Using serial N-of-1 trials and subsequent analysis with Bayesian methods may allow study of therapies using small numbers of subjects. Our research questions were: (1) Can serial N-of-1 trials analyzed with Bayesian statistical techniques be used to estimate the population effect of a therapeutic intervention? (2) Compared to placebo, how likely is it that low-dose amitriptyline therapy in children aged 10-18 years with active polyarticular-course juvenile idiopathic arthritis (JIA) results in a significant improvement in pain?
Six children (age 10.3-16.3 yrs, 4 girls) were enrolled. There were 3 pairs of randomized, double-blinded treatments (amitriptyline 25 mg or placebo) per participant. Each treatment lasted 2 weeks, with a 1 week washout. The primary outcome was pain, measured by 10 cm visual analog scale. Assessments were at the beginning and end of each treatment. A Bayesian statistical model was used to determine the treatment effect. Values < 0 indicated superiority of amitriptyline.
Bayesian techniques were used successfully to obtain estimates of population effect, despite the small number of participants. The mean treatment effect for pain was 0.67 (SD 0.89, 95% credible interval -0.99, 2.55). The probability that the treatment effect was < 0 was only 16%.
These methods can be used successfully to estimate population effects when sample sizes are small. It is unlikely that amitriptyline reduced pain by a clinically significant amount in these children with polyarticular JIA. These methods may be particularly suited to pilot studies and the study of rare illnesses.