Background: There are currently approximately 3.5 million breast cancer survivors in the U.S. This number will continue to rise due to the medical and scientific advances that have improved diagnostic tools and standards of care for women treated for breast cancer. The increasing number of breast cancer survivors also means that the population at risk for cancer recurrence will increase. Cancer recurrence is defined as a cancer that was treated, reduced to undetectable levels, and later returned either locally, regionally, or distantly. After a recurrence diagnosis, patients’ experience reduced health outcomes and quality of life as well as the financial burden of additional treatments. Post-treatment surveillance strategies are critical for the early detection of recurrences so that interventions can be more effective at ensuring long term survival and quality of life. Currently, risk factors for breast cancer recurrence are not well understood in part due to limited population level data in cancer registries world-wide. The clinical endpoints that provide recurrence estimates are disease free survival (DFS), relapse free survival (RFS), and time to recurrence (TTR). Studies that provide recurrence estimates are limited to clinical trials (which lack diversity and represent less than 5% of cancer patients) and prospective cohorts that follow patients for a defined number of years. Currently, population-based cancer registries in North America do not collect recurrence data from patients that would allow the calculation of DFS, RFS, and TTR. The absence of population level data has limited the understanding of cancer patients’ individual risks and evidence-based recommendations for recurrence prevention strategies. Moreover, recurrence data on cancers with long term latency (greater than 5-10 years) such as estrogen receptor positive breast cancer are limited.Purpose: We seek to identify which data elements and surveillance strategies are collected for recurrence data in breast cancer clinical trials. Our long-term goal is to implement these data elements into the Surveillance, Epidemiology, and End Results (SEER) program to facilitate the calculation of breast cancer recurrence estimates at the U.S. population level.Methods: We performed a systematic literature review evaluating phase II-IV clinical trials, their reported clinical outcomes, surveillance strategies, and their diagnostic tests that confirm recurrence. We used PubMed, clinicaltrials.gov, EMBASE, and the Cochrane Library for search terms “recurrence”, “relapse”, “recurrence free survival”, “surgery”, “adjuvant therapy” in breast cancer for our literature search. Inclusion criteria included clinical trials with published results, trials that compared outcomes of surgical resections, surgery with adjuvant treatments, or multiple adjuvant treatments. We included trials that provided DFS, RFS, TTR, recurrence rate, recurrence free interval, progression free survival, and time to progression. We excluded trials that did not provide recurrence estimates and those that performed recurrence modeling.Conclusion: From our review, we identified data elements and recurrence estimates for breast cancer that are collected in clinical trials but are not included in North American registries. New data elements need to be included in North American cancer registries to calculate population-based estimates for recurrence.

Citation Format: Esmeralda Ramirez-Pena, Sarah Hussey, Serban Negoita, Brandy Heckman-Stoddard. Learning from breast cancer clinical trials how to capture recurrence estimates for North American cancer registries: A systematic review [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PS7-37.