Assessment of the REPLACE study composite endpoint in riociguat‐treated patients in the PATENT study
Bibliographic record
Abstract
The goal of treatment in patients with pulmonary arterial hypertension is to achieve a low risk status, indicating a favorable long‐term outcome. The REPLACE study investigated the efficacy of switching to riociguat in patients with pulmonary arterial hypertension and an insufficient response to phosphodiesterase‐5 inhibitors. In this post hoc analysis, we applied the REPLACE composite endpoint of clinical improvement to the placebo‐controlled PATENT‐1 study of riociguat in pulmonary arterial hypertension and its long‐term extension, PATENT‐2. Clinical improvement was defined as ≥2 of the following in patients who completed the study without clinical worsening: ≥10% or ≥30 m improvement in 6‐minute walking distance; World Health Organization functional class I or II; ≥30% decrease in N‐terminal prohormone of brain natriuretic peptide. At PATENT‐1 Week 12, patients treated with riociguat were more likely to achieve the composite endpoint vs. placebo (P < 0.0001), with similar results in pretreated (P = 0.0189) and treatment‐naïve (P < 0.0001) patients. Achievement of the composite endpoint at Week 12 was associated with a 45% reduction in relative risk of death and a 19% reduction in relative risk of clinical worsening in PATENT‐2. Overall, these data suggest that use of the REPLACE composite endpoint in patients with pulmonary arterial hypertension is a valid assessment of response to treatment.
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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 | 0.008 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".