Dataset Information

A clinical diabetes risk prediction model for prediabetic women with prior gestational diabetes.

ABSTRACT:

Introduction

Without treatment, prediabetic women with a history of gestational diabetes mellitus (GDM) are at greater risk for developing type 2 diabetes compared with women without a history of GDM. Both intensive lifestyle intervention and metformin can reduce risk. To predict risk and treatment response, we developed a risk prediction model specifically for women with prior GDM.

Methods

The Diabetes Prevention Program was a randomized controlled trial to evaluate the effectiveness of intensive lifestyle intervention, metformin (850mg twice daily), and placebo in preventing diabetes. Data from the Diabetes Prevention Program (DPP) was used to conduct a secondary analysis to evaluate 11 baseline clinical variables of 317 women with prediabetes and a self-reported history of GDM to develop a 3-year diabetes risk prediction model using Cox proportional hazards regression. Reduced models were explored and compared with the main model.

Results

Within three years, 82 (25.9%) women developed diabetes. In our parsimonious model using 4 of 11 clinical variables, higher fasting glucose and hemoglobin A1C were each associated with greater risk for diabetes (each hazard ratio approximately 1.4), and there was an interaction between treatment arm and BMI suggesting that metformin was more effective relative to no treatment for BMI ≥ 35kg/m2 than BMI < 30kg/m2. The model had fair discrimination (bias corrected C index = 0.68) and was not significantly different from our main model using 11 clinical variables. The estimated incidence of diabetes without treatment was 37.4%, compared to 20.0% with intensive lifestyle intervention or metformin treatment for women with a prior GDM.

Conclusions

A clinical prediction model was developed for individualized decision making for prediabetes treatment in women with prior GDM.

SUBMITTER: Man B

PROVIDER: S-EPMC8232404 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:Implementation of dietary and lifestyle interventions prior to and early in pregnancy in high risk women has been shown to reduce the risk of gestational diabetes mellitus (GDM) development later in pregnancy. Although numerous risk factors for GDM have been identified, the ability to accurately identify women before or early in pregnancy who could benefit most from these interventions remains limited. As nulliparous women are an under-screened population with risk profiles that differ from their multiparous counterparts, development of a prediction model tailored to nulliparous women may facilitate timely preventive intervention and improve maternal and infant outcomes. We aimed to develop and validate a model for preconception and early pregnancy prediction of gestational diabetes mellitus based on clinical risk factors for nulliparous women. A risk prediction model was built within a large California birth cohort including singleton live birth records from 2007-2012. Model accuracy was assessed both internally and externally, within a cohort of women who delivered at University of Iowa Hospitals and Clinics between 2009-2017, using discrimination and calibration. Differences in predictive accuracy of the model were assessed within specific racial/ethnic groups. The prediction model included five risk factors: race/ethnicity, age at delivery, pre-pregnancy body mass index, family history of diabetes, and pre-existing hypertension. The area under the curve (AUC) for the California internal validation cohort was 0.732 (95% confidence interval (CI) 0.728, 0.735), and 0.710 (95% CI 0.672, 0.749) for the Iowa external validation cohort. The model performed particularly well in Hispanic (AUC 0.739) and Black women (AUC 0.719). Our findings suggest that estimation of a woman's risk for GDM through model-based incorporation of risk factors accurately identifies those at high risk (i.e., predicted risk >6%) who could benefit from preventive intervention encouraging prompt incorporation of this tool into preconception and prenatal care.

Project description:AimsWomen with prior gestational diabetes mellitus (GDM) or high genetic susceptibility are prone to development of type 2 diabetes. We examined whether a lifestyle intervention modified the genetic effect on changes in glycemic markers among women with prior GDM.Research design and methodsThis study included 560 women with prior GDM from a randomized controlled trial, the Tianjin Gestational Diabetes Mellitus Prevention Program, who were assigned into an intervention arm (improved physical activity and healthy dietary intakes) or a control arm. We assessed associations of GDM related genetic variants in/near the CDKAL1 (rs7754840) and MTNR1B (rs10830962) genes with changes in fasting levels of glucose and insulin, β-cell function (HOMA-B) and insulin resistance (HOMA-IR) at 1 year and 2 years after the baseline.ResultsWe found significant interactions between CDKAL1 variant rs7754840 and lifestyle intervention on changes in fasting insulin and HOMA-IR at 1 year (P for interactions = 0.008 and 0.006, respectively). The GDM-increasing C allele was associated with a 0.07-unit greater increase in fasting insulin (P = 0.048) and HOMA-IR (P = 0.045) in the control group, while opposite-directional associations were observed in the intervention group; women with the C allele seemed to decrease more in these glycemic markers than the non-C-carriers (both P ≤ 0.06). The interactions between the CDKAL1 genetic variant and lifestyle intervention on changes in fasting insulin (P = 0.035) and HOMA-IR (P = 0.024) remained significant over the 2-year period, even though the effects of lifestyle intervention were attenuated at 2-year. The MTNR1B variant rs10830962 did not show interaction with lifestyle intervention on changes in the glycemic markers.ConclusionsHealthy lifestyle intervention may be beneficial for women with the GDM predisposing CDKAL1 genetic variant in improvement of insulin resistance.Trial registration numberClinicalTrials.gov NCT01554358. URL OF REGISTRATION: https://clinicaltrials.gov/ct2/show/NCT01554358.

Project description:ObjectivesTo evaluate the influence of genetic variants and clinical characteristics on the risk of gestational diabetes mellitus (GDM) and to construct and verify a prediction model of GDM in early pregnancy.MethodsFour hundred seventy five women with GDM and 487 women without, as a control, were included to construct the prediction model of GDM in early pregnancy. Both groups had complete genotyping results and clinical data. They were randomly divided into a trial cohort (70%) and a test cohort (30%). Then, the model validation cohort, including 985 pregnant women, was used for the external validation of the GDM early pregnancy prediction model.ResultsWe found maternal age, gravidity, parity, BMI and family history of diabetes were significantly associated with GDM (OR > 1; P < 0.001), and assisted reproduction was a critical risk factor for GDM (OR = 1.553, P = 0.055). MTNR1B rs10830963, C2CD4A/B rs1436953 and rs7172432, CMIP rs16955379 were significantly correlated with the incidence of GDM (AOR > 1, P < 0.05). Therefore, these four genetic susceptible single nucleotide polymorphisms (SNPs) and six clinical characteristics were included in the construction of the GDM early pregnancy prediction model. In the trial cohort, a predictive model of GDM in early pregnancy was constructed, in which genetic risk score was independently associated with GDM (AOR = 2.061, P < 0.001) and was the most effective predictor with the exception of family history of diabetes. The ROC-AUC of the prediction model was 0.727 (95% CI 0.690-0.765), and the sensitivity and specificity were 69.9% and 64.0%, respectively. The predictive power was also verified in the test cohort and the validation cohort.ConclusionsBased on the genetic variants and clinical characteristics, this study developed and verified the early pregnancy prediction model of GDM. This model can help screen out the population at high-risk for GDM in early pregnancy, and lifestyle interventions can be performed for them in a timely manner in early pregnancy.