Efficacy of Glucocorticoids and Calcineurin Inhibitors for Anti-aminoacyl-tRNA Synthetase Antibody–positive Polymyositis/dermatomyositis–associated Interstitial Lung Disease: A Propensity Score–matched Analysis
Bibliographic record
Abstract
OBJECTIVE: The optimal treatment strategy for anti-aminoacyl-tRNA synthetase antibody-positive polymyositis/dermatomyositis-associated interstitial lung disease (anti-ARS-PM/DM-ILD) is yet to be established. We aimed to evaluate the efficacy of glucocorticoids and calcineurin inhibitors (CNI) in patients with ARS-PM/DM-ILD. METHODS: Progression-free survival (PFS) and overall survival rates were retrospectively evaluated in 32 consecutive patients with ARS-PM/DM-ILD. Disease progression was defined as deterioration in PM/DM-ILD (including recurrence). Predictive factors associated with PFS were analyzed by Cox hazards analysis. The efficacy of first-line prednisolone (PSL) plus CNI therapy was compared with that of PSL monotherapy using propensity score-matched analysis. RESULTS: Overall, 20 (62.5%) and 12 (37.5%) patients received first-line therapy with PSL + CNI and PSL, respectively. The 2-year PFS and 5-year survival rates in the overall cohort were 68.8% and 96.9%, respectively. On multivariate analysis, arterial oxygen pressure (HR 0.86) and PSL monotherapy (vs PSL + CNI; HR 7.29) showed an independent association with PFS. Baseline characteristics of propensity score-matched PSL + CNI and PSL groups were similar. The 2-year PFS rate was significantly higher in the matched PSL + CNI group than in the matched PSL group. All patients who experienced disease progression during first-line therapy were subsequently treated with second-line therapies. The 5-year survival rates of both the matched PSL + CNI and PSL groups were favorable. CONCLUSION: Propensity score-matched analysis demonstrated that first-line PSL + CNI therapy for patients with ARS-PM/DM-ILD significantly improved the PFS compared with PSL monotherapy, although there was no significant difference regarding longterm survival.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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) | 0.001 | 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".