Late-breaking abstract: Riociguat for the treatment of pulmonary arterial hypertension (PAH): 2-year results from the PATENT-2 long-term extension
Bibliographic record
Abstract
In the 12-wk PATENT-1 study, riociguat significantly improved 6MWD and other secondary endpoints in PAH pts. Improvements persisted for a further 1 yr in PATENT-2. We present 2-yr data from PATENT-2, the final analysis before most pts switch to the commercial drug. PAH pts who were treatment-naïve or pretreated with ERAs or prostanoids entered PATENT-2 after completing PATENT-1 without ongoing riociguat-related SAEs. All pts received riociguat adjusted up to 2.5 mg tid. Primary endpoints were safety and tolerability; secondary endpoints included 6MWD and WHO FC. Of 405 pts completing PATENT-1, 396 (98%) entered PATENT-2. At this cut-off (March 2014), 275 (69%) pts were ongoing, 307 (78%) had received ≥2 yrs of treatment and 13 (3%) had switched to the commercial drug. Riociguat was well tolerated; 10% of pts withdrew due to AEs. The most common drug-related AEs were dizziness (10%), headache (8%) and dyspepsia (9%). There were 13 (3%) drug-related SAEs of syncope and 4 (1%) drug-related SAEs of pulmonary bleeding. Mean±SD 6MWD increased from PATENT-1 baseline by +37±52 m in riociguat 2.5 mg–maximum pts vs +12±58 m in placebo pts at the end of PATENT-1 and by +47±85 m at 2 yrs (n=296). At the end of PATENT-1, WHO FC improved/stabilized/worsened in 21/78/2% of riociguat 2.5 mg–maximum pts vs 16/75/9% of placebo pts; proportions were 33/58/9% at 2 yrs (n=306). At 2 yrs, survival was 93% and 17% of former therapy-naïve pts were receiving additional PAH therapy. Analyses of correlation between efficacy endpoints and long-term outcomes will be presented. Riociguat has a good long-term safety profile and shows sustained clinical effect for up to 2 yrs in PAH pts.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".