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Prof. Kai Savonen
When a treatment aimed at changing our physiology is experienced, various inherited and acquired characteristics may modify the effect of the treatment, making it more or less beneficial, harmful, or ineffective in different individuals . The issue of individual responses to treatments is therefore one of the most important in experimental research, especially now that genome sequencing and pervasive monitoring of individuals can provide researchers with the subject characteristics that account for individual responses and allow more efficient targeting of treatments to individuals.
In 'personalised medicine', various plots and analyses are purported to quantify individual differences in intervention response, identify responders/non-responders and explore response moderators or mediators. In their thoughtful review Atkins and Batterham explain how popular plots used to present individual differences in response are contaminated by random within-subject variation and the regression to the mean artefact . Using a simulated data set of blood pressure measurements, they show that large individual differences in physiological response can be suggested by some plots and analyses, even when the true magnitude of response is exactly the same in all individuals.
They present the appropriate designs and analysis approaches for quantifying the true interindividual variation in physiological response . It is imperative to include a comparator arm/condition to quantify true interindividual differences in response. The most important statistic is the standard deviation (SD) of changes in the intervention arm, which should be compared with the same SD in the comparator arm. Only if the difference between these SDs is clinically relevant is it logical to go on to explore any moderators or mediators of the intervention effect that might explain the individual response.
Personalised medicine is a potentially important topic for researching health interventions . Nevertheless, it is crucial to know whether the true individual difference in response is clinically important before any attempts are made to identify ‘non-responders’ and explore reasons for their non-response. It is primary important to look at the data in both intervention and comparator arms before leaping to conclusions that individual differences in response are important enough for further analysis. Otherwise there is a danger that personalised medicine is based on a leap of faith rather than reliable evidence derived from sound study designs and appropriate statistical analysis.
Note: The content of this article reflects the personal opinion of the author/s and is not necessarily the official position of the European Society of Cardiology
1. Hopkins WG. Individual responses made easy. J Appl Physiol 2015;118:1444-6.
2. Atkinson G, Batterham AM. True and false interindividual differences in the physiological response to an intervention. Exp Physiol 2015;100:577-88.
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