Metastatic Cervical Cancer: A Case That Recalls the Importance of a Multidisciplinary Approach.

Cervical cancer is one of the most common neoplasms in women. Usually, this cancer is only symptomatic in advanced stages and is associated with a poor prognosis. We present the case of a 34-year-old woman with localized cervical cancer at diagnosis treated with surgery in 2011. Six years later, she presented recurrent disease with vaginal, pelvic, and lung metastases. Since then, the patient completed three lines of chemotherapy and a line of immunotherapy, and she was submitted to external radiotherapy and orthopedic surgery. Currently, the patient keeps regular follow-ups and maintains a good performance status. The treatment of recurrent cervical cancer remains a challenge, and the prognosis is poor. This case emphasized the importance of multidisciplinary discussion towards cases of locally advanced or metastatic cervical cancer, which may change this paradigm.

Quality of Life in Male Breast Cancer: Prospective Study of the International Male Breast Cancer Program (EORTC10085/TBCRC029/BIG2-07/NABCG).

INTRODUCTION: Prospective data about quality of life (QoL) in men with breast cancer (BC) are lacking. A prospective registry (EORTC10085) of men with all BC stages, including a QoL correlative study, was performed as part of the International Male Breast Cancer Program. METHODS: Questionnaires at BC diagnosis included the EORTC QLQ-C30 and BR23 (BC specific module), adapted for men. High functioning and global health/QoL scores indicate high functioning levels/high QoL; high symptom-focused measures scores indicate high symptoms/problems levels. EORTC reference data for healthy men and women with BC were used for comparisons. RESULTS: Of 422 men consenting to participate, 363 were evaluable. Median age was 67 years, and median time between diagnosis and survey was 1.1 months. A total of 114 men (45%) had node-positive early disease, and 28 (8%) had advanced disease. Baseline mean global health status score was 73 (SD: 21), better than in female BC reference data (62, SD: 25). Common symptoms in male BC were fatigue (22, SD: 24), insomnia (21, SD: 28), and pain (16, SD: 23), for which women's mean scores indicated more burdensome symptoms at 33 (SD: 26), 30 (SD: 32), and 29 (SD: 29). Men's mean sexual activity score was 31 (SD: 26), with less sexual activity in older patients or advanced disease. CONCLUSIONS: QoL and symptom burden in male BC patients appears no worse (and possibly better) than that in female patients. Future analyses on impact of treatment on symptoms and QoL over time, may support tailoring of male BC management.

Interpreting Deep Machine Learning Models: An Easy Guide for Oncologists.

Healthcare agents, in particular in the oncology field, are currently collecting vast amounts of diverse patient data. In this context, some decision-support systems, mostly based on deep learning techniques, have already been approved for clinical purposes. Despite all the efforts in introducing artificial intelligence methods in the workflow of clinicians, its lack of interpretability - understand how the methods make decisions - still inhibits their dissemination in clinical practice. The aim of this article is to present an easy guide for oncologists explaining how these methods make decisions and illustrating the strategies to explain them. Theoretical concepts were illustrated based on oncological examples and a literature review of research works was performed from PubMed between January 2014 to September 2020, using "deep learning techniques," "interpretability" and "oncology" as keywords. Overall, more than 60% are related to breast, skin or brain cancers and the majority focused on explaining the importance of tumor characteristics (e.g. dimension, shape) in the predictions. The most used computational methods are multilayer perceptrons and convolutional neural networks. Nevertheless, despite being successfully applied in different cancers scenarios, endowing deep learning techniques with interpretability, while maintaining their performance, continues to be one of the greatest challenges of artificial intelligence.

Do Not Forget Poly (Adenosine Diphosphate-Ribose) Polymerase Inhibitors in Ovarian Carcinosarcoma.

Ovarian carcinosarcoma (OCS) is a rare entity with a poor prognosis and without evidence-based therapy. Here, we report the case of a 55-year-old woman with a germline BRCA1 mutation and a stage IV OCS who was proposed olaparib maintenance therapy after three platinum-based chemotherapies in relapsed disease. Currently, the patient has an overall survival of 102 months and progression-free survival of 60 months with olaparib, with a good quality of life and not experiencing any adverse events. Despite the lack of evidence for the use of poly (adenosine diphosphate-ribose) polymerase inhibitors in OCS, our case report proves that patients with a potential biomarker of response to these drugs (such as BRCA mutation and platinum-sensitive disease) derive great benefits from it.