Improving traditional intention-to-treat analyses: a new approach.
BACKGROUND
Drop-out, often accompanied by treatment non-compliance, is common in psychiatric trials. Methodologists have criticized the use of a traditional intention-to-treat (ITT) approach in such cases, and have proposed alternative methods. We set out to describe and assess methods for estimation of a treatment effect when the trial is 'broken'.


METHODS
We describe a stratified method of moments (SMOM) estimator that assesses treatment effects on subjects who are willing to comply with all the treatments under study. A simulation study and a re-analysis of data from an antipsychotics trial are used to compare SMOM to ITT, as-treated, and adequate estimators.


RESULTS
The new estimator retains good statistical properties under different levels of non-compliance and drop-out mechanisms. The re-analysis indicates that SMOM yields more precise results.


CONCLUSIONS
Although the traditional ITT approach provides a valid method to estimate treatment effects, it can be biased in the presence of treatment non-compliance and drop-out. It is critical that researchers move beyond traditional approaches when trials are broken. A key first step is to consider non-compliance and drop-out as two independent phenomena, tracking and reporting rates separately.
Horvitz-Lennon
Marcela
M
Department of Psychiatry, University of Pittsburgh, PA 15213, USA. horvitzlennonmv@upmc.edu
O'Malley
A James
AJ
Frank
Richard G
RG
Normand
Sharon-Lise T
SL
D014150:Antipsychotic Agents / Q000627:therapeutic use; D002986:Clinical Trials as Topic / Q000592:standards*; D006801:Humans; D001523:Mental Disorders / Q000628:therapy*; D010349:Patient Compliance; D010352:Patient Dropouts; D015203:Reproducibility of Results; D016896:Treatment Outcome
D014150:Antipsychotic Agents