Gynecologic Oncology Reports (Apr 2022)
“It was a no-brainer”: A qualitative study of factors driving previvors’ decision-making when considering risk-reducing salpingectomy with delayed oophorectomy
Abstract
Objective: Previvors are becoming more aware of the option of risk-reducing salpingectomy with delayed oophorectomy (RRS-DO) to mitigate their risk of ovarian cancer. In this qualitative study, we explored the clinical and non-clinical factors that impacted previvors’ decision-making to pursue RRS-DO as a risk reduction strategy. Methods: Semi-structured telephone interviews were conducted with previvors and transcribed verbatim. Using ATLAS.ti® software, two primary investigators interpreted data through thematic analysis. After coding four interviews, the investigators discussed discrepancies between codes with a moderator and resolved and refined code. The investigators applied the universal codebook to all interviews and revised the codebook using an iterative approach. Examining codes within and across interviews allowed for major themes and patterns to emerge. Results: Interviews were conducted with seventeen previvors (ages 31–46). 6 (25%) previvors had a BRCA1 mutation, 7 (41%), a BRCA2 mutation, 3 (13%), a Lynch-related mutation, and 1 (6%), other (MUTYH mutation). At the time of interview, 12 previvors (71%) were planning (6) or had undergone (6) RRS-DO, 4 (23%) were planning (1) or had undergone (3) risk reducing salpingo-oophorectomy (RRSO), and 1 (6%) was undecided. Three major themes emerged: motivating factors for selecting surgical risk reduction option, barriers complicating surgical decision-making, and facilitating factors for surgical decision-making. RRS-DO-focused previvors prioritized avoiding menopause, and they also emphasized that self-advocacy and building rapport with providers facilitated their decision-making. Conclusion: By understanding previvors’ priorities and experiences, physicians can better partner with previvors as they navigate their ovarian cancer risk reduction journey. This will ultimately optimize shared decision-making.