Treatment of interstitial lung disease in systemic sclerosis: guidelines and new clinical trial results
Bibliographic record
Abstract
PURPOSE OF REVIEW: Interstitial lung disease (ILD) is the leading cause of death in patients with systemic sclerosis-associated interstitial lung disease (SSc-ILD). The American College of Rheumatology (ACR), in conjunction with the American College of Chest Physicians (CHEST), recently published clinical practice guidelines for the treatment of adults with systemic autoimmune rheumatic disease-associated ILD, including SSc-ILD. Herein, we summarize evidence from randomized trials evaluating the safety and efficacy of pharmacologic therapies for the treatment of SSc-ILD. RECENT FINDINGS: In this review, we present findings from recent randomized controlled trials in SSc-ILD. The pharmacologic therapies discussed include immunosuppressive medications (mycophenolate, cyclophosphamide, rituximab, and tocilizumab) and antifibrotic medications (nintedanib and pirfenidone). SUMMARY: Randomized trials provide an evidence base for the SSc-ILD treatment recommendations put forth in the ACR/CHEST Guidelines for the treatment of ILD in people with systemic autoimmune rheumatic diseases. These guidelines will help inform clinical practice and highlight areas in which further research is needed.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".