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Ovarian cancer is the seventh most common cancer in women in the world, with an estimated worldwide mortality of over 207'000 women every year. This cancer, due to the current lack of adequate screening techniques, is commonly diagnosed late and has a poor prognosis. The oral contraceptive pill is considered the most effective prevention strategy for ovarian cancer in the general population, being associated with a decreased incidence while also having a substantial positive impact on the mortality rate, which is reduced by up to 50%. BRCA1 and BRCA2 germline mutated women have an augmented risk of ovary and breast cancer: despite international guidelines that consider prophylactic surgery as the gold standard for ovarian cancer prevention, there are currently no effective non-invasive preventive methods. In BRCA1\2 mutated patients, clinicians should weigh the benefits of contraceptive pills against the risk of long-term thromboembolic side effects and hormonal malignancies such as breast and cervical cancer. A multidisciplinary team should counsel patients on the most appropriate risk-reduction strategy tailored to their needs and expectations, proposing the oral contraceptive pill to selected patients after balancing the risks of adverse effects and the benefits on both contraception and chemoprevention., (© 2023. The Author(s), under exclusive licence to Hellenic Endocrine Society.)

Background: Accurate characterization of newly diagnosed a solid adnexal lesion is a key step in defining the most appropriate therapeutic approach. Despite guidance from the International Ovarian Tumor Analyzes Panel, the evaluation of these lesions can be challenging. Recent studies have demonstrated how machine learning techniques can be applied to clinical data to solve this diagnostic problem. However, ML models can often consider as black-boxes due to the difficulty of understanding the decision-making process used by the algorithm to obtain a specific result., Aims: For this purpose, we propose an Explainable Artificial Intelligence model trained on clinical characteristics and qualitative ultrasound indicators to predict solid adnexal masses diagnosis., Materials & Methods: Since the diagnostic task was a three-class problem (benign tumor, invasive cancer, or ovarian metastasis), we proposed a waterfall classification model: a first model was trained and validated to discriminate benign versus malignant, a second model was trained to distinguish nonmetastatic versus metastatic malignant lesion which occurs when a patient is predicted to be malignant by the first model. Firstly, a stepwise feature selection procedure was implemented. The classification performances were validated on Leave One Out scheme., Results: The accuracy of the three-class model reaches an overall accuracy of 86.36%, and the precision per-class of the benign, nonmetastatic malignant, and metastatic malignant classes were 86.96%, 87.27%, and 77.78%, respectively., Discussion: SHapley Additive exPlanations were performed to visually show how the machine learning model made a specific decision. For each patient, the SHAP values expressed how each characteristic contributed to the classification result. Such information represents an added value for the clinical usability of a diagnostic system., Conclusions: This is the first work that attempts to design an explainable machine-learning tool for the histological diagnosis of solid masses of the ovary., (© 2024 The Author(s). Cancer Medicine published by John Wiley & Sons Ltd.)

BRCA1 and BRCA2 mutations are responsible for a higher incidence of breast and ovarian cancer (from 55% up to 70% vs. 12% in the general population). If their functions have been widely investigated in the onset of these malignancies, still little is known about their role in fertility impairment. Cancer patients treated with antineoplastic drugs can be susceptible to their gonadotoxicity and, in women, some of them can induce apoptotic program in premature ovarian follicles, progressive depletion of ovarian reserve and, consequently, cancer treatment-related infertility (CTRI). BRCA variants seem to be associated with early infertility, thus accelerating treatment impairment of ovaries and making women face the concrete possibility of an early pregnancy. In this regard, fertility preservation (FP) procedures should be discussed in oncofertility counseling-from the first line of prevention with risk-reducing salpingo-oophorectomy (RRSO) to the new experimental ovarian stem cells (OSCs) model as a new way to obtain in vitro-differentiated oocytes, several techniques may represent a valid option to BRCA-mutated patients. In this review, we revisit knowledge about BRCA involvement in lower fertility, pregnancy feasibility, and the fertility preservation (FP) options available.

Objectives: The objective of this multicenter retrospective study aimed to evaluate the association of clinical variables and the incidence of ovarian cancer in patients with BRCA 1-2 mutation carriers who underwent risk-reducing salpingo-oophorectomy (RRSO)., Design: Patients with a pathogenic mutation of BRCA 1-2 genes and with no evidence of disease are considered eligible. The exclusion criterion was the refusal to undergo the surgery. The retrospective study included all RRSO performed from May 2015 to April 2022 in the three gynecological Institutions of Southern Italy for were included in this retrospective study., Participants/materials, Setting, Methods: Age, menarche age, BMI, menopause at time of RRSO, breast cancer first- and second-degree relatives, ovarian cancer first- and second-degree relatives, estroprogestin use, pregnancy normal full-term delivery, history of endometriosis, previous breast cancer and histologic type, previous abdominal/pelvic surgery, BRCA 1 or BRCA 2 status, preoperative serum CA-125 levels (IU/mL), age at time of RRSO and histological analysis were collected., Results: 184 were recruited. One was excluded. To assess cancer risk, the outcome variable was classified into three classes: no event, cancer, and other conditions excluding cancer. 14 women presented ovarian cancer and tubal intraepithelial carcinoma (STIC) on histopathologic final report. Ovarian cancer was found in 8 patients, whereas the presence of STIC was found in 6 of them., Limitations: The low incidence of patients diagnosed with ovarian cancer or STIC compared with the total number of patients undergoing RRSO is a potential bias., Conclusions: Our study did not demonstrate a correlation between clinical features and the occurrence of precancerous or cancerous lesions in BRCA mutation carrier patients., (© 2024 S. Karger AG, Basel.)