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

Abstract

Background Pregnancy 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. Methods Data 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. Discussion The 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.

The association between offspring birthweight and future risk of maternal diabetes: A population‐based study

“…The analyses, conclusions, opinions and statements expressed herein are solely those of the authors and do not reflect those of the funding or data sources; no endorsement is intended or should be inferred. This study also received funding from a Foundation Grant from Physicians Services Incorporated (19)(20)(21)(22)(23). LL received support by a Diabetes Investigator Award from Diabetes Canada and receives support as the Director of the University of Toronto Novo Nordisk Network for Healthy Populations.…”

“…The primary outcome was a new diagnosis of diabetes after a minimum of 6 months postpartum to avoid including cases of pre‐existing diabetes, ascertained using a validated algorithm 19 . The validated case definition is based on physician claims or hospital admissions bearing a diagnosis of diabetes.…”

“…The primary outcome was a new diagnosis of diabetes after a minimum of 6 months postpartum to avoid including cases of pre-existing diabetes, ascertained using a validated algorithm. 19 The validated case definition is based on physician claims or hospital admissions bearing a diagnosis of diabetes. Index date was set to 6 months postpartum and women were followed from index date until date of diabetes diagnosis, a subsequent pregnancy, death, or end of study period, whichever came first.…”

Pregnancy as an opportunity to prevent type 2 diabetes mellitus: FIGO Best Practice Advice

“…These risk models are applicable for the general population and can help to identify individuals with undiagnosed conditions or prioritize individuals with higher risk of type 2 diabetes progression to target them for lifestyle or behavior modification. Such prevention efforts targeting high‐risk individuals are thought to be more cost‐effective than population‐wide intervention efforts, 29 , 30 and may help to reduce subsequent type 2 diabetes progression. While pregnancy provides a unique opportunity for healthcare engagement, risk stratification models specifically targeting postpartum women or women with a history of GDM remain scarce.…”

ENDOCRINOLOGY IN PREGNANCY: Targeting metabolic health promotion to optimise maternal and offspring health

“…Working partnerships among primary care healthcare professionals and holding education events aimed at healthcare providers have been shown to significantly improve screening rates (67). Significant work is in progress to develop prediction models for type 2 diabetes following GDM (68). Such work may allow targeted interventions aimed at prevention, as well as increased frequency of monitoring in those most at risk.…”