Oral Presentation Clinical Oncology Society of Australia Annual Scientific Meeting 2022

FoRECAsT study: Predicting individualised risk of developing infertility in young breast cancer patients: an international multi-cohort study. (#97)

Zobaida Edib 1 2 , Yasmin Jayasinghe 1 2 3 , Martha Hickey 1 2 , Kevin Nguyen 4 , Alex Gorelik 5 6 , FoRECAsT Consortium 2 , Michelle Peate 1 2
  1. Department of Obstetrics and Gynaecology, The Royal Women's Hospital, Parkville, Victoria, Australia
  2. University of Melbourne, Parkville, VICTORIA, Australia
  3. The Royal Children's Hospital, Parkville, Victoria, Australia
  4. Melbourne School of Population and Global Health, University of Melbourne, Melbourne, Victoria, Australia
  5. Department of Medicine, The Royal Melbourne Hospital, University of Melbourne, Parkville, Victoria, Australia
  6. Monash-Cabrini Department of Musculoskeletal Health and Clinical Epidemiology, Cabrini Health, Department of Epidemiology and Preventive Medicine School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia

Aim: The potential for developing treatment-related infertility is a high priority for young breast cancer patients. Yet, current tools to predict fertility outcomes after breast cancer treatments are imprecise, with minimal applicability for clinical practice. We aimed to develop a web-based tool to provide an individualised risk of developing infertility for young breast cancer patients.

Methods: A literature review addressing the impact of chemotherapy for breast cancer on the risk of amenorrhoea was conducted. Authors of identified articles and known data registries were contacted and invited to contribute their data to the FoRECAsT database. Logistic regression was used to develop risk prediction models, and prediction performance was evaluated internally using the area under the receiver operating curve (AUC).

Results: Out of 7473 individual records in the FoRECAsT database, menstrual history data was available for 2833 (37.91%) at 12 months and 2118 (28.34%) at 24 months. In multivariate analyses, common predictors for amenorrhea (used as a surrogate marker of infertility) at 12 and 24 months were older age at diagnosis, lower body mass index, chemotherapy regimens, use of endocrine therapy, and higher pre-treatment follicle stimulating hormone level. In addition, history of smoking and alcohol consumption were also predictors for developing amenorrhea at 12 months. Receiver–operator characteristic analysis produced an estimated AUC of 0.88 and 0.92 for amenorrhoea at 12 and 24 months. Internal validation with 1000 bootstrap resampling showed good discrimination for both models, C-index of 0·88 (95% CI 0·84–0·91) for amenorrhoea at 12 months and C-index of 0·93 (95% CI 0.90−0.94) amenorrhoea at 24 months. Based on these models, a web-based calculator is under development for implementing in clinical practice worldwide.

Conclusions: These models require external validation. However, the excellent prediction performance of the models and good precision in the estimate of accuracy in internal validation provides reassurance.