Effect of regression to the mean on decision making in health care

Knowledge of regression to the mean can help with everything from interpreting test results to improving your career prospects. All healthcare professionals should be aware of its implication

Evidence for risk of bias in cluster randomised trials: review of recent trials published in three general medical journals

Objective To examine the prevalence of a risk of bias associated with the design and conduct of cluster randomised controlled trials among a sample of recently published studies. Design Retrospective review of cluster randomised trials published in the BMJ, Lancet, and New England Journal of Medicine from January 1997 to October 2002. Main outcome measures Prevalence of secure randomisation of clusters, identification of participants before randomisation (to avoid foreknowledge of allocation), differential recruitment between treatment arms, differential application of inclusion and exclusion criteria, and differential attrition. Results Of the 36 trials identified, 24 were published in the BMJ, I I in the Lancet, and a single trial in the New England journal of Medicine. At the cluster level, 15 (42%) trials provided evidence for secure allocation and 25 (69%) used stratified allocation. Few trials showed evidence of imbalance at the cluster level. However, some evidence of susceptibility to risk of bias at the individual level existed in 14 (39%) studies. Conclusions Some recently published cluster randomised trials may not have taken adequate precautions to guard against threats to the internal validity of their design

Population Genetics of Rare Variants and Complex Diseases

Identifying drivers of complex traits from the noisy signals of genetic variation obtained from high throughput genome sequencing technologies is a central challenge faced by human geneticists today. We hypothesize that the variants involved in complex diseases are likely to exhibit non-neutral evolutionary signatures. Uncovering the evolutionary history of all variants is therefore of intrinsic interest for complex disease research. However, doing so necessitates the simultaneous elucidation of the targets of natural selection and population-specific demographic history. Here we characterize the action of natural selection operating across complex disease categories, and use population genetic simulations to evaluate the expected patterns of genetic variation in large samples. We focus on populations that have experienced historical bottlenecks followed by explosive growth (consistent with most human populations), and describe the differences between evolutionarily deleterious mutations and those that are neutral. Genes associated with several complex disease categories exhibit stronger signatures of purifying selection than non-disease genes. In addition, loci identified through genome-wide association studies of complex traits also exhibit signatures consistent with being in regions recurrently targeted by purifying selection. Through simulations, we show that population bottlenecks and rapid growth enables deleterious rare variants to persist at low frequencies just as long as neutral variants, but low frequency and common variants tend to be much younger than neutral variants. This has resulted in a large proportion of modern-day rare alleles that have a deleterious effect on function, and that potentially contribute to disease susceptibility.Comment: 36 pages, 7 figure

Sources of bias in outcome assessment in randomised controlled trials: a case study

Randomised controlled trials (RCTs) can be at risk of bias. Using data from a RCT we considered the impact of post-randomisation bias. We compared the trial primary outcome, which was administered blindly, with the secondary outcome which was not administered blindly. 522 children from 44 schools were randomised to receive a one-to-one maths tuition programme that was assessed using two outcome measures. The primary outcome measure was assessed blindly whilst the secondary outcome was delivered by the classroom teacher and therefore this was un-blinded. The effect sizes for primary and secondary outcomes were substantially different (0.33 and 1.11 respectively). Test questions that were similar between the two tests this did not explain the difference. There was greater heterogeneity between schools for the primary outcome, compared with the secondary outcome. We conclude that, in this trial, the difference between the primary and secondary outcomes was likely to have been due to lack of blinding of testers