Abstract BACKGROUND Incidence, prevalence, and survival are population-based cancer statistics that describe cancer burden. The National Cancer Institute’s Comprehensive Oncology Network Evaluating Rare CNS Tumors (NCI-CONNECT) specializes in research of 12 rare CNS tumor types to improve approaches to care and treatment. These tumors include atypical teratoid/rhabdoid tumors, brainstem and midline glioma, choroid plexus tumors, ependymoma, high grade meningioma, gliomatosis cerebri, medulloblastoma, oligodendroglioma/anaplastic oligodendroglioma, pineal region tumors, pleomorphic xanthoastrocytoma, CNS embryonal tumors, not elsewhere classified (NEC)/not otherwise specified (NOS), and primary CNS sarcoma. This study aimed to update incidence, prevalence, and survival statistics for these tumors. METHODS The Central Brain Tumor Registry of the United States (CBTRUS) database, a combined dataset of CDC’s National Program of Cancer Registries (NPCR) and NCI’s Surveillance, Epidemiology and End RESULTS (SEER) data, was used to calculate average annual age-adjusted incidence rates (AAAIR) per 100,000 population overall and by sex, race-ethnicity, and age (2008-2019). NPCR data were used to calculate relative survival (RS) estimates (2008-2018). Prevalence on December 31, 2019 was estimated using annual age-specific incidence and survival from CBTRUS and SEER, respectively. RESULTS AAAIR was 1.51 per 100,000 for these tumors combined, with highest incidence in ependymomas (AAAIR=0.41/100,000). Most tumor types were more common in males, adults (ages 40+ years) or children ages < 15 years, and non-Hispanic White individuals. Ependymomas were most prevalent (19,339 cases) followed by oligodendrogliomas (15,070 cases). RS for all subtypes combined at 1-, 5-, and 10-years was 86.6%, 71.9%, and 65.3%, respectively. Ependymomas had the highest RS (5-years=90.6%) and primary CNS sarcomas had the lowest RS (5-years=7.7%). CONCLUSIONS Incidence, prevalence, and survival patterns for these 12 selected rare cancer subtypes varied significantly by type. Population-based data are critical to guiding effective design of and accrual expectations for clinical trials in rare cancers.