The effect of covariate adjustment for baseline severity in acute stroke clinicaltrials with responder analysis outcomes

Abstract

Abstract Background Traditionally in acute stroke clinical trials, the primary clinical outcomeemployed is a dichotomized modified Rankin Scale (mRS). New statisticalmethods, such as responder analysis, are being used in stroke studies toaddress the concern that baseline prognostic variables, such as strokeseverity, impact the likelihood of a successful outcome. Responder analysisallows the definition of success to vary according to baseline prognosticvariables, producing a more clinically relevant insight into the actualeffect of investigational treatments. It is unclear whether or notstatistical analyses should adjust for prognostic variables when responderanalysis is used, as the outcome already takes these prognostic variablesinto account. This research aims to investigate the effect of covariateadjustment in the responder analysis framework in order to determine theappropriate analytic method. Methods Using a current stroke clinical trial and its pilot studies to guidesimulation parameters, 1,000 clinical trials were simulated at varyingsample sizes under several treatment effects to assess power and type Ierror. Covariate-adjusted and unadjusted logistic regressions were used toestimate the treatment effect under each scenario. In the case ofcovariate-adjusted logistic regression, the trichotomized National Instituteof Health Stroke Scale (NIHSS) was used in adjustment. Results Under various treatment effect settings, the operating characteristics of theunadjusted and adjusted analyses do not substantially differ. Power and typeI error are preserved for both the unadjusted and adjusted analyses. Conclusions Our results suggest that, under the given treatment effect scenarios, thedecision whether or not to adjust for baseline severity when using aresponder analysis outcome should be guided by the needs of the study, astype I error rates and power do not appear to vary largely between themethods. These findings are applicable to stroke trials which use the mRSfor the primary outcome, but also provide a broader insight into theanalysis of binary outcomes that are defined based on baseline prognosticvariables. Trial registration This research is part of the Stroke Hyperglycemia Insulin Network Effort(SHINE) trial, Identification Number NCT01369069.