摘要：Background: Around one-third of breast cancers diagnosed every year in the UK are in women aged ≥70 years. However, there are currently no decision support interventions (DESIs) for older women who have a choice between primary endocrine therapy and surgery followed by adjuvant endocrine therapy (surgery+endocrine therapy), or who can choose whether or not to have chemotherapy following surgery. There is also little evidence-based guidance specifically on the management of these older patients. A large UK cohort study is currently underway to address this lack of evidence and to develop two DESIs to facilitate shared decision-making with older women about breast cancer treatments. Here, we present the development and initial testing of these two DESIs. Methods: An initial prototype DESI was developed for the choice of primary endocrine therapy or surgery+endocrine therapy. Semi-structured interviews with healthy volunteers and patients explored DESI acceptability, usability, and utility. A framework approach was used for analysis. A second DESI for the choice of having chemotherapy or not was subsequently developed based on more focused development and testing. Results: Participants (n=22, aged 75–94 years, 64% healthy volunteers, 36% patients) found the primary endocrine therapy / surgery+endocrine therapy DESI acceptable, and contributed to improved wording and illustrations to address misunderstandings. The chemotherapy DESI (tested with 14 participants, aged 70–87 years, 57% healthy volunteers, 43% patients) was mostly understandable, however, suggestions for rewording sections were made. Most participants considered the DESIs helpful, but highlighted the importance of complementary discussions with clinicians. Conclusion: It was possible to use a template DESI to efficiently create a second prototype for a different treatment option (chemotherapy). Both DESIs were acceptable and considered helpful to support/augment consultations. Development of acceptable additional DESIs for similar target populations using simplified methods may be an efficient way to develop future DESIs. Further research is needed to test the effectiveness of the DESIs.
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