Abstract
Introduction and Objective: We asked if a binary endpoint for change (∆) from baseline to a fixed timepoint of 1 year could be useful in future trials. Methods: We used 2hr-OGTT data from the negative abatacept prevention trial and the positive teplizumab prevention trial, and from participants in the observational TrialNet Pathway to Prevention Study (PTP) with similar characteristics. Glucose and C-peptide response curves were plotted and vectors for curve movement from baseline to 1 year were used to categorize simultaneous glucose ∆ and C-peptide ∆ as metabolic treatment failure vs. success. Results: PTP participants with ∆glucose>0 and ∆C-peptide<0 from baseline to 1 year were at substantially higher risk for stage 3 T1D than those with ∆glucose<0 and ∆C-peptide>0 (p<0.0001). Based on this, we compared placebo vs. treatment groups in both trials for failure (∆glucose>0 with ∆C-peptide<0) vs. success (∆glucose<0 with ∆C-peptide>0) after 1 year. In the table, the failure vs. success endpoint at 1 year revealed more treatment efficacy than the original endpoints used for each trial, which required 8.0 years to implement for abatacept and 10.5 years to implement for teplizumab. Conclusion: An analytic approach using a binary metabolic endpoint of failure vs. success at a fixed time interval appears to detect treatment effects at least as well as standard primary endpoints with shorter follow-up.