Abstract 86: Understanding Patterns Of Missingness In Acute Ischemic Stroke Trials: A Secondary Analysis Of Pooled Patient-level Follow-up Data.

Background: Understanding the magnitude and causes of missing data is crucial to ensuring scientific integrity of clinical trials. Missing data threaten statistical and ecological validity, as results will only generalize to those who remain represented in the sample. Goal: Identify factors associated with loss at follow-up in acute ischemic stroke trials. Methods: We harmonized patient-level data from multiple NIH-funded acute ischemic stroke trials including NINDS IV-tPA, ALIAS part 2, SHINE, FAST-MAG, IMS-III, POINT, and DEFUSE 3, all of which had a 90-day study outcome. The primary outcome was the proportion of missing modified Rankin Scale (mRS) scores at 90 days. We compared patients with and without a 90-day mRS score among a variety of baseline patient characteristics. Results: Among 9580 subjects, 459 (4.8%) were missing their 90-day mRS. Age and race were associated with missingness. Compared to those with complete data, participants with missing data were younger (62 vs 66 years, p<0.001). Non-Hispanic Black participants represented 18.8% of those with complete data, but 25.3% of those with missing data (p=0.001). History of cardiac disease —atrial fibrillation, coronary artery disease, myocardial infarction—and better baseline NIHSS score were associated less missingness (p’s≤.002 and p<.001, respectively). History of stroke/TIA, however, was positively associated with missingness (50.3% vs. 35.4%, p<.001). Conclusion: Bias due to missingness is an important consideration for all clinical trials, including genetic studies. Disparities in the availability of genetic data compounded by missing phenotypic data creates a twofold disadvantage for underrepresented groups. Long term, we need to understand the biomedical and sociological causes of these associations and develop recruitment and retention strategies to ensure the generalizability of trial results.