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Analyses of longitudinal and time-to-event data in a reandomized clinical trial in the presence of a lag time in the stablization of treatment

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Title: Analyses of longitudinal and time-to-event data in a reandomized clinical trial in the presence of a lag time in the stablization of treatment
Author: Yin, Eugenia Yu Hoi
Degree Master of Science - MSc
Program Statistics
Copyright Date: 2003
Abstract: Randomized controlled clinical trials (RCTs) are generally considered to be the best experimental setting for assessing new medical therapies. In medical research, the evaluation of RCTs is often based on two approaches: the commonly recommended intent-to-treat (ITT) analysis, and the more controversial per-protocol (PP) approach, which respectively attempt to assess the clinical effectiveness and the efficacy of a therapy. In the presence of a variable lag time in treatment stabilization following randomization, the two approaches may differ not only in their patient inclusion and exclusion criteria, but also in their definitions of the baseline time, from which follow-up is to be measured. In this work, ITT and PP analyses are applied to the evaluation of an eye pressure lowering therapy, in data from the Collaborative Normal Tension Glaucoma Study. In this study, the therapeutic intervention consisted of achieving a 30% reduction in intra-ocular pressure, and necessitated a lag time before the lowered pressure level became stable. This thesis includes longitudinal and survival analyses, based on measurements taken on some of the main variables in this study. In this case, the PP approach defines baseline time in the treated group as the time at which treatment stabilization has been achieved. It thus loses some of the advantages of randomization, and may suffer potential bias in parameter estimation as well as diminishing statistical power in testing the treatment effect. We investigate these potential problems through some simulation work. While the ITT and the PP approaches fail to account for the delay in treatment stabilization, we also develop a multistate model for survival analysis and a piecewise linear mixed effects (LME) model for longitudinal analysis, both of which address the lag time problem in assessing the effectiveness of the therapy. Finally, we consider a baseline-adjustment approach to match the control group to the delayed treatment group for an efficacy assessment of the therapy. These methods that account for the lag time are compared to the ITT and the PP approaches, and recommendations based on their performance in our study and their general applicability are given.
URI: http://hdl.handle.net/2429/14377
Series/Report no. UBC Retrospective Theses Digitization Project [http://www.library.ubc.ca/archives/retro_theses/]

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