Table 2

Summary of GEE logistic regression results for prediction of C-peptide detection

CoefficientOR95% CIP
Duration0.697(0.59, 0.82)<0.0001
Onset age1.070(1.01, 1.14)0.033
GRS1.180(0.87, 1.62)0.294
Duration * GRS0.895(0.84, 0.96)<0.001
  • The effects of type 1 diabetes duration, age at onset, GRS, and their interactions on detectable C-peptide were modeled using GEE with assumption of binomial variance and logit link. GEE models were used to account for the mixed cohort of both cross-sectional and longitudinal samples. Type 1 diabetes duration and onset age were found to be significantly predictive of C-peptide detection at the mean GRS (OR 0.697, P < 0.0001, and OR 1.070, P < 0.033, respectively). GRS was not found to be a direct significant predictor of C-peptide detection with duration = 0 (P = 0.294). An interaction effect between disease duration and GRS (Duration * GRS) was found to be significantly predictive of C-peptide detection (OR 0.895, P < 0.001). OR with 95% CI and corresponding P values are reported for disease duration, GRS, and the interaction effect between duration and GRS. Sex was not a significant predictor of C-peptide detection (P = 0.443) and was not included in the model.