Adjusting treatment comparisons to account for non-randomized interventions: an example from an angina trial

Abstract

In a clinical trial where some subjects receive one or more non-randomized interventions during follow-up, primary interest is in the effect of the overall treatment strategies as implemented, but it may also be of interest to adjust treatment comparisons for non-randomized interventions. We consider non-randomized interventions, especially surgical procedures, which only occur when the outcome would otherwise have been poor. Focusing on an outcome measured repeatedly over time, we describe the variety of questions that may be addressed by an adjusted analysis. The adjusted analyses involve new outcome variables defined in terms of the observed outcomes and the history of non-randomized intervention. We also show how to check the assumption that the outcome would otherwise have been poor, and how to do a sensitivity analysis. We apply these methods to a clinical trial comparing initial angioplasty with medical management in patients with angina. We find that the initial benefit of a single angioplasty in reducing angina tends to disappear with time, but a policy of additional interventions as required yields a benefit that is maintained over 4 years. Such methods may be of interest to many pragmatic randomized trials in which the effects of the initial randomized treatments and the effects of the overall treatment strategies as implemented are both of interest.