Development of the Sjögren’s Syndrome Responder Index, a data-driven composite endpoint for assessing treatment efficacy
Bibliographic record
Abstract
OBJECTIVES: To determine which outcome measures detected rituximab efficacy in the Tolerance and Efficacy of Rituximab in Sjögren's Disease (TEARS) trial and to create a composite endpoint for future trials in primary SS (pSS). METHODS: Post hoc analysis of the multicentre randomized placebo-controlled double-blind TEARS trial. The results were validated using data from two other randomized controlled trials in pSS, assessing rituximab (single-centre trial in the Netherlands) and infliximab, respectively. RESULTS: Five outcome measures were improved by rituximab in the TEARS trial: patient-assessed visual analogue scale scores for fatigue, oral dryness and ocular dryness, unstimulated whole salivary flow and ESR. We combined these measures into a composite endpoint, the SS Responder Index (SSRI), and we defined an SSRI-30 response as a ≥30% improvement in at least two of five outcome measures. In TEARS, the proportions of patients with an SSRI-30 response in the rituximab and placebo groups at 6, 16 and 24 weeks were 47% vs 21%, 50% vs 7% and 55% vs 20%, respectively (P < 0.01 for all comparisons). SSRI-30 response rates after 12 and 24 weeks in the single-centre rituximab trial were 68% (13/19) vs 40% (4/10) and 74% (14/19) vs 40% (4/10), respectively. No significant differences in SSRI-30 response rates were found between infliximab and placebo at any of the time points in the infliximab trial. CONCLUSION: A core set of outcome measures used in combination suggests that rituximab could be effective and infliximab ineffective in pSS. The SSRI might prove useful as the primary outcome measure for future therapeutic trials in pSS.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".