Diabetes after pregnancy: a study protocol for the derivation and validation of a risk prediction model for 5-year risk of diabetes following pregnancy

Diagnostic and Prognostic Research

Karen Fleming¹  Howard Berger²  Padma Kaul³  Laura C. Rosella⁴  Denice S. Feig⁵  Baiju R. Shah⁶  Joel G. Ray⁷  Lorraine L. Lipscombe⁸  Stephanie H. Read⁹ 

[1] Department of Family and Community Medicine, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada;Division of Maternal-Fetal Medicine, St. Michael’s Hospital, Toronto, Ontario, Canada;Faculty of Medicine and Dentistry, University of Alberta, Edmonton, Alberta, Canada;Canadian VIGOUR Centre, University of Alberta, Edmonton, Alberta, Canada;Institute for Clinical Evaluative Sciences, Toronto, Ontario, Canada;Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada;Public Health Ontario, Toronto, Ontario, Canada;Institute for Clinical Evaluative Sciences, Toronto, Ontario, Canada;Department of Medicine, University of Toronto, Toronto, Ontario, Canada;Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Ontario, Canada;Sinai Health System, Toronto, Ontario, Canada;Institute for Clinical Evaluative Sciences, Toronto, Ontario, Canada;Division of Maternal-Fetal Medicine, St. Michael’s Hospital, Toronto, Ontario, Canada;Department of Medicine, University of Toronto, Toronto, Ontario, Canada;Department of Medicine, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada;Institute for Clinical Evaluative Sciences, Toronto, Ontario, Canada;Public Health Ontario, Toronto, Ontario, Canada;Department of Medicine, University of Toronto, Toronto, Ontario, Canada;Department of Obstetrics and Gynaecology, St. Michael’s Hospital, Toronto, Ontario, Canada;Women’s College Research Institute, Women’s College Hospital, 76 Grenville Street, M5S 1B2, Toronto, Ontario, Canada;Institute for Clinical Evaluative Sciences, Toronto, Ontario, Canada;Department of Medicine, University of Toronto, Toronto, Ontario, Canada;Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Ontario, Canada;Women’s College Research Institute, Women’s College Hospital, 76 Grenville Street, M5S 1B2, Toronto, Ontario, Canada;Institute for Clinical Evaluative Sciences, Toronto, Ontario, Canada;Evidence and Access, Certara, London, UK;

关键词: Pregnancy;    Type 2 diabetes mellitus;    Prognosis;    Prediction model;    Risk;    Study protocol;   

DOI  :  10.1186/s41512-021-00095-6

来源: Springer

【 摘 要 】

BackgroundPregnancy offers a unique opportunity to identify women at higher future risk of type 2 diabetes mellitus (DM). In pregnancy, a woman has greater engagement with the healthcare system, and certain conditions are more apt to manifest, such as gestational DM (GDM) that are important markers for future DM risk. This study protocol describes the development and validation of a risk prediction model (RPM) for estimating a woman’s 5-year risk of developing type 2 DM after pregnancy.MethodsData will be obtained from existing Ontario population-based administrative datasets. The derivation cohort will consist of all women who gave birth in Ontario, Canada between April 2006 and March 2014. Pre-specified predictors will include socio-demographic factors (age at delivery, ethnicity), maternal clinical factors (e.g., body mass index), pregnancy-related events (gestational DM, hypertensive disorders of pregnancy), and newborn factors (birthweight percentile). Incident type 2 DM will be identified by linkage to the Ontario Diabetes Database. Weibull accelerated failure time models will be developed to predict 5-year risk of type 2 DM. Measures of predictive accuracy (Nagelkerke’s R2), discrimination (C-statistics), and calibration plots will be generated. Internal validation will be conducted using a bootstrapping approach in 500 samples with replacement, and an optimism-corrected C-statistic will be calculated. External validation of the RPM will be conducted by applying the model in a large population-based pregnancy cohort in Alberta, and estimating the above measures of model performance. The model will be re-calibrated by adjusting baseline hazards and coefficients where appropriate.DiscussionThe derived RPM may help identify women at high risk of developing DM in a 5-year period after pregnancy, thus facilitate lifestyle changes for women at higher risk, as well as more frequent screening for type 2 DM after pregnancy.

【 授权许可】

CC BY