Open AccessExternal validation and clinical utility of prognostic prediction models for gestational diabetes mellitus: A prospective cohort study
Author(s) -
Meertens Linda J. E.,
Scheepers Hubertina C. J.,
Kuijk Sander M. J.,
Roeleveld Nel,
Aardenburg Robert,
Dooren Ivo M. A.,
Langenveld Josje,
Zwaan Iris M.,
Spaanderman Marc E. A.,
Gelder Marleen M. H. J.,
Smits Luc J. M.
Publication year - 2020
Publication title -
acta obstetricia et gynecologica scandinavica
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.401
H-Index - 102
eISSN - 1600-0412
pISSN - 0001-6349
DOI - 10.1111/aogs.13811
Subject(s) - medicine , gestational diabetes , prospective cohort study , predictive modelling , cohort , cohort study , diabetes mellitus , risk assessment , obstetrics , pregnancy , gestation , machine learning , endocrinology , computer science , genetics , computer security , biology
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.