A tutorial on principal stratification-based sensitivity analysis: application to smoking cessation studies

Abstract

Background: One problem with assessing effects of smoking cessation interventions on withdrawal symptoms is that symptoms are affected by whether participants abstain from smoking during trials. Those who enter a randomized trial but do not change smoking behavior might not experience withdrawal-related symptoms.

Purpose: We present a tutorial of how one can use a principal stratification sensitivity analysis to account for abstinence in the estimation of smoking cessation intervention effects. The article is intended to introduce researchers to principal stratification and describe how they might implement the methods.

Methods: We provide a hypothetical example that demonstrates why estimating effects within observed abstention groups is problematic. We demonstrate how estimation of effects within groups defined by potential abstention that an individual would have in either arm of a study can provide meaningful inferences. We describe a sensitivity analysis method to estimate such effects, and use it to investigate effects of a combined behavioral and nicotine replacement therapy intervention on withdrawal symptoms in a female prisoner population.

Results: Overall, the intervention was found to reduce withdrawal symptoms but the effect was not statistically significant in the group that was observed to abstain. More importantly, the intervention was found to be highly effective in the group that would abstain regardless of intervention assignment. The effectiveness of the intervention in other potential abstinence strata depends on the sensitivity analysis assumptions.

Limitations: We make assumptions to narrow the range of our sensitivity analysis estimates. While appropriate in this situation, such assumptions might not be plausible in all situations.

Conclusions: A principal stratification sensitivity analysis provides a meaningful method of accounting for abstinence effects in the evaluation of smoking cessation interventions on withdrawal symptoms. Smoking researchers have previously recommended analyses in subgroups defined by observed abstention status in the evaluation of smoking cessation interventions. We believe that principal stratification analyses should replace such analyses as the preferred means of accounting for post-randomization abstinence effects in the evaluation of smoking cessation programs. Clinical Trials 2010; 7: 286-298. http://ctj.sagepub.com.

Figure 1

Historical depiction of intermediate variable (mediation) pathway.

Figure 2

Intervention effects in those who always and never abstain under various assumptions about the sensitivity parameters. The estimate of the effect is statistically significant in the region in which the 95% confidence interval does not cross 0. Legend: $$u=\frac{\text{Average intervention withdrawal score if in group that abstains with intervention only}}{\text{Average intervention withdrawal score if in group that always abstains}}$$ $$v=\frac{\text{Average control withdrawal score if in group that never abstains}}{\text{Average control withdrawal score if in group that abstains with intervention only}}$$

Figure 3

Intervention effect in those who abstain with the intervention only under various assumptions about the sensitivity parameters. The contour lines represent the point estimates and the shading represents the p-value. Legend: $$u=\frac{\text{Average intervention withdrawal score if in group that abstains with intervention only}}{\text{Average intervention withdrawal score if in group that always abstains}}$$ $$v=\frac{\text{Average control withdrawal score if in group that never abstains}}{\text{Average control withdrawal score if in group that abstains with intervention only}}$$