Mediators of First- Versus Second-generation Antipsychotic-related Mortality in Older Adults

Abstract

Background: Observational studies of older adults showed higher mortality for first-generation antipsychotics than their second- generation counterparts, which led to US Food and Drug Administration warnings, but the actual mechanisms involved remain unclear.

Methods: A cohort of 9,060 initiators of first-generation antipsychotics and 17,137 of second-generation antipsychotics enrolled in New Jersey and Pennsylvania Medicare were followed for 180 days. Medical events were assessed using diagnostic and procedure codes on inpatient billing claims. For the individual and joint set of medical events (mediators), we estimated the total, direct, and indirect effects of antipsychotic type (first versus second generation) on mortality on the risk ratio scale and the proportion mediated on the risk difference scale, obtaining 95% confidence intervals through bootstrapping. We performed bias analyses for false-negative mediator misclassification in claims data, with sensitivity ranging from 0.25 to 0.75.

Results: There were 3,199 deaths (outcomes), 862 cardiovascular events, 675 infectious events, and 491 hip fractures (potential mediators). Mortality was higher for first- than second-generation antipsychotic initiators (adjusted risk ratio: 1.14; 95% confidence interval: 1.06, 1.22). In naïve analyses, that ignored potential misclassification, less than 4% of this difference was explained by any particular medical event. In bias analyses, the proportion mediated ranged from 6% to 16% for stroke, 3% to 9% for ventricular arrhythmia, 3% to 11% for myocardial infarction, 0% venous thromboembolism, 3% to 9% for pneumonia, 0% to 1% for other bacterial infection, and 1% to 3% for hip fracture.

Conclusions: Acute cardiovascular events and pneumonia may explain part of the mortality difference between first- and second-generation antipsychotic initiators in this analysis.

Figure 1

Bias analysis for false-negative medical event misclassification. Each panel presents the results for a specific medical event: the adjusted proportion-mediated (y-axis) under various bias scenarios characterized by sensitivity among those survived (Sn_Y=0; x-axis) and among those who died (Sn_Y=1; symbols), assuming perfect specificity. The nature of bias due to misclassification can be observed from the graph: if it were driven by non-differential misclassification, the lines for all symbols would be identical; the influence of misclassification among those who died is reflected by a line’s slope, and the influence of misclassification among those who survived is reflected in the degree of vertical separation between the lines.