Oral Presentation Clinical Oncology Society of Australia Annual Scientific Meeting 2023

Supporting informed decision making in the fertility preservation process including work on fertility decision aids and the FORECAST study (#10)

Michelle Peate 1 2 , Y Jayasinghe 1 2 3 4 , A Roman 3 5 , L Song 2 6 , Z Edib 1 2 3
  1. Department of Obstetrics and Gynaecology, , University of Melbourne, Melbourne, VIC
  2. FoRECAsT Consortium, VIC
  3. Royal Women's Hospital, Parkville, VIC, Australia
  4. Australian Fertility Decision Aid Collaborative group, VIC
  5. Endometrial Decision Aid team, VIC
  6. School of Computing and Information Systems, Faculty of Engineering and IT, University of Melbourne, VIC

Background: Infertility is a common consequence of cancer and its treatment for reproductive aged patients, and is a key concern for many, with negative long-term outcome. Fertility preservation may be an option, but for optimal results, it should be discussed prior commencement of treatment. At this high stress time, the decision to undertake fertility preservation is complex, and patients need support. There are several ways we can provide this support.

Aims: To present the evidence on different tools to support informed oncofertility decision-making.

Methods: Multiple studies will be described, including data from qualitative, cross-sectional, clinical trial, and meta-analyses of an international databank.

Results: The team have been involved in the development of four different oncofertility decision aids, at different stages of development, for: women with breast cancer, women with endometrial cancer, and parents of children with cancer. Oncofertility decision aids are acceptable to patients, reduce decisional conflict and regret, and improve the quality of decision-making around fertility and fertility preservation and patient satisfaction. They also are well accepted by clinicians.

We are also in the process of developing a web-based tool (FoRECAsT: infertility after cancer predictor) to provide an individualised risk of developing ovarian function decline and likely fertility outcomes for young breast cancer patients. The risk prediction models have been developed based on a databank of 24,678 individual fertility records of pre-menopausal women across 19 clinical centres in Australia, the United Kingdom, the United States of America, Hong Kong, France, Belgium, Denmark, Italy, and International Trial Groups. The development of this tool will be described, as well as the original and imputed model prediction models.

Conclusions: Providing patients with tools to support decision-making can improve their experience and lead to better outcomes.