Immunotherapeutic agents in type 1 diabetes: a systematic review and meta‐analysis of randomized trials
Bibliographic record
Abstract
OBJECTIVE: Although recent trial results of anti-CD3 therapy are promising, there have been conflicting results of various immunotherapeutic agents used in patients with type 1 diabetes. We conducted a systematic review and meta-analysis to determine the efficacy of nonantigen-based immunotherapeutic approaches for preservation of beta-cell function in patients with type 1 diabetes. METHODS: We searched MEDLINE, EMBASE, Cochrane CENTRAL, reference lists, and content expert files up to September 2006. Eligible studies were randomized controlled trials (RCTs) of antiproliferative agents (methotrexate, azathioprine), monoclonal antibodies (CD3, CD4), T-cell inhibitors (cyclosporin) and other immunotherapeutic agents (photopheresis, linomide, fusidin, buffy coat, intravenous immunoglobulin, BCG, nicotinamide) in patients with newly diagnosed type 1 diabetes followed for > or = 6 months. Pairs of reviewers working independently and with adequate reliability assessed the trials' methodological quality, collected data, and conducted random-effects meta-analyses on measures of preservation of beta-cell function (e.g. C-peptide secretion, insulin independence). RESULTS: Of the 299 potentially relevant articles identified after an initial search, 20 trials met selection criteria. Meta-analysis of 20 trials (n = 1187 patients) found a small to moderate improvement in beta-cell function with immunotherapy [vs. placebo, effect size 0.37, 95% confidence interval (CI) 0.14-0.6] but there was moderate inconsistency in results across trials (I(2) 65%, 95% CI 39-77%). Subgroup analysis suggested a greater effect of cyclosporin and antiproliferative agents on beta-cell function when used for > or = 6 months (pooled effect size 0.77 vs. -0.11, respectively; P(interaction) = 0.002). CONCLUSIONS: Long-term immunotherapy may preserve beta-cell function in newly diagnosed patients with type 1 diabetes. Patients and clinicians must await the conduct of rigorous trials reporting on diabetes resolution, adverse events, and other patient-important outcomes.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.020 | 0.047 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.024 | 0.033 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".