Stroke. 2023 Jan 5. doi: 10.1161/STROKEAHA.122.040638. Online ahead of print.
The Stroke Preclinical Assessment Network (SPAN) is a multicenter preclinical trial platform using rodent models of transient focal cerebral ischemia to address translational failure in experimental stroke. In addition to centralized randomization and blinding and large samples, SPAN aimed to introduce heterogeneity to simulate the heterogeneity embodied in clinical trials for robust conclusions. Here, we report the heterogeneity introduced by allowing the 6 SPAN laboratories to vary most of the biological and experimental model variables and the impact of this heterogeneity on middle cerebral artery occlusion (MCAo) performance. We included the modified intention-to-treat population of the control mouse cohort of the first SPAN trial (n=421) and examined the biological and procedural independent variables and their covariance. We then determined their impact on the dependent variables cerebral blood flow drop during MCAo, time to achieve MCAo, and total anesthesia duration using multivariable analyses. We found heterogeneity in biological and procedural independent variables introduced mainly by the site. Consequently, all dependent variables also showed heterogeneity among the sites. Multivariable analyses with the site as a random effect variable revealed filament choice as an independent predictor of cerebral blood flow drop after MCAo. Comorbidity, sex, use of laser Doppler flow to monitor cerebral blood flow, days after trial onset, and maintaining anesthesia throughout the MCAo emerged as independent predictors of time to MCAo. Total anesthesia duration was predicted by most independent variables. We present with high granularity the heterogeneity introduced by the biological and model selections by the testing sites in the first trial of cerebroprotection in rodent transient filament MCAo by SPAN. Rather than trying to homogenize all variables across all sites, we embraced the heterogeneity to better approximate clinical trials. Awareness of the heterogeneity, its sources, and how it impacts the study performance may further improve the study design and statistical modeling for future multicenter preclinical trials.