Optimizing antiseizure medication deprescribing decisions across the lifespan by integrating seizure risk prediction and patient preferences towards individualized net-benefit assessment

PROJECT SUMMARY / ABSTRACT Objectives. A critical need remains for comprehensive, personalized strategies for considering deprescribing across the lifespan. My long-term goal is to improve pharmacologic stewardship of neurologic medications to promote healthy aging using decision science techniques. This application’s objective is to

collect preliminary data for a future large, multicenter RCT that will capture how the absolute effect of discontinuation changes across key subgroups such as evolving healthcare preferences across life (SA1) and different levels of seizure risk (SA2). Aims/Methods. First, we will define how patient preferences influencing ASM decisions change across

the lifespan. We will survey ~300 patients with epilepsy at 4 sites, with stratified sampling across ages. The survey will include best-worst scaling ranking and time trade-off rating exercises, plus more general questions assessing willingness to enroll in our future deprescribing trial. A deeper understanding of how patients rank

the importance of seizure relapse versus other factors would more closely align clinicians with patient values, and therefore enhance our ability to deliver patient-centered values-concordant care. Second, we will improve post-deprescribing seizure prediction. We will update the prior individualized post-discontinuation seizure risk

calculator by adding modern adult data and statistical techniques for improved out-of-sample predictions in 3,147 international patients. We will then execute decision analytic models to assess which patients might experience theoretical net benefit versus harm from deprescribing ASMs and the effects of different population-

wide deprescribing strategies. This modeling would improve clinicians’ ability to deliver personalized medicine, plus facilitate our future trial by developing analytic procedures (the future trial will assess how low seizure risk must be until deprescribing exerts predicted benefit on quality of life) and justifying which patients to enroll.

Third, we will refine our trial protocol and test procedures at 3 sites for our future planned trial in which we will randomize seizure-free patients to deprescribing ASMs. This work will result in more personalized evidence- based recommendations to tailor ASM deprescribing decisions to a person’s risk, healthcare preferences, and

stage of life. This will lead to many R01’s including but not limited to applying these techniques to other deprescribing decisions particularly as they pertain to neurological medications used by older patients. Candidate. Through expert mentorship, advanced coursework, and the intellectually rich environment

of the University of Michigan, this award will develop Dr Terman into a leader using decision sciences synthesizing patient preferences with risk prediction, and leading clinical trials, aimed at rational (de)prescribing of central nervous system agents tailored to how preferences and risk change across life.