Combining single patient (N-of-1) trials to estimate population treatment effects & to evaluate individual patient responses to treatment

When treating individual patients, physicians may face difficulties

using the evidence from center-based randomized control trials

(RCTs) due to limitations in these studies generalizability.

Therefore, they often perform their own “informal” tests of

treatment effectiveness. Single patient (“N-of-1”) trials

provide a structured design for more rigorous assessment of

medical treatments of chronic diseases, but are applied only

to the index patient. We present a hierarchical Bayesian

random effects model to combine N-of-1 studies to obtain an

estimate of treatment effectiveness for the population and to

use this population information to aid in the evaluation of an

individual patient’s trial results. The model’s treatment

effect estimates are adjustments between the population

estimate and the individual’s observed results. This

adjustment is based upon the within-patient and

between-patient heterogeneity. We demonstrate this

patient-focused method using published data from 23 N-of-1

trial results comparing amitriptyline and placebo for the

treatment of fibromyalgia.

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