The relationship between forced vital capacity (FVC), modified Rodnan skin score (mRSS) and long-term patient outcomes in systemic sclerosis (SSc) with interstitial lung disease (ILD): a literature review
Bibliographic record
Abstract
Background: Identifying a strong relationship between short-term clinical trial outcomes and long-term patient/payer relevant outcomes for SSc-ILD could allow faster appraisal of orphan drugs via surrogate outcomes while clinical studies are ongoing. Aim: Investigate if a surrogate relationship exists between FVC or mRSS and long-term overall survival (OS) or health-related quality of life (HRQoL) in patients with SSc-ILD. Method: A targeted literature review (TLR) of Embase, NICE appraisals and bibliography searches investigated evidence of a relationship between FVC or mRSS and long-term OS or HRQoL. Strength of associations assessed using established criteria. A clinical systematic literature review (SLR) of MEDLINE, Embase, CCTR and clinical trial registries using PRISMA guidelines established an evidence base for surrogacy analyses. GSK Studies 219938, 222153. Results: No studies in the TLR (N=10) reported correlation coefficients or coefficients of determination to evaluate the strength of relationships between outcomes. Limited evidence suggested a clinically plausible relationship between FVC and OS in SSc/SSc-ILD (3 studies), and between mRSS and OS in SSc/diffuse cutaneous SSc (2 studies). Available evidence found no relationship between FVC or mRSS and HRQoL. In the SLR, FVC, mRSS and OS were reported in most of the 35 trials identified. Conclusions: De novo surrogacy analyses are warranted to provide more robust evidence for potential relationships between FVC or mRSS and long-term outcomes in SSc-ILD; the SLR suggests this is feasible with existing evidence. Funding: GSK
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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 | 0.008 | 0.038 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.006 |
| Bibliometrics | 0.015 | 0.018 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".