Single patient (n-of-1) trials with binary treatment preference.
The use of a fully parametric Bayesian method for analysing single patient trials based on the notion of treatment 'preference' is described. This Bayesian hierarchical modelling approach allows for full parameter uncertainty, use of prior information and the modelling of individual and patient sub-group structures. It provides updated probabilistic results for individual patients, and groups of patients with the same medical condition, as they are sequentially enrolled into individualized trials using the same medication alternatives. Two clinically interpretable criteria for determining a patient's response are detailed and illustrated using data from a previously published paper under two different prior information scenarios.
Schluter
P J
PJ
Longitudinal Studies Unit, School of Population Health, The University of Queensland, Herston, Qld 4006, Australia. philip_schluter@hotmail.com
Ware
R S
RS
D000639:Amitriptyline / Q000627:therapeutic use; D018712:Analgesics, Non-Narcotic / Q000627:therapeutic use; D001499:Bayes Theorem; D005356:Fibromyalgia / Q000188:drug therapy; D006801:Humans; D015233:Models, Statistical; D009716:Numerical Analysis, Computer-Assisted; D016032:Randomized Controlled Trials as Topic / Q000379:methods*
D018712:Analgesics, Non-Narcotic; D000639:Amitriptyline