Missing outcome data management in acute stroke trials testing iv thrombolytics. Is there risk of bias?

We considered 9657 patients from eight of the studies included in VISTA, 3034 (31%) thrombolysed. Missing data replacement by LOCF with analysis by dichotomisation gave the highest estimate of thrombolysis influence. Imputing while increasing the burden of missing data progressively raised the odds ratios estimates, though thresholds for overestimation were 10% for LOCF; 20% for multiple imputation.Discussion: Replacing missing outcome data tended to overestimate differences of thrombolysed versus non-thrombolysed patients, but had minimal impact below a 10% burden of missing data.Conclusion: In the specific context of acute stroke trials testing iv thrombolytics, replacing missing data by carrying forward the last observation tended to overestimate treatment odds ratios more than multiple imputation.