title: The Choice of Analytical Strategies in Inverse-Probability-of-Treatment-Weighted Analysis: A Simulation Study.
abstract: We sought to explore the impact of intention to treat and complex treatment use assumptions made during weight construction on the validity and precision of estimates derived from inverse-probability-of-treatment-weighted analysis. We simulated data assuming a nonexperimental design that attempted to quantify the effect of statin on lowering low-density lipoprotein cholesterol. We created 324 scenarios by varying parameter values (effect size, sample size, adherence level, probability of treatment initiation, associations between low-density lipoprotein cholesterol and treatment initiation and continuation). Four analytical approaches were used: 1) assuming intention to treat; 2) assuming complex mechanisms of treatment use; 3) assuming a simple mechanism of treatment use; and 4) assuming invariant confounders. With a continuous outcome, estimates assuming intention to treat were biased toward the null when there were nonnull treatment effect and nonadherence after treatment initiation. For each 1% decrease in the proportion of patients staying on treatment after initiation, the bias in estimated average treatment effect increased by 1%. Inverse-probability-of-treatment-weighted analyses that took into account the complex mechanisms of treatment use generated approximately unbiased estimates. Studies estimating the actual effect of a time-varying treatment need to consider the complex mechanisms of treatment use during weight construction.
authors: Shibing
authors: S
authors: Yang
authors: Juan
authors: J
authors: Lu
authors: Charles B
authors: CB
authors: Eaton
authors: Spencer
authors: S
authors: Harpe
authors: Kate L
authors: KL
authors: Lapane
mesh_terms: D003198:Computer Simulation; D016001:Confidence Intervals; D050171:Dyslipidemias / Q000188:drug therapy* / Q000453:epidemiology; D005260:Female; D006801:Humans; D000960:Hypolipidemic Agents / Q000627:therapeutic use*; D057194:Intention to Treat Analysis / Q000379:methods*; D008297:Male
chemical_list: D000960:Hypolipidemic Agents
keywords: as-treated analysis; data simulation; intention to treat; marginal structural models