits1. 1. Department of Epidemiology, Care and Public Health Research Institute (CAPHRI), Maastricht University, Maastricht, The Netherlands. 2. Department of Obstetrics and Gynecology, School for Oncology and Developmental Biology (GROW), Maastricht University Medical Center, Maastricht, The Netherlands. 3. Department of Clinical Epidemiology and Medical Technology Assessment (KEMTA), Maastricht University Medical Center, Maastricht, The Netherlands. 4. Department for Health Evidence, Radboud Institute for Health Sciences, Radboud University Medical Center, Nijmegen, The Netherlands. 5. Department of Obstetrics and Gynecology, Zuyderland Medical Center, Heerlen, The Netherlands. 6. Department of Obstetrics and Gynecology, Sint Jans Gasthuis Weert, Weert, The Netherlands. 7. Department of Obstetrics and Gynecology, Laurentius Hospital, Roermond, The Netherlands.
Abstract
INTRODUCTION: We performed an independent validation study of all published first trimester prediction models, containing non-invasive predictors, for the risk of gestational diabetes mellitus. Furthermore, the clinical potential of the best performing models was evaluated. MATERIAL AND METHODS: Systemically selected prediction models from the literature were validated in a Dutch prospective cohort using data from Expect Study I and PRIDE Study. The predictive performance of the models was evaluated by discrimination and calibration. Clinical utility was assessed using decision curve analysis. Screening performance measures were calculated at different risk thresholds for the best model and compared with current selective screening strategies. RESULTS: The validation cohort included 5260 women. Gestational diabetes mellitus was diagnosed in 127 women (2.4%). The discriminative performance of the 12 included models ranged from 68% to 75%. Nearly all models overestimated the risk. After recalibration, agreement between the observed outcomes and predicted probabilities improved for most models. CONCLUSIONS: The best performing prediction models showed acceptable performance measures and may enable more personalized medicine-based antenatal care for women at risk of developing gestational diabetes mellitus compared with current applied strategies.
INTRODUCTION: We performed an independent validation study of all published first trimester prediction models, containing non-invasive predictors, for the risk of gestational diabetes mellitus. Furthermore, the clinical potential of the best performing models was evaluated. MATERIAL AND METHODS: Systemically selected prediction models from the literature were validated in a Dutch prospective cohort using data from Expect Study I and PRIDE Study. The predictive performance of the models was evaluated by discrimination and calibration. Clinical utility was assessed using decision curve analysis. Screening performance measures were calculated at different risk thresholds for the best model and compared with current selective screening strategies. RESULTS: The validation cohort included 5260 women. Gestational diabetes mellitus was diagnosed in 127 women (2.4%). The discriminative performance of the 12 included models ranged from 68% to 75%. Nearly all models overestimated the risk. After recalibration, agreement between the observed outcomes and predicted probabilities improved for most models. CONCLUSIONS: The best performing prediction models showed acceptable performance measures and may enable more personalized medicine-based antenatal care for women at risk of developing gestational diabetes mellitus compared with current applied strategies.
Authors: Grammata Kotzaeridi; Julia Blätter; Daniel Eppel; Ingo Rosicky; Martina Mittlböck; Gülen Yerlikaya-Schatten; Christian Schatten; Peter Husslein; Wolfgang Eppel; Evelyn A Huhn; Andrea Tura; Christian S Göbl Journal: Eur J Clin Invest Date: 2021-06-18 Impact factor: 5.722