Pragmaticism of Randomized Controlled Trials of Biologic Treatment With Methotrexate in Rheumatoid Arthritis: A Systematic Review
Bibliographic record
Abstract
OBJECTIVE: Randomized controlled trials (RCTs) exist along a spectrum, from explanatory, designed to evaluate interventions under ideal conditions, to pragmatic, designed to reflect usual care. This study assessed the pragmatism of RCTs of advanced therapeutics in rheumatoid arthritis (RA). METHODS: A systematic review was conducted to identify RA RCTs comparing biologic or targeted synthetic therapy in combination with methotrexate, to placebo or any other disease-modifying antirheumatic drugs (DMARDs). Trials were rated using the Pragmatic Explanatory Continuum Indicator Summary-2 (PRECIS-2) tool in 9 domains, each rated from 1 (very explanatory) to 5 (very pragmatic). Latent class and regression analyses examined the heterogeneity in PRECIS-2 scores and the relationship to trial characteristics. RESULTS: In total, 96 trials were included. Eligibility, follow-up, and flexibility of delivery of the intervention were rated as explanatory, with mean ± SD PRECIS-2 scores of 2.0 ± 0.7, 2.0 ± 1.1, and 2.1 ± 0.7, respectively, reflecting strict inclusion criteria, intensive follow-up, and rigid protocols. Studies were rated as pragmatic in setting (3.6 ± 1.5) because many were international, multicenter trials, and in primary analysis (4.1 ± 1.3), because most used intent-to-treat analyses. In latent class analyses, 2 groups were identified; the majority (74%) were rated as explanatory for most domains assessed. These trials had larger sample sizes, were more likely to be industry-funded, and enrolled patients with higher Disease Activity Score in 28 joints and Health Assessment Questionnaire disability index scores, but were less likely to be at high risk of bias. CONCLUSION: RCTs of biologic DMARD treatment in combination with methotrexate for RA were rated as predominantly explanatory, which may affect the generalizability of trial results to clinical practice.
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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 | 0.356 | 0.660 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.022 | 0.021 |
| Bibliometrics | 0.010 | 0.008 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.009 | 0.008 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".