Pelvic magnetic resonance imaging in the ewe: a model for experimental gynecologic research.

AIM: Our goal was to demonstrate the feasibility of pelvic magnetic resonance imaging (MRI) in the ewe. MATERIAL AND METHODS: Two ewes underwent a pelvic 3 Tesla MRI scan, under light anesthesia, with T2-weighted fast spin-echo images and T1-weighted spoiled gradient-echo images. Multiplan T1 weighted images were also obtained after the intravenous injection of a contrast product. One ewe was anestrous and the other one had undergone ovarian stimulation. RESULTS: No incident occurred during the examination. Both the uterus (with two horns) and the ovaries were identified. The intensity of the endometrial, myometrial and ovarian signals was similar to that encountered in women. The uterus and ovaries could be enhanced in both cases. Pelvic vasculature was also studied. In the case of hormonal stimulation, the endometrium was thicker, follicular growth was identified and enhancement seemed greater. CONCLUSION: MRI in the ewe is feasible and could be helpful in experimental gynecologic research, especially in uterus transplantation.

Dynamic Projection of Medication Nonpersistence and Nonadherence Among Patients With Early Breast Cancer.

Importance: Oral endocrine treatments have been shown to be effective when carefully adhered to. However, in patients with early breast cancer, adherence challenges are notable, with 17% experiencing nonpersistence and 41% nonadherence at least once. Objective: To model the persistence of and adherence to oral anticancer treatment of a patient with localized breast cancer. Design, Setting, and Participants: This cohort study was conducted using anonymous reimbursement data belonging to French female patients with breast cancer, extracted from the French Health Insurance database from January 2013 to December 2018. Data analysis was conducted from January 2021 to May 2022. Main Outcomes and Measures: The main outcome was the detection of episodes of nonpersistence and nonadherence 6 months before they happened. Adherence was defined as the ratio between the time covered by a drug purchase and the time between 2 purchases; patients were considered nonadherent if the ratio of their next 3 purchases was less than 80%. Disparities in persistence and adherence based on criteria such as age, treatment type, and income were identified. Results: A total of 229 695 female patients (median [IQR] age, 63 [52-72] years) with localized breast cancer were included. A deep learning model based on a gated-recurrent unit architecture was used to detect episodes of nonpersistence or nonadherence. This model demonstrated an area under the receiving operating curve of 0.71 for persistence and 0.73 for adherence. Analyzing the Shapley Additive Explanations values also gave insights into the contribution of the different features over the model's decision. Patients older than 70 years, with past nonadherence, taking more than 1 treatment in the previous 3 months, and with low income had greater risk of episodes of nonpersistence. Age and past nonadherence, including regularity of past adherence, were also important features in the nonadherence model. Conclusions and Relevance: This cohort study found associations of patient age and past adherence with nonpersistence or nonadherence. It also suggested that regular intervals in treatment purchases enhanced adherence, in contrast to irregular purchasing patterns. This research offers valuable tools for improving persistence of and adherence to oral anticancer treatment among patients with early breast cancer.

External validation of a published nomogram for prediction of brain metastasis in patients with extra-cerebral metastatic breast cancer and risk regression analysis.

BACKGROUND: Survival of patients with metastatic breast cancer (MBC) suffering from brain metastasis (BM) is limited and this event is usually fatal. In 2010, the Graesslin's nomogram was published in order to predict subsequent BM in patients with breast cancer (BC) with extra-cerebral metastatic disease. This model aims to select a patient population at high risk for BM and thus will facilitate the design of prevention strategies and/or the impact of early treatment of BM in prospective clinical studies. PATIENTS AND METHODS: Nomogram external validation was retrospectively applied to patients with BC and later BM between January 2005 and December 2012, treated in our institution. Moreover, risk factors of BM appearance were studied by Fine and Gray's competing risk analysis. RESULTS: Among 492 patients with MBC, 116 developed subsequent BM. Seventy of them were included for the nomogram validation. The discrimination is good (area under curve = 0.695 [95% confidence interval, 0.61-0.77]). Risk factors of BM appearance are: human epidermal growth factor receptor 2 (HER2) overexpression/amplification, triple-negative BC and number of extra-cerebral metastatic sites (>1). With a competing risk model, we highlight the nomogram interest for HER2+ tumour subgroup exclusively. CONCLUSION: Graesslin's nomogram external validation demonstrates exportability and reproducibility. Importantly, the competing risk model analysis provides additional information for the design of prospective trials concerning the early diagnosis of BM and/or preventive treatment on high risk patients with extra-cerebral metastatic BC.