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The oxidative stress theory of disease: levels of evidence and epistemological aspects
Author(s) -
Ghezzi Pietro,
Jaquet Vincent,
Marcucci Fabrizio,
Schmidt Harald H H W
Publication year - 2017
Publication title -
british journal of pharmacology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.432
H-Index - 211
eISSN - 1476-5381
pISSN - 0007-1188
DOI - 10.1111/bph.13544
Subject(s) - disease , narrative review , clinical trial , popularity , medicine , perspective (graphical) , oxidative stress , bioinformatics , psychology , intensive care medicine , computer science , biology , social psychology , pathology , artificial intelligence
The theory that oxidative stress (OS) is at the root of several diseases is extremely popular. However, so far, no antioxidant has been recommended or offered by healthcare systems neither has any been approved as therapy by regulatory agencies that base their decisions on evidence-based medicine. This is simply because, so far, despite many preclinical and clinical studies indicating a beneficial effect of antioxidants in many disease conditions, randomised clinical trials have failed to provide the evidence of efficacy required for drug approval. In this review, we discuss the levels of evidence required to claim causality in preclinical research on OS, the weakness of the oversimplification associated with OS theory of disease and the importance of the narrative in its popularity. Finally, from a more translational perspective, we discuss the reasons why antioxidants acting by scavenging ROS might not only prevent their detrimental effects but also interfere with essential signalling roles. We propose that ROS have a complex metabolism and are generated by different enzymes at diverse sites and at different times. Aggregating this plurality of systems into a single theory of disease may not be the best way to develop new drugs, and future research may need to focus on specific oxygen-toxifying pathways rather than on non-specific ROS scavengers. Finally, similarly to what is nowadays required for clinical trials, we recommend making unpublished data available in repositories (open data), as this will allow big data approaches or meta-analyses, without the drawbacks of publication bias.

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