Analysis of Relapse Events in the DECIDE Study Using a Novel Weighted Hurdle Model (P2.111)
Bibliographic record
Abstract
Objective: To utilize a novel weighted hurdle model to evaluate the effect of daclizumab HYP versus intramuscular interferon beta-1a in patients who experienced ≥1 relapse in DECIDE. Background: Traditional statistical approaches for analyzing the efficacy of disease-modifying therapies on relapses in relapsing-remitting multiple sclerosis (RRMS) compare overall relapse rates, but provide little information on whether patients still having relapses despite treatment might still be benefitting. DECIDE was a phase 3 study of daclizumab HYP 150 mg subcutaneous every 4 weeks (n=919) versus interferon beta-1a 30 mcg intramuscular once weekly (n=922) for 96-144 weeks in RRMS; annualized relapse rate (primary endpoint) was 0.22 with daclizumab HYP versus 0.39 with intramuscular interferon beta-1a (rate ratio: 0.55 [95[percnt] confidence interval (CI): 0.47-0.65], P<0.0001; 45[percnt] reduction). Methods: Post hoc analysis using a weighted hurdle model adjusting for baseline covariates; this analysis accounts for patients with no relapses and variation in individual follow-up time, and simultaneously evaluates odds of relapse (binary outcome, yes/no) and relapse rate ratio in patients with ≥1 relapse. Results: During DECIDE, more patients were relapse free with daclizumab HYP (72[percnt]) than intramuscular interferon beta-1a (57[percnt]). Fewer daclizumab HYP- than intramuscular interferon beta-1a-treated patients experienced one (19[percnt]; 25[percnt]); two (6[percnt]; 12[percnt]); or ≥3 (4[percnt]; 6[percnt]) relapses, respectively. In the hurdle analysis, odds ratio for relapse for daclizumab HYP versus intramuscular interferon beta-1a was 0.51 (95[percnt] CI: 0.39-0.67, P<0.0001; ie, 49[percnt] reduction with daclizumab HYP); conditional on experiencing ≥1 relapse, relapse rate ratio was 0.77 (95[percnt] CI: 0.62-0.96, P=0.0202; ie, 23[percnt] reduction in relapse rate with daclizumab HYP in those experiencing ≥1 relapse). Conclusions: This novel analysis demonstrated that, in addition to reducing relapses overall versus intramuscular interferon beta-1a, daclizumab HYP reduced the risk of further relapse(s) even in patients continuing to relapse despite treatment. Study Supported by: Biogen and AbbVie Biotherapeutics Inc.
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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 | 0.047 | 0.047 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.009 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| 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".