Evaluation of Person-level Heterogeneity of Treatment Effects in Published Multiperson N-of-1 Studies: Systematic Review and Reanalysis
To understand when and how individual treatment effects are examined, conducted and reported, this study evaluated existing multiperson N-of-1 studies, which can identify whether an intervention is likely to benefit or cause unwanted effects in an individual patient.
Authors: Raman G, Balk EM, Lai L, Shi J, Chan J, Lutz JS, Dubois RW, Kravitz RL, Kent DM
Publication: BMJ Open, published online May 26, 2018
Scientists recognize that individual patients may react differently to a particular health treatment, even if it works well for the average patient population with the same condition. These differences are the underpinning for personalized medicine, in which new methods of molecular analysis are used to determine a patient’s treatment options based on his or her genetic and environmental profile.
Research published in BMJ Open indicates that these individual differences are rarely studied, although individual responses to treatments (known as personal-level heterogeneity of treatment effects, or HTE) are common and often substantial. The study strongly indicates that for certain conditions, the “average” patient is just a myth; a treatment that works well in some patients may not work well for certain individuals.
To understand when and how individual treatment effects are examined, conducted and reported, this study evaluated existing multiperson N-of-1 studies, which can identify whether an intervention is likely to benefit or cause unwanted effects in an individual patient. During an N-of-1 study, each patient receives two or more treatments in a predefined, often randomized, sequence (e.g., they try treatment A and monitor outcomes, then switch to treatment B and monitor outcomes. Depending on those outcomes, patients could return to treatment A, and so on.) Multiperson N-of-1 studies also are useful in comparing treatment differences within an individual patient as well as between individuals.
Highlights from the study include:
- The findings could have implications for clinical practice and formulary design. For conditions marked by individual differences in treatment effects, even when studies show one treatment might work better on average than others, having multiple medication options would help to improve outcomes across patients. Doing so can ensure patients get the right medication for their needs, especially for chronic conditions where individual patient differences might not be detectable in conventional trials and subgroup analysis.
- This research shows N-of-1 studies may be clinically relevant for certain conditions, especially conditions for which there is a greater amount of variation in patient response to a treatment.
- Individual patient results are sometimes reported in existing studies, but are not always identified and analyzed. It is possible to extract relevant information from existing studies via reanalysis, but those results are currently rarely analyzed to show person-level HTE.
- N-of-1 studies are underutilized tools to help identify where individual patient differences may exist, and where efforts to find predictors could be focused in the future. Future studies are needed to apply greater methodological rigor to improve the state of science on the evaluation of individual treatment effects.