Real-world experience with selexipag in patients with pulmonary arterial hypertension in North America and Europe
Bibliographic record
Abstract
Real-world data contribute to understanding the treatment landscape of rare diseases such as pulmonary arterial hypertension (PAH). SPHERE ( NCT03278002 ; US; completed) and EXPOSURE (EUPAS19085; Europe and Canada; ongoing, data cut-off Nov 2021) are two large, prospective, multicentre observational studies on PAH. The aim of this pooled analysis was to describe real-world experience with selexipag, a selective oral prostacyclin receptor agonist. Overall, 894 patients had newly initiated selexipag. Median (Q1, Q3) age was 61 (48, 70) years and time since diagnosis was 2.7 (0.8, 7.4) years. Most patients were female (74%) with idiopathic PAH (54%) and initiated selexipag as triple oral therapy (67%). Median (Q1, Q3) selexipag exposure was 10.8 (3.3, 18.6) months. Following titration, 41% (307/742) of patients discontinued selexipag, with 150 (20%) discontinuations due to tolerability and 46 (6%) due to death. Overall, 8% (70/894) of patients died. A total of 591 patients had 1-year mortality risk score (2022 ESC/ERS 4-strata risk assessment) available at selexipag initiation. The 1-year Kaplan-Meier (KM) survival estimates were 100% for low-risk patients, 96% for intermediate-low, 91% for intermediate-high, and 59% for high-risk (Figure 1). In North American and European clinical practices, patients initiated selexipag across all risk strata, with an overall 1-year KM survival estimate of 93%. erj;64/suppl_68/PA4319/F1 F1 F1
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".