Translational failure of anti-inflammatory compounds for myocardial infarction: a meta-analysis of large animal models

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Publication year
2016Source
Cardiovascular Research, 109, 2, (2016), pp. 240-8ISSN
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Article / Letter to editor

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Organization
Central Animal Laboratory
Journal title
Cardiovascular Research
Volume
vol. 109
Issue
iss. 2
Page start
p. 240
Page end
p. 8
Subject
Radboudumc 16: Vascular damage RIHS: Radboud Institute for Health SciencesAbstract
AIMS: Numerous anti-inflammatory drugs have been tested in large animal studies of myocardial infarction (MI). Despite positive results, translation of anti-inflammatory strategies into clinical practice has proved to be difficult. Critical disparities between preclinical and clinical study design that influence efficacy may partly be responsible for this translational failure. The aim of the present systematic review was to better understand which factors underlie the failure of transition towards the clinic. METHODS AND RESULTS: Meta-analysis and regression of large animal studies were performed to identify sources that influenced effect size of anti-inflammatory compounds in large animal models of MI. We included 183 studies, containing 3331 large animals. Infarct size (IS) as a ratio of the area at risk (12.7%; 95% confidence interval, CI 11.1-14.4%, P < 0.001) and IS as a ratio of the left ventricle (3.9%; 95% CI 3.1-4.7%, P < 0.001) were reduced in treatment compared with control groups. Effect size was higher when outcome was assessed early after MI (P = 0.013) and where studies included only male animals (P < 0.001). Mortality in treated animals was higher in studies that blinded the investigator during the experiment (P = 0.041) and depended on the type of drug used (P < 0.001). CONCLUSIONS: As expected, treatment with anti-inflammatory drugs leads to smaller infarct size in large animal MI models. Timing of outcome assessment, sex, and study quality are significantly associated with outcome and may explain part of the translational failure in clinical settings. Effect size depends on the type of drug used, enabling identification of compounds for future clinical testing.
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