OBJECTIVES: Unlike randomized clinical trials (RCTs), prospective observational studies typically address objectives rather than test specific hypotheses. Nevertheless, a minimum sample size is required to allow for adequate exploration of the objectives, and estimation of sample size is an important part of the planning process for these studies. Sample size estimation for observational studies is more complex than sample size calculation for RCTs; subgroup analyses and modeling are to be expected in observational studies, and these analysis methods may require more assumptions and larger sample sizes. At the same time, sample sizes must not be so large as to raise concern that the study includes an unnecessarily high number of sites and patients.  This is particularly true for product registries where a specific product is being observed. METHODS: This poster will provide examples/case studies of sample size estimations performed for a variety of prospective observational studies and objectives.  These case studies will focus on the following methods: 1) Incorporation of planned propensity score matching to support comparisons of cohorts or subgroups; 2) Investigation of factors that influence outcomes within subgroups; 3) Estimation expressed as number of person-years rather than persons; and 4) Re-estimation of sample size based on interim results. RESULTS AND CONCLUSIONS: These methods illustrate the difference between sample size estimation in prospective observational studies and sample size calculation in randomized clinical trials.