Catharyn Stern

Treatment-induced ovarian function loss is a significant concern for many young patients with breast cancer. Accurately predicting this risk is crucial for counselling young patients and informing their fertility-related decision-making. However, current risk prediction models for treatment-related ovarian function loss have limitations. To provide a broader representation of patient cohorts and improve feature selection, we combined retrospective data from six datasets within the FoRECAsT (Infertility after Cancer Predictor) databank, including 2679 pre-menopausal women diagnosed with breast cancer. This combined dataset presented notable missingness, prompting us to employ cross imputation using the k-nearest neighbours (KNN) machine learning (ML) algorithm. Employing Lasso regression, we developed an ML model to forecast the risk of treatment-related amenorrhea as a surrogate marker of ovarian function loss at 12 months after starting chemotherapy. Our model identified 20 variables significantly associated with risk of developing amenorrhea. Internal validation resulted in an area under the receiver operating characteristic curve (AUC) of 0.820 (95% CI: 0.817–0.823), while external validation with another dataset demonstrated an AUC of 0.743 (95% CI: 0.666–0.818). A cutoff of 0.20 was chosen to achieve higher sensitivity in validation, as false negatives—patients incorrectly classified as likely to regain menses—could miss timely opportunities for fertility preservation if desired. At this threshold, internal validation yielded sensitivity and precision rates of 91.3% and 61.7%, respectively, while external validation showed 92.9% and 60.0%. Leveraging ML methodologies, we not only devised a model for personalised risk prediction of amenorrhea, demonstrating substantial enhancements over existing models but also showcased a robust framework for maximally harnessing available data sources.

Treatment-induced ovarian function loss is a significant concern for many young patients with breast cancer. Accurately predicting this risk is crucial for counselling young patients and informing their fertility-related decision-making. However, current risk-prediction models for treatment-related ovarian function loss have limitations. To provide a broader representation of patient cohorts and improve feature selection, we combined retrospective data from six datasets within the FoRECAsT (Infertility after Cancer Predictor) databank, including 2,679 pre-menopausal women diagnosed with breast cancer. This combined dataset presented notable missingness, prompting us to employ cross imputation using the k-nearest neighbours (KNN) machine learning (ML) algorithm. Employing Lasso regression, we developed an ML model to forecast the risk of treatment-related amenorrhea as a surrogate marker of ovarian function loss at 12 months after starting chemotherapy. Our model identified 20 variables significantly associated with risk of developing amenorrhea. Internal validation resulted in an area under the receiver operating characteristic curve (AUC) of 0.820 (95% CI: 0.817-0.823), while external validation with another dataset demonstrated an AUC of 0.743 (95% CI: 0.666-0.818). A cutoff of 0.20 was chosen to achieve higher sensitivity in validation, as false negatives—patients incorrectly classified as likely to regain menses—could miss timely opportunities for fertility preservation if desired. At this threshold, internal validation yielded sensitivity and precision rates of 91.3% and 61.7%, respectively, while external validation showed 92.9% and 60.0%. Leveraging ML methodologies, we not only devised a model for personalised risk prediction of amenorrhea, demonstrating substantial enhancements over existing models but also showcased a robust framework for maximally harnessing available data sources.

Purpose As a further step to elucidate the actual diverse spectrum of oncofertility practices for breast cancer around the globe, we present and discuss the comparisons of oncofertility practices for breast cancer in limited versus optimum resource settings based on data collected in the Repro-Can-OPEN Study Part I & II. Methods We surveyed 39 oncofertility centers including 14 in limited resource settings from Africa, Asia & Latin America (Repro-Can-OPEN Study Part I), and 25 in optimum resource settings from the United States, Europe, Australia and Japan (Repro-Can-OPEN Study Part II). Survey questions covered the availability of fertility preservation and restoration options offered to young female patients with breast cancer as well as the degree of utilization. Results In the Repro-Can-OPEN Study Part I & II, responses for breast cancer and calculated oncofertility scores showed the following characteristics: (1) higher oncofertility scores in optimum resource settings than in limited resource settings especially for established options, (2) frequent utilization of egg freezing, embryo freezing, ovarian tissue freezing, GnRH analogs, and fractionation of chemo- and radiotherapy, (3) promising utilization of oocyte in vitro maturation (IVM), (4) rare utilization of neoadjuvant cytoprotective pharmacotherapy, artificial ovary, and stem cells reproductive technology as they are still in preclinical or early clinical research settings, (5) recognition that technical and ethical concerns should be considered when offering advanced and innovative oncofertility options. Conclusions We presented a plausible oncofertility best practice model to guide oncofertility teams in optimizing care for breast cancer patients in various resource settings.

Purpose The main objective of Repro-Can-OPEN Study Part 2 is to learn more about oncofertility practices in optimum resource settings to provide a roadmap to establish oncofertility best practice models. Methods As an extrapolation for oncofertility best practice models in optimum resource settings, we surveyed 25 leading and well-resourced oncofertility centers and institutions from the USA, Europe, Australia, and Japan. The survey included questions on the availability and degree of utilization of fertility preservation options in case of childhood cancer, breast cancer, and blood cancer. Results All surveyed centers responded to all questions. Responses and their calculated oncofertility scores showed three major characteristics of oncofertility practice in optimum resource settings: (1) strong utilization of sperm freezing, egg freezing, embryo freezing, ovarian tissue freezing, gonadal shielding, and fractionation of chemo- and radiotherapy; (2) promising utilization of GnRH analogs, oophoropexy, testicular tissue freezing, and oocyte in vitro maturation (IVM); and (3) rare utilization of neoadjuvant cytoprotective pharmacotherapy, artificial ovary, in vitro spermatogenesis, and stem cell reproductive technology as they are still in preclinical or early clinical research settings. Proper technical and ethical concerns should be considered when offering advanced and experimental oncofertility options to patients. Conclusions Our Repro-Can-OPEN Study Part 2 proposed installing specific oncofertility programs for common cancers in optimum resource settings as an extrapolation for best practice models. This will provide efficient oncofertility edification and modeling to oncofertility teams and related healthcare providers around the globe and help them offer the best care possible to their patients.

Young women diagnosed with breast cancer may be confronted by many difficult decisions, especially around fertility preservation prior to commencing cancer treatment. The information to be conveyed is complex, and it may be difficult to weigh up the risks and benefits of the different fertility preservation options available. This complexity is compounded by the widespread low levels of literacy and health literacy in Australia, which may result in greater difficulties in understanding available health information and in decision-making. A working group of experts have developed a fertility-related online decision aid for a low health literacy population, guided by health literacy principles. The decision aid will be pilot tested with 30 women diagnosed with early breast cancer between 5 years and 6 months previously. To be eligible, at the time of diagnosis, women must be between 18 and 40 years (inclusive), pre-menopausal, have no history of metastatic disease, have not completed their families, be able to give informed consent and have low health literacy. Participants will be asked to reflect back to the time in which they were diagnosed. Participants will complete a questionnaire before and after reviewing the decision aid to determine the feasibility, use and acceptability of the decision aid. The decision aid will be modified accordingly. Participants may also choose to review a previously developed (high literacy) decision aid and provide feedback in comparison to the low health literacy decision aid. This project represents the first study to develop an online fertility decision aid developed from low health literacy models in the context of breast cancer. It is anticipated that the low health literacy decision aid will be useful and acceptable to young women with low health literacy who have been diagnosed with breast cancer and that it will be preferred over the high literacy decision aid. ACTRN12615001364561p

Cancer treatment can diminish fertility in women and men. The need for fertility preservation is growing as increasing numbers of people survive cancer. Cryostorage of reproductive material to preserve potential for conception for cancer survivors has moved from being experimental to being a part of clinical management of women and men who are diagnosed with cancer in their reproductive years. There is little existing evidence about how fertility preservation services can be enhanced to meet the complex needs of patients who are diagnosed with cancer in their reproductive years. The aim of this research was to inform clinical practice development by drawing on the collective experience and knowledge of staff at well-established clinics that offer fertility preservation before cancer treatment. A qualitative research model was adopted using semi-structured interviews with professionals involved in the care of people who freeze reproductive material before cancer treatment. In the state of Victoria, Australia, two large assisted reproductive technology (ART) centres have been providing fertility preservation services for more than two decades. An invitation to participate in a semi-structured interview about clinical care in the context of fertility preservation was emailed to past and current staff members. To capture diverse perspectives, informants were sought from all relevant professions: fertility specialists, andrologists, nurses, embryologists/scientists, counsellors, and administrative staff. Transcripts were analysed thematically. Thirteen key informants were interviewed from August 2013 to February 2014. The identified themes relating to enhancing clinical care in a fertility preservation service were communication between oncology and ART specialists; managing urgency; managing patients’ expectations; establishing and implementing protocols, systems, and data bases; and maintaining contact with patients. The collective knowledge of this study’s informants, who represent multidisciplinary teams with more than two decades’ experience in fertility preservation, yields important insights into strategies that fertility preservation services can employ to promote the integration of oncology and fertility care, the psychosocial care of patients, data recording and monitoring, and reporting of outcomes.

Ovarian tissue cryopreservation and transplantation is a form of fertility preservation offered to young women at high risk of losing ovarian function after cancer treatment. While there have been successful births resulting from orthotopic site grafts, we report the first case of an ongoing pregnancy from a heterotopic graft in a patient who had previously undergone bilateral oopherectomy for a granulosa cell tumour. Frozen–thawed ovarian tissue was transplanted to the anterior abdominal wall. Subsequent ovarian stimulation and transabdominal ultrasound-guided oocyte retrieval from the grafts resulted in two oocytes. These were fertilized with ICSI and two embryos were transferred. Serial ultrasounds have confirmed an ongoing 26-week intrauterine twin pregnancy. Thus, this first demonstration of a pregnancy from a heterotopic graft site provides unequivocal evidence that cryopreservation preserves complete follicle development and that normal ovarian function can occur at a non-ovarian site. This provides optimism for further efforts to assist women who have had oophorectomy and pelvic surgery or radiotherapy, without an appropriate orthotopic site for grafting.

Cryostorage of reproductive potential, in the form of ovarian cortex, for young women about to undergo cytotoxic therapies has been offered clinically for some time. However, the prospects of re-establishing reproductive function using this tissue remain unclear. We now report reproducible follicular development, oocyte retrieval and embryo development following heterotopic grafting of cryopreserved ovarian cortex which had been stored for over 10 years.