A case study in comparing therapies involving informative drop-out, non-ignorable non-compliance and repeated measurements

• Published in: Statistics in medicine Vol. 24; no. 24; pp. 3773 - 3787
• Main Authors: Härkänen, T., Knekt, P., Virtala, E., Lindfors, O.
• Format: Journal Article
• Language: English
• Published: Chichester, UK John Wiley & Sons, Ltd 30-12-2005; Wiley Subscription Services, Inc
• Subjects: Adult; Bayesian analysis; Bayesian inference; Case studies; clinical trial; Clinical trials; Female; Finland; Humans; Male; non-ignorable missing data; non-ignorable non-compliance; Patient Compliance - statistics & numerical data; Psychotherapy; repeated measurements; Treatment Outcome; Finland
• ISSN: 0277-6715; 1097-0258
• DOI: 10.1002/sim.2409

Virtually no comparisons of different psychotherapies with long follow‐up times have been carried out until now. The Helsinki Psychotherapy Study is a randomized clinical trial, where patients were monitored for 12 months after the onset of study treatments, of which each lasted approximately 6 months. The patients' psychiatric status was measured at five pre‐determined time points during the follow‐up period. In general, the analyses of trials are complicated in cases where compliance with the given treatment is incomplete or the drop‐out from the follow‐up is non‐ignorable. In the present study, the quality of the treatment deviated from the protocol for some patients and some patients took auxiliary treatments which had similar effects to the study treatment during the study treatment or follow‐up period. This might have resulted in standard intention‐to‐treat analyses providing excessively conservative or liberal conclusions. Non‐compliance may have been non‐ignorable in some cases, so subject‐specific latent factors may have influenced the outcome both directly and indirectly via compliance behaviour. The most and least healthy patients are the most likely to dropout from the follow‐up a priori, so the missing data process is informative. The missing data can partly be augmented with surrogate information collected during interviews with patients who dropped out. A Bayesian hierarchical as‐treated model, which uses random‐effects‐based selection models to account for non‐ignorable missing data and non‐compliance, was compared with different mixed effects models. Copyright © 2005 John Wiley & Sons, Ltd.