Cancer is a powerful paradigm for how progress in precision medicine will improve human health. For no other condition have there been greater advances in treatments or in the precision of the evaluative test algorithms directing their use. It will be in cancer that we will learn most about how to do more for patients by doing less. Indeed, an essential mission of precision medicine today is to target treatment in patients to reduce harm while achieving better survival benefit. This dynamic treatment context obligates population research to inform interventions by tracking trends in treatment and investigating evolving developments that impact individualized cancer management and patient experiences and outcomes. Our interdisciplinary research team has married clinical, behavioral, and decision sciences within a compelling scientific framework to close the gaps between findings in the social sciences and applications in community oncology practice. The scientific framework of our Program (the Figure) is that results from population-based oncology research can identify actionable targets and inform strategies for interventions that will maximize the impact of precision oncology and patient-centered care to reduce the cancer burden.

The CanSORT Program has uniquely contributed to both oncology population and implementation sciences. We have built an innovative vision and strategy for team infrastructure including partnerships with patients and their attending cancer doctors in the community, physician organizations, academics, SEER regional and national leaders, industry, and the NCI Community Oncology Research Program trial network. We leveraged these relationships to build and evaluate innovative approaches and methodologies in population oncology sciences.  We have implemented strategies to increase technical capacities in population oncology through a growing data infrastructure for research and leveraged it to produce high impact results. Our population-based data infrastructure is an important model for vitalizing the SEER program and a foundation for research for many years to come. We have developed, evaluated, and disseminated many measures including multi-item scales of patient-reported experiences and clinician attitudes about treatment and their perspectives about encounter communication. We have enhanced rigor of the statistical approaches to common problems in population-based survey research including addressing measurement errors and bias from patient selection into testing and treatment, handling missing data, examining mediation, and estimating latent traits. We have made substantial innovative contributions to methodologies in intervention science. We have developed novel tools and strategies to integrate shared learning systems between patients and doctors into practice with a keen eye on scalability. Finally, we deploy innovative strategies to disseminate the new knowledge and products emanating from the Program into practice. We will continue to translate findings from the CanSORT Program’s population-based and interventional research to create the next generation of health communication tools and strategies to improve breast cancer care. We apply a Learning Health System framework to facilitate the adoption of the Program’s research products into future research and practice.

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