Trial reportDiabetes2025
Novel Approach for Assessing Outcomes of Type 1 Diabetes Prevention Trials Over a Fixed Time Interval.
Trial report in Diabetes, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
14 authors.
Funding
Abstract
We evaluated whether a binary metabolic end point for change (Δ) from baseline to 1-year postrandomization could be useful in type 1 diabetes (T1D) prevention trials. Using 2-h oral glucose tolerance testing data from the stage 1 participants in the recent abatacept prevention trial and similar participants in the observational TrialNet Pathway to Prevention (PTP) study, we assessed Δmetabolic measures, plotted glucose and C-peptide response curves, and categorized vectors for Δ from baseline to 1 year as metabolic treatment failure versus success. Analyses were validated using the teplizumab prevention study. PTP participants with Δglucose >0 and ΔC-peptide <0 from baseline to 1 year were at substantially higher risk for stage 3 T1D than those with Δglucose <0 and ΔC-peptide >0 (P < 0.0001). Based on this, we compared placebo versus treatment groups in both trials for failure (Δglucose >0 with ΔC-peptide <0) versus success (Δglucose <0 with ΔC-peptide >0) after 1 year. Using this end point, a favorable metabolic impact of abatacept was found after 12 months of treatment. An analytic approach using a binary metabolic end point of failure versus success at a fixed time interval appears to detect treatment effects at least as well as standard primary end points with shorter follow-up. ARTICLE HIGHLIGHTS: Challenges in time to event type 1 diabetes (T1D) prevention trial design can yield negative results even for treatments that may actually improve disease pathology. We evaluated whether a binary metabolic end point for 12-month change from baseline to 1 year postrandomization could be useful in T1D prevention trials. This approach detected treatment effects at least as well as standard primary end points with shorter follow-up. Fixed interval metabolic end points should be used in combination with traditional T1D end points to better understand treatment effects of preventive agents.
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What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.