ArticleBritish journal of clinical pharmacology2016
Cholesterol trials and mortality.
Article in British journal of clinical pharmacology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
10 citing papers in PubMed, 19 citations in OpenAlex.
- Trends in Lipid-Lowering Agent Consumption in Croatia: A 25-Year Observational Study.Pharmacology research & perspectives · 2025Observational
- Familial Hypercholesterolaemia as a Predisposing Factor for Atherosclerosis.Biomedicines · 2022Review
- Translating the dose response into risk and benefit.British journal of clinical pharmacology · 2019Review
- The pharmacodynamic and clinical trial evidence for statin dose.British journal of clinical pharmacology · 2018Review
- Disconnect Between Genes Associated With Ischemic Heart Disease and Targets of Ischemic Heart Disease Treatments.EBioMedicine · 2018Article
- When less is more - efficacy with less toxicity at the ED50.British journal of clinical pharmacology · 2017Article
- Statins and mortality: the untold story.British journal of clinical pharmacology · 2017Article
- Composite endpoints and the distortion of risk-benefit analysis.British journal of clinical pharmacology · 2017Article
- Cholesterol trials and mortality.British journal of clinical pharmacology · 2016Article
- Statins in primary prevention: is the enthusiasm justified?Indian heart journalArticle
Corrections and comments
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Authors and funding
3 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
An overview of clinical trials can reveal a class effect on mortality that is not apparent from individual trials. Most large trials of lipid pharmacotherapy are not powered to detect differences in mortality and instead assess efficacy with composite cardiovascular endpoints. We illustrate the importance of all-cause mortality data by comparing survival in three different sets of the larger controlled lipid trials that underpin meta-analyses. These trials are for fibrates and statins. Fibrate treatment in five of the six main trials was associated with a decrease in survival, one fibrate trial showed a non-significant reduction in mortality that can be explained by a different target population. In secondary prevention, statin treatment increased survival in all five of the main trials, absolute mean increase ranged from 0.43% to 3.33%, the median change was 1.75%, which occurred in the largest trial. In primary prevention, statin treatment increased survival in six of the seven main trials, absolute mean change in survival ranged from -0.09% to 0.89%, median 0.49%. Composite safety endpoints are rare in these trials. The failure to address composite safety endpoints in most lipid trials precludes a balanced summary of risk-benefit when a composite has been used for efficacy. Class effects on survival provide informative summaries of the risk-benefit of lipid pharmacotherapy. We consider that the presentation of key mortality/survival data adds to existing meta-analyses to aid personal treatment decisions.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.