Inflammation reduction with colchicine in atherosclerotic cardiovascular disease
Bibliographic record
Abstract
This commentary refers to ‘Long-term trials of colchicine for secondary prevention of vascular events: a meta-analysis’, by M. Samuel et al., https://doi.org/10.1093/eurheartj/ehaf174 and the discussion piece ‘Colchicine in cardiovascular disease: a promising therapy, a precision challenge’, by P. Karakasis et al., https://doi.org/10.1093/eurheartj/ehaf629. Colchicine has recently emerged as an efficacious and cost-effective therapy to target the residual risk of inflammation in atherosclerotic cardiovascular disease (ASCVD), as reflected in European and American clinical guideline recommendations. In addition to other guideline-directed medical therapy, colchicine reduced major adverse cardiovascular events (MACE) by 25% in a meta-analysis of 6 randomized trials and 21 800 patients.1 Karakasis and colleagues concluded that these results support the benefit and role of colchicine for the treatment of ASCVD and correctly emphasized some important considerations.2 Karakasis and colleagues are correct to highlight the effect of COVID-19 on the results of CLEAR-SYNERGY and dispel potential uncertainty regarding the efficacy of colchicine.2 The P-value for the interaction between treatment and COVID phase in that trial was <0.10, and stratified results showed a 22% reduction in MACE with colchicine prior to COVID-19, an effect comparable to that in other colchicine trials.3 The effect of COVID-19 on an apparent reduction in the incidence of cardiovascular events in clinical trials is well-documented.4 It is primarily due to underreporting, misclassification, and detection bias of outcomes. Comparison to pre-pandemic trials like COMPLETE suggests underreporting of myocardial infarctions by at least 60% in CLEAR-SYNERGY. Furthermore, inadequate control of inflammation in the colchicine arm of CLEAR-SYNERGY (least-squares mean hs-CRP: 3.0 mg/L) probably contributed to its failure and the strange lack of benefit on pericarditis.4 Samuel et al reported a sensitivity analysis that pooled the results of the pre-COVID-19 period of CLEAR-SYNERGY with the other trials, which yielded a pooled relative risk reduction of 30% in MACE with colchicine (HR, 0.70; 95% CI, .60–.81).1
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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 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.006 | 0.010 |
| Insufficient payload (model declined to judge) | 0.011 | 0.003 |
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".