Use of clinically relevant responder threshold criteria to evaluate the response to treatment in the Phase III PATENT-1 study
Bibliographic record
Abstract
BACKGROUND: In PATENT-1, riociguat significantly improved 6-minute walking distance (6MWD) and a range of secondary end-points in patients with pulmonary arterial hypertension (PAH). We investigated whether riociguat increased the proportion of patients achieving clinically relevant responder thresholds compared with placebo during PATENT-1. METHODS: In PATENT-1, a randomized, double-blind study, treatment-naïve patients or patients on background PAH-targeted therapy with symptomatic PAH received 12 weeks of treatment with placebo, riociguat up to 2.5 mg 3 times daily, or riociguat up to 1.5 mg 3 times daily. Increases in 6MWD ≥40 m, 6MWD ≥380 m, cardiac index ≥2.5 liter/min/m(2), mixed venous oxygen saturation ≥65%, World Health Organization functional class I/II, N-terminal pro-brain natriuretic peptide <1,800 pg/ml, and right atrial pressure <8 mm Hg were chosen as threshold criteria of a positive response. RESULTS: Riociguat increased the proportion of treatment-naïve patients and patients on background PAH-targeted therapy with 6MWD ≥380 m at Week 12 (+21% and +15%, respectively), whereas there was a small reduction in 6MWD in placebo-treated patients for both sub-groups. Riociguat also increased the proportion of treatment-naïve patients and patients on background PAH-targeted therapy achieving World Health Organization functional class I/II (+12% and +19%, respectively) and cardiac index ≥2.5 liter/min/m(2) (+30% and +33%, respectively) at Week 12, whereas there was little change in the respective placebo groups. CONCLUSIONS: Compared with placebo, riociguat increased the proportion of treatment-naïve patients and patients on background PAH-targeted therapy who fulfilled criteria defining a positive response to therapy.
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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 | 0.061 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".