Repository Corticotropin Injection for the Treatment of Pulmonary Sarcoidosis: A Narrative Review
Bibliographic record
Abstract
Although corticosteroids are the standard first-line therapy for pulmonary sarcoidosis, long-term and high-dose use of these drugs are associated with increased risk of adverse events and high healthcare utilization costs. Treatment guidelines for pulmonary sarcoidosis indicate that off-label immunomodulators and biologics may be warranted for severe disease. Repository corticotropin injection (RCI, Acthar ® Gel), a complex mixture of adrenocorticotropic hormone analogs and other pituitary peptides, is one of only two therapies approved by the US Food and Drug Administration for symptomatic pulmonary sarcoidosis and is recommended by current European Respiratory Society treatment guidelines for use on a case-by-case basis. With its unique anti-inflammatory and immunomodulatory mechanism of action through activation of melanocortin receptors in various cell types, RCI has demonstrated steroid-sparing properties. RCI has a long history of use in autoimmune and inflammatory disorders, with proven safety and efficacy for pulmonary sarcoidosis. In this narrative review, we present the clinical evidence for the safety and efficacy of RCI in the treatment of pulmonary sarcoidosis, identify where RCI falls within the current treatment guidelines, and describe the unique mechanism of action of RCI for promoting anti-inflammatory and immunomodulatory effects.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".