Industry sponsorship bias in research findings: a network meta-analysis of LDL cholesterol reduction in randomised trials of statins
Bibliographic record
Abstract
OBJECTIVE: To explore the risk of industry sponsorship bias in a systematically identified set of placebo controlled and active comparator trials of statins. DESIGN: Systematic review and network meta-analysis. ELIGIBILITY: Open label and double blind randomised controlled trials comparing one statin with another at any dose or with control (placebo, diet, or usual care) for adults with, or at risk of developing, cardiovascular disease. Only trials that lasted longer than four weeks with more than 50 participants per trial arm were included. Two investigators assessed study eligibility. DATA SOURCES: Bibliographic databases and reference lists of relevant articles published between 1 January 1985 and 10 March 2013. DATA EXTRACTION: One investigator extracted data and another confirmed accuracy. MAIN OUTCOME MEASURE: Mean absolute change from baseline concentration of low density lipoprotein (LDL) cholesterol. DATA SYNTHESIS: Study level outcomes from randomised trials were combined using random effects network meta-analyses. RESULTS: We included 183 randomised controlled trials of statins, 103 of which were two-armed or multi-armed active comparator trials. When all of the existing randomised evidence was synthesised in network meta-analyses, there were clear differences in the LDL cholesterol lowering effects of individual statins at different doses. In general, higher doses resulted in higher reductions in baseline LDL cholesterol levels. Of a total of 146 industry sponsored trials, 64 were placebo controlled (43.8%). The corresponding number for the non-industry sponsored trials was 16 (43.2%). Of the 35 unique comparisons available in 37 non-industry sponsored trials, 31 were also available in industry sponsored trials. There were no systematic differences in magnitude between the LDL cholesterol lowering effects of individual statins observed in industry sponsored versus non-industry sponsored trials. In industry sponsored trials, the mean change from baseline LDL cholesterol level was on average 1.77 mg/dL (95% credible interval -11.12 to 7.66) lower than the change observed in non-industry sponsored trials. There was no detectable inconsistency in the evidence network. CONCLUSIONS: Our analysis shows that the findings obtained from industry sponsored statin trials seem similar in magnitude as those in non-industry sources. There are actual differences in the effectiveness of individual statins at various doses that explain previously observed discrepancies between industry and non-industry sponsored trials.
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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 | 0.124 | 0.342 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.015 | 0.043 |
| Bibliometrics | 0.012 | 0.009 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.004 | 0.003 |
| 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".