A threshold causal model for clinical trials with departures from intended treatment.
Randomized clinical trials often are planned to study a specific intervention. However, the collection of data on treatment actually received often reveals variable levels of treatment exposure (or 'dose') across subjects, due to non-compliance or other reasons. This paper presents a new method, using such 'dose' data as well as control group responses, to assess a causal dose-response relationship. The specific model utilizes a threshold function and incorporates a random effect term to allow for heterogeneous treatment responses among subjects. Further modelling of the random effects allows for reduction of error variance and control for potential confounders. The threshold dose is estimated using a residual variance criterion based on a transformed model. Estimates of standard errors and confidence intervals are obtained using a bootstrap procedure. The method is applied to data from an AIDS clinical trial. A simulation study demonstrates the adequacy of the threshold estimates for particular sample sizes and error variances. The limitations of this essentially exploratory method, as well as some possible extensions, are discussed. Published in 1999 by John Wiley & Sons, Ltd. This article is a US Government Work and is in the public domain in the United States.
Department of Epidemiology and Biostatistics, School of Medicine, BRB-G19, Case Western Reserve University, 10900 Euclid Avenue, Cleveland, OH 44106-4945, USA. jma13@po.cwru.edu
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Albert
D018791:CD4 Lymphocyte Count; D015984:Causality; D003198:Computer Simulation; D004305:Dose-Response Relationship, Drug; D015987:Effect Modifier, Epidemiologic; D015658:HIV Infections / Q000188:drug therapy; D006801:Humans; D007376:Interleukin-2 / Q000627:therapeutic use; D015233:Models, Statistical; D010349:Patient Compliance; D016032:Randomized Controlled Trials as Topic / Q000706:statistics & numerical data*; D012044:Regression Analysis
D007376:Interleukin-2