Use of artificial intelligence to predict response to neoadjuvant chemotherapy in breast cancer

:Breast cancer is the object of thousands of studies worldwide. Nevertheless, few tools are available to corroborate prediction of response to neoadjuvant chemotherapy. Artificial intelligence is being researched for its potential utility in several fields of knowledge, including oncology. The development of a standardized Artificial intelligence-based predictive model for patients with breast cancer may help make clinical management more personalized and effective. We aimed to apply Artificial intelligence models to predict the response to neoadjuvant chemotherapy based solely on clinical and pathological data. Methods: Medical records of 130 patients treated with neoadjuvant chemotherapy were reviewed and divided into two groups: 90 samples to train the network and 40 samples to perform prospective testingand validate the results obtained by the Artificial intelligence method. Results: Using clinicopathologic data alone, the artificial neural network was able to correctly predict pathologic complete response in 83.3% of the cases. It also correctly predicted 95.6% of locoregional recurrence, as well as correctly determined whether patients were alive or dead at a given time point in 90% of the time. To date, no published research has used clinicopathologic data to predict the response to neoadjuvant chemotherapy in patients with breast cancer, thus highlighting the importance of the present study. Conclusions: Artificial neural network may become an interesting tool for predicting response to neoadjuvant chemotherapy, locoregional recurrence, systemic disease progression, and survival in patients with breast cancer (AU)

Perception of gender discrimination among spine surgeons across Latin America: a web-based survey.

BACKGROUND CONTEXT: Female physicians rarely choose spine surgery as their specialty. Although the specialty's nature and its associated lifestyle are potential barriers, gender-related issues may play an important part. PURPOSE: To evaluate the gender discrimination among spine surgeons across Latin America. STUDY DESIGN: Cross-sectional survey. PATIENT SAMPLE: The participants in this study were 223 AO Spine Latin America (AOSLA) registered members who answered the web-based survey. OUTCOME MEASURES: Personal and professional demographics; gender-related objective and subjective experiences regarding career and personal life. METHODS: A survey link containing a 24-item questionnaire was sent to the members' e-mails in September 2019. The survey was designed to evaluate the perception of gender discrimination by spine surgeons during their academic and professional lives. RESULTS: Out of 223 members who answered the survey, 196 (87.96%) were male and 27 (12.11%) female. Most were orthopedic surgeons (64.13%), ≥40 years of age (55.16%), and had <20 years of experience (69.95%). Gender discrimination was more frequent among women than among men (66.67% vs. 1.02%), as did discouragement from becoming a spine surgeon, orthopedic surgeon, or neurosurgeon (81.48% vs. 0.51%). Females reported higher rates of sexual harassment (44.44% vs. 7.65%) and more often felt disadvantaged because of gender (55.56% vs. 2.55%). Working harder than men to achieve the same prestige and lack of female mentorship were the most common obstacles reported by women (55.56%). Residency/fellowship influenced the decision to postpone/avoid having children for 66.67% of women but only 37.75% of men. Creation of a Women's Committee in AO Spine was supported by 74.07% of women and 38.78% of men. CONCLUSIONS: Gender-based discrimination affects women more frequently than men in spine surgery. These experiences likely contribute to the low prevalence of female spine surgeons. Efforts to mitigate bias and support the professional development of women in neurosurgery, orthopedics and spine communities are encouraged.