Doubly blind: a systematic review of gender in randomised controlled trials

Although observational data show social characteristics such as gender or socio-economic status to be strong predictors of health, their impact is seldom investigated in randomised controlled studies (RCTs).

Using a random sample of recent RCTs from high-impact journals, we examined how the most often recorded social characteristic, sex/gender, is considered in design, analysis, and interpretation. Of 712 RCTs published from September 2008 to 31 December 2013 in the Annals of Internal Medicine, British Medical Journal, Lancet, Canadian Medical Association Journal, or New England Journal of Medicine, we randomly selected 57 to analyse funding, methods, number of centres, documentation of social circumstances, inclusion/exclusion criteria, proportions of women/men, and reporting about sex/gender in analyses and discussion.

Participants' sex was recorded in most studies (52/57). Thirty-nine percent included men and women approximately equally. Overrepresentation of men in 43% of studies without explicit exclusions for women suggested interference in selection processes. The minority of studies that did analyse sex/gender differences (22%) did not discuss or reflect upon these, or dismissed significant findings. Two studies reinforced traditional beliefs about women's roles, finding no impact of breastfeeding on infant health but nevertheless reporting possible benefits. Questionable methods such as changing protocols mid-study, having undefined exclusion criteria, allowing local researchers to remove participants from studies, and suggesting possible benefit where none was found were evident, particularly in industry-funded research.

Social characteristics like sex/gender remain hidden from analyses and interpretation in RCTs, with loss of information and embedding of error all along the path from design to interpretation, and therefore, to uptake in clinical practice. Our results suggest that to broaden external validity, in particular, more refined trial designs and analyses that account for sex/gender and other social characteristics are needed.