The use of outcome information in shared decision-making about surveillance after breast cancer

Thanks to major advances in early detection and treatment, the survival of people with breast cancer has significantly increased in recent decades. In addition, the incidence of breast cancer is rising. These developments mean an increasing number of people who have had
breast cancer (prevalence) and that make use of follow-up care after curative treatment. Follow-up after breast cancer consists of aftercare and post-treatment surveillance. Aftercare includes providing information, guidance, detecting immediate or late effects of disease and treatment, addressing these complaints and symptoms, and attention for social consequences. Post-treatment surveillance focuses on detecting new manifestations of the treated breast cancer or new associated malignancies. Until now, the surveillance for all breast cancer patients was ‘one-size-fits-all’: annual imaging (mammography or MRI) and a physical examination for at least five years after surgery. However, research shows that the risks of breast cancer recurrence differ per patient and that there are possibilities for personalising surveillance since the intensity of surveillance can safely be decreased for patients with low risks for recurrences.

The process of shared decision-making (SDM) can support the delivery of value-based health care (VBHC) as it can strengthen the position of patients by tailoring information to patient needs and by improving engagement and outcomes, whilst reducing costs and health care burden by avoiding unnecessary treatments or care procedures that do not align with patients’ goals and values. SDM can be supported using patient decision aids (PtDAs) that provide structured information and help patients to consider and prioritise their preferences and choices. PtDAs can be even more valuable when they contain personalised information about outcomes of care (so-called ‘outcome information’). For SDM about personalised surveillance after breast cancer it may be beneficial to develop a PtDA which contains outcome information regarding the individual risks for recurrences. These risks can be estimated using the INFLUENCE 2.0-nomogram. 1