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How many patients do you need? Investigating trial designs for anti-seizure treatment in acute brain injury patients.
Parikh, Harsh; Sun, Haoqi; Amerineni, Rajesh; Rosenthal, Eric S; Volfovsky, Alexander; Rudin, Cynthia; Westover, M Brandon; Zafar, Sahar F.
  • Parikh H; Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA.
  • Sun H; Department of Neurology, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA.
  • Amerineni R; Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts, USA.
  • Rosenthal ES; Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts, USA.
  • Volfovsky A; Department of Computer Science, Duke University, Duke, North Carolina, USA.
  • Rudin C; Department of Computer Science, Duke University, Duke, North Carolina, USA.
  • Westover MB; Department of Neurology, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA.
  • Zafar SF; Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts, USA.
Ann Clin Transl Neurol ; 11(7): 1681-1690, 2024 Jul.
Article en En | MEDLINE | ID: mdl-38867375
ABSTRACT
BACKGROUND/

OBJECTIVES:

Epileptiform activity (EA), including seizures and periodic patterns, worsens outcomes in patients with acute brain injuries (e.g., aneurysmal subarachnoid hemorrhage [aSAH]). Randomized control trials (RCTs) assessing anti-seizure interventions are needed. Due to scant drug efficacy data and ethical reservations with placebo utilization, and complex physiology of acute brain injury, RCTs are lacking or hindered by design constraints. We used a pharmacological model-guided simulator to design and determine the feasibility of RCTs evaluating EA treatment.

METHODS:

In a single-center cohort of adults (age >18) with aSAH and EA, we employed a mechanistic pharmacokinetic-pharmacodynamic framework to model treatment response using observational data. We subsequently simulated RCTs for levetiracetam and propofol, each with three treatment arms mirroring clinical practice and an additional placebo arm. Using our framework, we simulated EA trajectories across treatment arms. We predicted discharge modified Rankin Scale as a function of baseline covariates, EA burden, and drug doses using a double machine learning model learned from observational data. Differences in outcomes across arms were used to estimate the required sample size.

RESULTS:

Sample sizes ranged from 500 for levetiracetam 7 mg/kg versus placebo, to >4000 for levetiracetam 15 versus 7 mg/kg to achieve 80% power (5% type I error). For propofol 1 mg/kg/h versus placebo, 1200 participants were needed. Simulations comparing propofol at varying doses did not reach 80% power even at samples >1200.

CONCLUSIONS:

Our simulations using drug efficacy show sample sizes are infeasible, even for potentially unethical placebo-control trials. We highlight the strength of simulations with observational data to inform the null hypotheses and propose use of this simulation-based RCT paradigm to assess the feasibility of future trials of anti-seizure treatment in acute brain injury.
Asunto(s)

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Convulsiones / Levetiracetam / Anticonvulsivantes Límite: Adult / Aged / Female / Humans / Male / Middle aged Idioma: En Año: 2024 Tipo del documento: Article

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Convulsiones / Levetiracetam / Anticonvulsivantes Límite: Adult / Aged / Female / Humans / Male / Middle aged Idioma: En Año: 2024 Tipo del documento: Article