Appreciating the Nuance of Daily Symptom Variation to Individualize Patient Care

A Useful and Sustainable Role for N-of-1 Trials in the Healthcare Ecosystem

Clinicians and patients often try a treatment for an initial period to inform longer‐term therapeutic decisions. A more rigorous approach involves N‐of‐1 trials. In these single‐patient crossover trials, typically conducted in patients with chronic conditions, individual patients are given candidate treatments in a double‐blinded, random sequence of alternating periods to determine the most effective treatment for that patient. However, to date, these trials are rarely done outside of research settings and have not been integrated into general care where they could offer substantial benefit. Designating this classical, N‐of‐1 trial design as type 1, there also are new and evolving uses of N‐of‐1 trials that we designate as type 2. In these, rather than focusing on optimizing treatment for chronic diseases when multiple approved choices are available, as is typical of type 1, a type 2 N‐of‐1 trial tests treatments designed specifically for a patient with a rare disease, to facilitate personalized medicine. While the aims differ, both types face the challenge of collecting individual‐patient evidence using standard, trusted, widely accepted methods. To fulfill their potential for producing both clinical and research benefits, and to be available for wide use, N‐of‐1 trials will have to fit into the current healthcare ecosystem. This will require generalizable and accepted processes, platforms, methods, and standards. This also will require sustainable value‐based arrangements among key stakeholders. In this article, we review opportunities, stakeholders, issues, and possible approaches that could support general use of N‐of‐1 trials and deliver benefit to patients and the healthcare enterprise. To assess and expand the benefits of N‐of‐1 trials, we propose multistakeholder meetings, workshops, and the generation of methods, standards, and platforms that would support wider availability and the value of N‐of‐1 trials.

Analysing N-of-1 observational data in health psychology and behavioural medicine: a 10-step SPSS tutorial for beginners

Background: N-of-1 observational studies can be used to describe natural intra-individual changes in health-related behaviours or symptoms over time, to test behavioural theories and to develop highly personalised health interventions. To date, N-of-1 observational methods have been under-used in health psychology and behavioural medicine. One reason for this may be the perceived complexity of statistical analysis of N-of-1 data.

Objective: This tutorial paper describes a 10-step procedure for the analysis of N-of-1 observational data using dynamic regression modelling in SPSS for researchers, students and clinicians who are new to this area. The 10-step procedure is illustrated using real data from an N-of-1 observational study exploring the relationship between pain and physical activity.

Conclusion: The availability of a user-friendly and robust statistical technique for the analysis of N-of-1 data using SPSS may foster increased awareness, knowledge and skills and establish N-of-1 designs as a useful methodological tool in health psychology and behavioural medicine.