MétaCan
Menu
← Back to cohort

Combination of moderate-intensity statins and ezetimibe versus high-intensity statins alone for primary prevention of cardiovascular events

2024· article· en· W4403822648 on OpenAlexaffabout
Lucas C. Godoy, Michel Kiflen, Rea Alonzo, Anne Chu, Peter C. Austin, Jiming Fang, Shalane Basque, Patrick R. Lawler, J T Nunes, Cynthia A. Jackevicius, Dennis T. Ko, Douglas S. Lee, Shaun G. Goodman, Michael E. Farkouh, Jacob A. Udell

Bibliographic record

VenueEuropean Heart Journal · 2024
Typearticle
Languageen
FieldMedicine
TopicLipoproteins and Cardiovascular Health
Canadian institutionsUniversity of TorontoHealth Sciences CentreSunnybrook Health Science CentreMcGill University Health Centre
Fundersnot available
KeywordsMedicineEzetimibeIntensity (physics)Internal medicineStatinPrimary preventionCardiologyPharmacologyDisease

Abstract

fetched live from OpenAlex

Abstract Background Combination of a moderate-intensity statin with ezetimibe can lead to similar reductions in cardiovascular events as monotherapy with a high-intensity statin in patients with established atherosclerotic cardiovascular disease (ASCVD). The comparative effectiveness of these two cholesterol-lowering strategies in the primary prevention setting is unknown. Purpose To compare incident ASCVD events associated with a combination of moderate-intensity statin and ezetimibe versus monotherapy with a high-intensity statin in adults without prior history of cardiovascular disease. Methods We conducted a new-user active comparator retrospective population-based cohort study in Canada. We included all adults aged ≥ 67 years (eligible for drug coverage) with a first prescription of either a combination of moderate-intensity statin with ezetimibe ("combination therapy") or high-intensity statin alone between January 2010 and December 2022. Patients were excluded if they had not received any prior lipid lowering therapies or had a history of myocardial infarction (MI), stroke, heart failure, peripheral vascular disease or prior coronary revascularisation at any time before or within 3 months of treatment initiation. The primary outcome was a composite of all-cause death, hospitalization for MI or stroke, or coronary revascularization. An inverse probability of treatment weighting propensity score was used to account for confounding (demographics, comorbidities, laboratory tests, other medications). Results Among 67,884 patients (mean age: 74.0±5.5y; 53% females), 8,798 (13%) initiated combination therapy and 59,086 (87%) initiated a high-intensity statin. At 1 year, after weighting, the mean achieved LDL-C was ~1.9 mmol/L in both groups. The median follow-up was 6.5 years. The cumulative incidence of the primary outcome at 10 years in the weighted cohort was 32.7% in the combination therapy group and 36.1% in the high-intensity statin group (HR: 0.87; 95% CI: 0.82 to 0.92; p<0.001; absolute risk reduction: 3.5%; 95% CI: 0.8 to 6.1; Figure 1). This result was primarily driven by a lower risk of all-cause death (HR: 0.85; 95% CI: 0.80 to 0.91; p<0.001; Figure 2) and stroke (cause-specific [cs] HR: 0.86; 95% CI 0.74 to 0.99; p=0.04), whereas no differences were observed in the risk of MI (csHR: 0.97; 95% CI: 0.82 to 1.15) or coronary revascularization (csHR: 0.97; 95% CI 0.85 to 1.11). Conclusion The combination of moderate-intensity statins with ezetimibe was associated with a lower risk of incident ASCVD compared with high-intensity statins alone among primary prevention patients in a real-world setting. These results were driven by a lower risk of all-cause death and stroke, but not coronary events. The influence of statin intolerance on the allocated strategy and adherence to therapy cannot be addressed in this analysis, which, along with verifying these estimates, may be best determined in a prospective randomized trial.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.041
GPT teacher head0.297
Teacher spread0.256 · 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 designRandomized trial
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".

Quick stats

Citations0
Published2024
Admission routes2
Has abstractyes

Explore more

Same venueEuropean Heart Journal→Same topicLipoproteins and Cardiovascular Health→French-language works237,207→