Understanding decision making for preventive interventions: The unruptured intracranial aneurysm example

Abstract

Background

Decision making for preventive interventions in asymptomatic patients, such as the treatment of incidental intracranial aneurysms, is eminently uncertain and at risk of over-treatment. One approach suggests that the weighing of the natural risk of the disease against the risk of intervention should be replaced by a comparison of outcomes measured as expected quality-adjusted life-years survival.

Methods

We review the problems of over-diagnosis and over-treatment and how prognostic studies can help address the clinical uncertainty. We examine and compare the assumptions that underlie the mathematical transformations that are involved in the so-called outcome-based approach with the risk-based approach when they are both derived from observational data. Finally, we propose a more pragmatic approach.

Results

Both risk-based and outcome-based models depend on two strong assumptions: exchangeability of patients selected to be observed and patients selected to be treated (in other words ignorability of treatment assignment), and ii) dominance of time-to-event data (the only thing pertinent for decision making is the time to the first event in the patient’s history). The outcome-based approach needs an additional assumption: fatality (once a patient suffers a poor outcome from an event, recovery is impossible). These three theoretical assumptions are rarely verified in practice.

Conclusion

Clinical decision-making based on observational data relies on unrealistic assumptions. Clinical practice should instead be guided by conducting pragmatic clinical trials.