Nonindustry-Sponsored Preclinical Studies on Statins Yield Greater Efficacy Estimates Than Industry-Sponsored Studies: A Meta-Analysis

Krauth, David; Anglemyer, Andrew; Philipps, Rose; Bero, Lisa

doi:10.1371/journal.pbio.1001770

Cited by 34 publications

(32 citation statements)

References 49 publications

(40 reference statements)

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“…A previous analysis of preclinical studies of statins found a notable discordance between results and conclusions in industry‐sponsored studies compared with non‐industry‐sponsored studies 7. This discrepancy between results and conclusions has also been observed in meta‐analyses of randomized controlled trials and trials of drugs conducted in humans 2, 3.…”

Section: Discussionmentioning

confidence: 95%

“…The Institute of Medicine (IOM) 2010 report on Conflicts of Interest in Medical Research, Education and Practice highlights the need for systematic reviews to reveal the extent of financial relationships and their consequences in preclinical research 6. One systematic review has found that, in contrast to clinical studies, industry‐sponsored preclinical studies underestimate effect sizes of the drugs being tested compared with non‐industry‐sponsored studies 7. Thus, industry sponsors may have different incentives that could influence the outcomes of clinical versus preclinical studies 8.…”

Section: Introductionmentioning

confidence: 99%

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The relationship between risk of bias criteria, research outcomes, and study sponsorship in a cohort of preclinical thiazolidinedione animal studies: a meta‐analysis

Abdel-Sattar

Krauth

Anglemyer

et al. 2014

Evid Based Preclin Med

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IntroductionThere is little evidence regarding the influence of conflicts of interest on preclinical research. This study examines whether industry sponsorship is associated with increased risks of bias and/or effect sizes of outcomes in published preclinical thiazolidinedione (TZD) studies.MethodsWe identified preclinical TZD studies published between January 1, 1965, and November 14, 2012. Coders independently extracted information on study design criteria aimed at reducing bias, results for all relevant outcomes, sponsorship source and investigator financial ties from the 112 studies meeting the inclusion criteria. The average standardized mean difference (SMD) across studies was calculated for plasma glucose (efficacy outcome) and weight gain (harm outcome). In subgroup analyses, TZD outcomes were assessed by sponsorship source and risk of bias criteria.ResultsSeven studies were funded by industry alone, 17 studies funded by both industry and non‐industry, 49 studies funded by non‐industry alone and 39 studies had no disclosures. None of the studies used sample size calculations, intention‐to‐treat analyses, blinding of investigators or concealment of allocation. Most studies reported favourable results (88 of 112) and conclusions (95 of 112) supporting TZD use. Efficacy estimates were significantly larger in six studies sponsored by industry alone (−3.41; 95% CI −5.21, −1.53; I2 = 93%) versus 42 studies sponsored by non‐industry sources (−0.97; 95% CI −1.37, −0.56; I2 = 81%; p‐value = 0.01). Harms estimates were significantly larger in four studies sponsored by industry alone (5.00; 95% CI 1.22, 8.77; I2 = 93%) versus 38 studies sponsored by non‐industry sources (0.30; 95% CI −0.08, 0.68; I2 = 79%; p‐value = 0.02). TZD efficacy and harms did not differ by disclosure of financial COIs or risks of bias.ConclusionsIndustry‐sponsored TZD animal studies have exaggerated efficacy and harms outcomes compared with studies funded by non‐industry sources. There was poor reporting of COIs.

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Section: Discussionmentioning

confidence: 95%

Section: Introductionmentioning

confidence: 99%

The relationship between risk of bias criteria, research outcomes, and study sponsorship in a cohort of preclinical thiazolidinedione animal studies: a meta‐analysis

Abdel-Sattar

Krauth

Anglemyer

et al. 2014

Evid Based Preclin Med

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“…Recent evidence indicated that industry-sponsored research is less biased than academic research [40]. We therefore predicted higher rates of reporting of measures against risks of bias in applications from private compared to academic institutions.…”

Section: Discussionmentioning

confidence: 96%

Authorization of Animal Experiments Is Based on Confidence Rather than Evidence of Scientific Rigor

et al. 2016

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Accumulating evidence indicates high risk of bias in preclinical animal research, questioning the scientific validity and reproducibility of published research findings. Systematic reviews found low rates of reporting of measures against risks of bias in the published literature (e.g., randomization, blinding, sample size calculation) and a correlation between low reporting rates and inflated treatment effects. That most animal research undergoes peer review or ethical review would offer the possibility to detect risks of bias at an earlier stage, before the research has been conducted. For example, in Switzerland, animal experiments are licensed based on a detailed description of the study protocol and a harm–benefit analysis. We therefore screened applications for animal experiments submitted to Swiss authorities (n = 1,277) for the rates at which the use of seven basic measures against bias (allocation concealment, blinding, randomization, sample size calculation, inclusion/exclusion criteria, primary outcome variable, and statistical analysis plan) were described and compared them with the reporting rates of the same measures in a representative sub-sample of publications (n = 50) resulting from studies described in these applications. Measures against bias were described at very low rates, ranging on average from 2.4% for statistical analysis plan to 19% for primary outcome variable in applications for animal experiments, and from 0.0% for sample size calculation to 34% for statistical analysis plan in publications from these experiments. Calculating an internal validity score (IVS) based on the proportion of the seven measures against bias, we found a weak positive correlation between the IVS of applications and that of publications (Spearman’s rho = 0.34, p = 0.014), indicating that the rates of description of these measures in applications partly predict their rates of reporting in publications. These results indicate that the authorities licensing animal experiments are lacking important information about experimental conduct that determines the scientific validity of the findings, which may be critical for the weight attributed to the benefit of the research in the harm–benefit analysis. Similar to manuscripts getting accepted for publication despite poor reporting of measures against bias, applications for animal experiments may often be approved based on implicit confidence rather than explicit evidence of scientific rigor. Our findings shed serious doubt on the current authorization procedure for animal experiments, as well as the peer-review process for scientific publications, which in the long run may undermine the credibility of research. Developing existing authorization procedures that are already in place in many countries towards a preregistration system for animal research is one promising way to reform the system. This would not only benefit the scientific validity of findings from animal experiments but also help to avoid unnecessary harm to animals for inconclusive research.

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“…When a promising therapy fails in clinical trials there is an opportunity to critically evaluate flaws in the experimental model in the reverse translation approach: however, attempts at reverse translation have been rather limited. Explanations for failed translation that explore reasons beyond preclinical modeling have been advanced, including clinical trial design features, inconsistent test article application between nonclinical and clinical trials (dose, timing, and route), bias or selective reporting, and data interpretation Krauth et al, 2014).…”

Section: Why Are Some Models More Predictive Than Others?mentioning

confidence: 99%

The safety, efficacy and regulatory triangle in drug development: Impact for animal models and the use of animals

Meer

Graham

Schuurman³

2015

European Journal of Pharmacology

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Nonindustry-Sponsored Preclinical Studies on Statins Yield Greater Efficacy Estimates Than Industry-Sponsored Studies: A Meta-Analysis

Abstract: This study by Lisa Bero and colleagues uses published preclinical statin research to show that nonindustry-funded animal studies yield more efficacious drug results than do industry-funded ones.

Cited by 34 publications

References 49 publications

The relationship between risk of bias criteria, research outcomes, and study sponsorship in a cohort of preclinical thiazolidinedione animal studies: a meta‐analysis

The relationship between risk of bias criteria, research outcomes, and study sponsorship in a cohort of preclinical thiazolidinedione animal studies: a meta‐analysis

Authorization of Animal Experiments Is Based on Confidence Rather than Evidence of Scientific Rigor

The safety, efficacy and regulatory triangle in drug development: Impact for animal models and the use of animals

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