Pooled analysis of TNF inhibitor biosimilar studies comparing radiographic progression by disease activity states in rheumatoid arthritis
Bibliographic record
Abstract
OBJECTIVE: To evaluate the relationship between disease activity and radiographic progression in rheumatoid arthritis, three phase III studies of SB4, SB2 and SB5 (biosimilars of etanercept, infliximab and adalimumab) were pooled to assess radiographic progression by disease activity status. METHODS: Patients from each study with radiographic data were pooled and grouped based on disease activity state (remission, low disease activity (LDA), moderate disease activity (MDA) and high disease activity (HDA)), determined by disease activity score based on 28-joint count (DAS28) per erythrocyte sedimentation rate, Simplified Disease Activity Index (SDAI) and Clinical Disease Activity Index (CDAI) at different time points. Mean change in modified Total Sharp Score (mTSS) and the proportion of radiographic non-progressors of higher disease activity groups (LDA, MDA and HDA) in reference to remission were summarised descriptively, with comparison of ORs using logistic models. RESULTS: 1265 patients were included. In all treatments combined, the 1 year mean change in mTSS was 0.03, 0.4, 0.3 and 1.3 and proportion of radiographic non-progressors was 79.8%, 78.1%, 74.1% and 58.4% in the week 24/30 DAS28-determined remission, LDA, MDA and HDA groups, respectively. ORs (95% CIs) of the proportion of non-progressors were lowest in the HDA group in reference to remission (0.35 (0.23 to 0.54)), followed by MDA (0.72 (0.50 to 1.05)) and LDA (0.90 (0.55 to 1.48)) groups. Similar trends were observed when disease activity was assessed using SDAI or CDAI. CONCLUSION: A pooled analysis of radiographic assessment data from three biosimilar studies showed that radiographic progression is small overall but increases with worse disease activity. TRIAL REGISTRATION NUMBERS: NCT01895309, NCT01936181 and NCT02167139.
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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 | 0.042 | 0.060 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.018 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".