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Perils and pitfalls of reporting sex differences.

ABSTRACT: The idea of sex differences in the brain both fascinates and inflames the public. As a result, the communication and public discussion of new findings is particularly vulnerable to logical leaps and pseudoscience. A new US National Institutes of Health policy to consider both sexes in almost all preclinical research will increase the number of reported sex differences and thus the risk that research in this important area will be misinterpreted and misrepresented. In this article, I consider ways in which we might reduce that risk, for example, by (i) employing statistical tests that reveal the extent to which sex explains variation, rather than whether or not the sexes 'differ', (ii) properly characterizing the frequency distributions of scores or dependent measures, which nearly always overlap, and (iii) avoiding speculative functional or evolutionary explanations for sex-based variation, which usually invoke logical fallacies and perpetuate sex stereotypes. Ultimately, the factor of sex should be viewed as an imperfect, temporary proxy for yet-unknown factors, such as hormones or sex-linked genes, that explain variation better than sex. As scientists, we should be interested in discovering and understanding the true sources of variation, which will be more informative in the development of clinical treatments.

SUBMITTER: Maney DL

PROVIDER: S-EPMC4785904 | biostudies-literature | 2016 Feb

REPOSITORIES: biostudies-literature

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Perils and pitfalls of reporting sex differences.

Maney Donna L DL

Philosophical transactions of the Royal Society of London. Series B, Biological sciences 20160201 1688

The idea of sex differences in the brain both fascinates and inflames the public. As a result, the communication and public discussion of new findings is particularly vulnerable to logical leaps and pseudoscience. A new US National Institutes of Health policy to consider both sexes in almost all preclinical research will increase the number of reported sex differences and thus the risk that research in this important area will be misinterpreted and misrepresented. In this article, I consider way ...[more]

PMID: 26833839

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Project description:Background Medical treatment should be tailored to an individual's characteristics to optimize treatment benefits. We examined whether case-only analyses from spontaneous reporting systems can detect host-medication interactions in oral antidiabetic drug-associated myocardial infarction. Methods and Results Interaction between sex and use of oral antidiabetic drugs was mined among patients with myocardial infarction in the US Food and Drug Administration Adverse Event Reporting System from 2004 to 2014, including 55 718 males and 42 428 females. The odds ratio ( OR ) of multiplicative interactions was used to estimate sex-drug interaction. Detected signs of these interactions were then validated by a nested case-control study utilizing a healthcare record database, Taiwan's National Health Insurance Research Database, from 2001 to 2014, including 31 585 cases and 126 340 controls. In the US Food and Drug Administration Adverse Event Reporting System, a higher proportion of male than female patients used metformin (10.32% in males versus 7.82% in females) and sulfonylureas (4.75% in males versus 3.43% in females); after adjusting for patients' pharmacy-based chronic disease score, males had a higher risk of metformin-associated ( OR =1.07; 99% confidence interval, 1.00-1.14) and sulfonylureas-associated ( OR =1.21; 99% confidence interval, 1.10-1.33) myocardial infarction than females. Detected signs of sex-drug interactions were validated in the National Health Insurance Research Database ( OR for metformin=1.14; 99% confidence interval, 1.03-1.26; OR for sulfonylureas=1.13; 99% confidence interval, 1.02-1.25). Conclusions Males have a higher risk of metformin- and sulfonylureas-associated myocardial infarction than females, which suggests that sex-drug interactions are a key issue in diabetes mellitus treatment plan development. This case-only approach using information from spontaneous reporting systems may be a potential tool for screening host-medication interactions that cause adverse events.

Dataset Information

Perils and pitfalls of reporting sex differences.

Publications

Perils and pitfalls of reporting sex differences.

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