Estimating a treatment effect in survival studies in which patients switch treatment.
For disease indications such as Acquired Immune Deficiency Syndrome (AIDS) and various cancers, randomization to a pure control treatment may be scientifically desirable but not ethically acceptable. Clinicians may insist that the experimental treatment be made available, at least as a rescue medication, for all patients in the control arm. A method for estimating a treatment effect in survival data from randomized clinical trials of this type is developed under an accelerated failure time model. This approach retains all patients in the groups to which they were randomized and is not based on an ad hoc subgroup analysis. By conditioning on having observed patient switch times, this method avoids the need to model patient switching patterns in the analysis. This new approach is evaluated using simulation studies, and is illustrated through analysing data from a Medical Research Council lung cancer trial.
Novartis Pharma AG, Lichtstrasse 35, CH-4056, Basel, Switzerland. mps@reading.ac.uk
Michael
M
Branson
John
J
Whitehead
D002289:Carcinoma, Non-Small-Cell Lung / Q000532:radiotherapy; D003198:Computer Simulation; D006801:Humans; D008175:Lung Neoplasms / Q000532:radiotherapy; D015233:Models, Statistical; D016032:Randomized Controlled Trials as Topic / Q000379:methods*; D016019:Survival Analysis