Immunosuppressive therapy in patients with connective tissue disease‐associated pulmonary arterial hypertension: A systematic review
Bibliographic record
Abstract
OBJECTIVES: It is currently accepted that inflammation plays an important role in the pathogenesis of connective tissue disease-associated pulmonary arterial hypertension (CTD-PAH). However, the efficacy of immunosuppressive therapy remains anecdotal. The objective of this systematic review was to evaluate the efficacy of immunosuppressive therapy in patients with CTD-PAH and to further assess whether response differs between CTD subtypes and clinical features. METHODS: We systematically searched studies reporting the treatment response of immunosuppressants and biological agents in CTD-PAH from PUBMED, EMBASE, the Cochrane Library, and Scopus. Studies had to report treatment regime and response criteria. The risk of bias was assessed using the Newcastle-Ottawa scale. RESULTS: Seven independent cohorts, 1 trial, and 1 case-series encompassing 439 patients with CTD-PAH were included. Patients were divided into 2 groups according to the therapeutic regimen. There were 146 patients in the immunosuppressants group with better heart function at baseline and 52.1% (76/146) of them were responders. There were 236 patients treated with immunosuppressants combined with PAH-specific therapy who showed more severity at baseline and 41.1% (97/236) of them were responders. Among different CTD subtypes, patients with systemic lupus erythematosus-associated PAH (SLE-PAH) showed a better response to immunosuppressants (response rate 48.1%). What is more, 1 randomized controlled trial showed the potential therapeutic value of rituximab (n = 57) in CTD-PAH patients. CONCLUSIONS: Current studies support the use of immunosuppressive therapy in CTD-PAH, especially in SLE-PAH. Further studies on biological agents and the therapeutic effect of different immunosuppressants are still 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 | 0.003 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.006 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".