Abstract 4147141: Relationship Between CVH and Survival in the Acoramidis Treated Participants Within ATTRibute-CM
Bibliographic record
Abstract
Background: Acoramidis is a novel, potent, investigational, transthyretin (TTR) stabilizer under development for the treatment of TTR amyloidosis that results in near-complete (≥90%) TTR stabilization. In a phase 3 study, ATTRibute-CM, acoramidis demonstrated improved clinical outcomes in participants with transthyretin amyloid cardiomyopathy (ATTR-CM), including a 50% reduction in the risk of CVH compared to placebo over 30 months. The study also demonstrated that cardiovascular hospitalization (CVH) during the study predicted a higher subsequent mortality in participants with ATTR-CM. Hypothesis: CVH portends a higher risk of mortality in participants with ATTR-CM. Since acoramidis reduces CVH, it can improve the prognosis of participants with ATTR-CM. Aim: To evaluate the relationship between CVH and survival in the acoramidis group within ATTRibute-CM. Methods: In this post-hoc analysis, the relationship between those with or without CVH and survival was analyzed within the acoramidis treatment group using the Kaplan-Meier (KM) estimator method. Results: Demographics and baseline disease characteristics were mostly comparable between acoramidis-treated participants with and without CVH, although participants with CVH had a higher baseline NT-proBNP and lower eGFR. At Month 30, in acoramidis-treated participants, those without any CVH (n=300) had a higher survival [86.8% (95% CI = 82.2, 90.3)] versus 62.4% (95% CI = 52.6, 70.7) in those who had any CVH (n=109); p<0.0001 from log-rank test (Figure). Conclusion: In the ATTRibute-CM study, pts without any CVH receiving acoramidis have a higher survival rate. CVHs remain a powerful predictor of mortality. This reinforces the importance of an effective therapy that reduces CVH and in turn may improve survival in patients with ATTR-CM.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".