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Reduction in the risk of MACE with apabetalone in patients with recent acute coronary syndrome and diabetes according to NAFLD fibrosis score: exploratory analysis of the BETonMACE trial

2021· article· en· W3208115069 on OpenAlexaff
Peter P. Tóth, Gregory G. Schwartz, S J Nicholls, C. Halliday, Henry N. Ginsberg, Jan O. Johansson, Kamyar Kalantar‐Zadeh, Ewelina Kulikowski, Ken Lebioda, Norman C.W. Wong, Michael Sweeney, Kausik K. Ray

Bibliographic record

VenueEuropean Heart Journal · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicProtein Degradation and Inhibitors
Canadian institutionsResverlogix (Canada)
Fundersnot available
KeywordsMedicineMaceInternal medicineHazard ratioGastroenterologyClinical endpointFibrosisType 2 diabetesMetabolic syndromeDiabetes mellitusCardiologyMyocardial infarctionEndocrinologyClinical trialObesityPercutaneous coronary interventionConfidence interval

Abstract

fetched live from OpenAlex

Abstract Background/Introduction Both major adverse cardiovascular events (MACE) and non-alcoholic fatty-liver disease (NAFLD) are highly prevalent in patients with high BMI and long-standing type 2 diabetes (T2DM). NAFLD is characterized by an augmented hepatic inflammation and fat deposition and is strongly associated with metabolic syndrome. Patients with NAFLD are at an increased risk of cardiovascular (CV) events, and MACE is the leading cause of death for patients with NAFLD. Apabetalone (APB) is a novel selective inhibitor of bromodomain and extra-terminal (BET) proteins, epigenetic regulators of gene expression. In the Phase 3 BETonMACE trial treatment of 2,425 T2DM patients post ACS with APB, resulted in hazard ratios (HR) of 0.82 (p=0.11) for the primary endpoint of ischemic MACE (CV death, non-fatal MI or stroke) and 0.59 (p=0.03) for the secondary endpoint of heart failure hospitalization (HFH) vs placebo (PBO). Transient elevations of alanine aminotransferase greater than 5xULN occurred in 3.3% of APB treated patients. Purpose In this exploratory post hoc analysis of BETonMACE we evaluated risk modification for a composite of MACE+HFH by APB based on the Angulo NAFLD fibrosis score (FS) using 6 variables (age, BMI, hyperglycemia/diabetes, AST/ALT ratio, platelet count, and albumin). The NAFLD FS categorizes individuals into groups that correlate with differing levels of fibrosis in biopsy studies: (FS F0-F2, no significant fibrosis; FS ID, indeterminant; and FS F3-F4, significant fibrosis). Methods Baseline characteristics and blood measurements were used to determine NAFLD FS at baseline. The incidence of MACE+HHF was compared between treatment groups. Results Based on FS, there were 618 pts were classified as FS F0-F2 (n=328 APB, n=290 PBO), 1,440 pts were classified as FS ID (n=708 APB, n=732 PBO) and 289 pts were classified as FS F3-F4 (n=144 APB, n=145). MACE+HHF in the PBO group was higher in FS ID and FS F3-F4 compared to FS F0-F2 (17.2% vs 15.0% vs 9.7%) and therefore the former two groups were combined into an elevated risk FS+ group. FS+ pts were older (63 vs 56), had longer duration of T2DM (9.0 vs 7.3 yrs), and higher BMI (30.8 vs 28.6) compared to FS- pts. Overall, APB was associated with fewer MACE+HHF (HR 0.78, 95% CI 0.60–1.01, p=0.06) compared to PBO in the FS+ pts with adjustment for age, duration of T2DM and BMI. Conclusions Patients with T2DM and ACS may share common risk factors with patients with NAFLD. Apabetalone appears to exert a favorable effect on MACE in patients with risk factors for NAFLD. Whether apabetalone has a modulatory effect on the development and progression of NAFLD is an important question requiring further investigation. Funding Acknowledgement Type of funding sources: Private company. Main funding source(s): Resverlogix Corp.

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 imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.003
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.013
GPT teacher head0.227
Teacher spread0.214 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations0
Published2021
Admission routes1
Has abstractyes

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