Discriminant Capacity of Clinical Efficacy and Nonsteroidal Antiinflammatory Drug-sparing Endpoints, Alone or in Combination, in Axial Spondyloarthritis
Bibliographic record
Abstract
OBJECTIVE: Using data from a randomized, double-blind, placebo-controlled study, we assessed the capacity of clinical and nonsteroidal antiinflammatory drug (NSAID)-sparing endpoints, alone and in combination, to discriminate between treatment effects in axial spondyloarthritis (axSpA). METHODS: Patients with active NSAID-resistant axSpA received etanercept (ETN) 50 mg/week or placebo for 8 weeks and tapered/discontinued NSAID. In posthoc logistic regression analyses, OR were calculated that indicated the capacity of the following endpoints to discriminate between the effects of ETN and placebo at Week 8: Bath Ankylosing Spondylitis Disease Activity Index (BASDAI) 50; BASDAI ≤ 3; Assessment of Spondyloarthritis international Society (ASAS) 20; ASAS40; Ankylosing Spondylitis Disease Activity Score (ASDAS) with C-reactive protein (CRP) < 1.3 and ASDAS-CRP < 2.1; ≥ 50% decrease from baseline in ASAS-NSAID score, score < 10, and score = 0; and each clinical and/or each NSAID measure. RESULTS: In 90 randomized patients (ETN, n = 42; placebo, n = 48), disease activity was similar between groups at baseline: mean (± SD) BASDAI (ETN vs placebo) 6.0 ± 1.6 versus 5.9 ± 1.5. NSAID intake was high: ASAS-NSAID score 98.2 ± 39.0 versus 93.0 ± 23.4. OR ranged from 1.6 (95% CI 0.5-5.4) for ASDAS-CRP < 1.3 to 5.8 (95% CI 1.2-29.1) for BASDAI50 and NSAID score of 0; most measures (34/45) reached statistical significance (α = 0.05) favoring ETN. Most combined outcome variables using OR were more discriminant than single outcome measures. CONCLUSION: These findings suggest that changes in NSAID intake during treatment do not prevent demonstration of clinically relevant effects of biologic treatment, and combined (i.e., clinical with NSAID-sparing) endpoints were frequently more discriminant than single (i.e., clinical) endpoints. ClinicalTrials.gov (NCT01298531).
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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 | 0.012 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".