Interpretation
We evaluated a range of potential cut-points from our predictive model
that could be used to prioritize groups of women to target for different
interventions. For example, the Diabetes Prevention Program demonstrated
that lifestyle modification in women with a history of GDM reduces the
risk of type 2 diabetes by 50%, but is costly to implement at
$9,000/year.35 For our model, a cut-point of 0.24
would identify 56% of women for additional intervention and had
reasonable sensitivity (80%) and low specificity (58%), suggesting it
could be a useful cut-point to identify a high risk subgroup of women
for the most intensive and costly postpartum lifestyle modification
interventions. Conversely, a cut-point of 0.13 would identify 76% of
the population for further intervention, had higher sensitivity (96%)
and lower specificity (35%) and may be more appropriate for low-cost
interventions, such as metformin or other pharmacological interventions.
Future cost-effectiveness analyses are required to investigate the
implications of offering interventions to women with GDM based on
different cut-points from the proposed model.
Our results indicate a clinical prediction model may be useful around
the time of delivery to identify women with recent GDM at high risk for
impaired glucose tolerance. However, a larger study with longer
follow-up is needed to assess the model’s ability to predict type 2
diabetes. In addition, future work should explore whether covariates
such as socioeconomic status, healthcare access, and diet help to
predict type 2 diabetes risk.