Effect of macitentan on morbidity and mortality in pulmonary arterial hypertension: A randomised controlled trial (SERAPHIN)
Bibliographic record
Abstract
The effect of macitentan, a novel dual endothelin receptor antagonist, on morbidity and mortality was assessed in patients with pulmonary arterial hypertension (PAH). In this double-blind, placebo-controlled, Phase III, event-driven study (SERAPHIN; NCT00660179 ), 742 PAH patients (≥12 years) were randomised to placebo (n=250), macitentan 3mg (n=250) or 10mg (n=242) once daily. 64% received PAH-specific drugs at baseline. Mean treatment duration was 85.3, 99.5 and 103.9 weeks, respectively. The primary endpoint was time from treatment initiation to first morbidity or mortality event (death, atrial septostomy, lung transplantation, initiation of i.v./s.c. prostanoids or PAH worsening – blindly and independently adjudicated). Macitentan reduced the risk of such an event vs placebo by 30% (97.5%CI: 4–48%; P=0.0108) in the 3mg group and 45% (97.5%CI: 24–61%; P<0.0001) in the 10mg group. This effect was established early, sustained over the entire study duration and, for the 10mg dose, was preserved across WHO functional class (FC), as well as in combination with other PAH-specific drugs. Macitentan 3mg and 10mg reduced the risk of PAH-related death or hospitalisation (a composite secondary endpoint) by 33% (97.5%CI: 3–54%; P=0.0146) and 50% (97.5%CI: 25–67%; P<0.0001). Macitentan was well tolerated; incidences of elevated liver aminotransferases and peripheral oedema were similar across groups. Headache, nasopharyngitis and anaemia occurred more frequently with macitentan than placebo. In conclusion, macitentan significantly reduced morbidity and mortality in patients with PAH, with a favourable safety profile.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".