Purpose of Review: Breast cancer (BC) is the most common cancer diagnosed in women in the West World. Coping with cancer is cause of extreme stress for patients and their family. The purpose of this review is to evaluate possible approaches to follow to control those situations that can impact on quality of life (QoL) and compliance to treatments. Recent Findings: Anxiety, distress, depression, and posttraumatic stress disorder are the most frequent psychological disorders in BC patients. Cognitive disorders and sexual dysfunction can also be important in affecting QoL both in younger and older patients. Younger and older patients show different characteristics of these disorders and different strategies of managing them. Summary: Several psychotherapeutic and supportive approaches have proven effective in managing psychological disorders in BC patients. Every BC patient should be supported with these techniques during her entire oncological history, in order to increase QoL and compliance to treatments.

Ovarian cancer is the most common cause of death from gynecological cancers in developed countries. It is a common disease of older women at or above 63 years upon diagnosis. Thanks to advance in new treatments, mortality from ovarian cancer has declined in developed countries in the last decade. This decline in mortality rate is unevenly distributed across the age-spectrum. While mortality in younger women has decreased 21.7%, for elderly women it has declined only 2.2%. Even if ovarian cancer is clearly a disease of the elderly, older women are underrepresented in clinical trials, and scant evidence exists for the treatment of women older than 80 years. Moreover, older women are frequently undertreated, receive less chemotherapy and less combination of surgery and chemotherapy, despite the fact that this is considered the optimal treatment modality. This may be mainly due to the lack of evidence and physician's confidence in the management of elderly women with ovarian cancer. In this review, we focus on the management of older women with ovarian cancer, considering geriatric features tied to this population.

Locally advanced vulvar cancer (LAVC) is a challenging disease, requiring multidisciplinary management. The aim of this review is to propose an integrated clinical approach including radiotherapy (RT) in the multidisciplinary management of LAVC to customize the treatment. A review of the literature was conducted on PubMed, Scopus, and Cochrane library to acquire all relevant studies on RT in LAVC. Based on the available evidence, RT, with or without concurrent chemotherapy, has a relevant role as adjuvant and exclusive treatment or in the neoadjuvant setting. However, multicentric prospective trials are needed to define the best treatment options based on tumor and patient characteristics. A multidisciplinary and multidimensional assessment can also be useful to identify the most suitable approach, considering patients’ age and comorbidities, in view of a better treatment personalization.

Background: Artificial Intelligence (AI) is increasingly used for process management in daily life. In the medical field AI is becoming part of computerized systems to manage information and encourage the generation of evidence. Here we present the development of the application of AI to IT systems present in the hospital, for the creation of a DataMart for the management of clinical and research processes in the field of breast cancer. Materials and methods: A multidisciplinary team of radiation oncologists, epidemiologists, medical oncologists, breast surgeons, data scientists, and data management experts worked together to identify relevant data and sources located inside the hospital system. Combinations of open-source data science packages and industry solutions were used to design the target framework. To validate the DataMart directly on real-life cases, the working team defined tumoral pathology and clinical purposes of proof of concepts (PoCs). Results: Data were classified into “Not organized, not ‘ontologized’ data”, “Organized, not ‘ontologized’ data”, and “Organized and ‘ontologized’ data”. Archives of real-world data (RWD) identified were platform based on ontology, hospital data warehouse, PDF documents, and electronic reports. Data extraction was performed by direct connection with structured data or text-mining technology. Two PoCs were performed, by which waiting time interval for radiotherapy and performance index of breast unit were tested and resulted available. Conclusions: GENERATOR Breast DataMart was created for supporting breast cancer pathways of care. An AI-based process automatically extracts data from different sources and uses them for generating trend studies and clinical evidence. Further studies and more proof of concepts are needed to exploit all the potentials of this system.