Traditionally, surgery and radiation represented the pillars of cancer therapy. In contrast to the European approach, in the United States chemotherapy for ovarian cancer has replaced radiation for a long time. Nevertheless, with the aim being cure of the patient, both approaches result in a sometimes severely diminished quality of life for the woman. With the recognition that aggressiveness in therapy many times did not correlate with improved survival time, paradigms in the treatment of women with reproductive organ cancers have shifted lately. Modern antiproliferative therapy strives for both, maximizing survival time as well as quality of life. New therapeutic concepts as well as an abundance of new drugs await the conclusion of clinical trials to identify their potential role in the advancement of ovarian cancer therapy. This article reviews the most recent literature available on systemic and intraperitoneal chemotherapy of early-stage and advanced epithelial ovarian cancer, high-dose chemotherapy, and biologic and gene therapy. Chemotherapy of germ cell and malignant ovarian stromal tumors is also discussed. Extensive tables provide a comprehensive overview of ongoing clinical trials in the US as well as elsewhere.
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An overview of the use of cutting-edge artificial intelligence (AI) modeling to produce synthetic medical data (SMD) in decentralized clinical machine learning (ML) for ovarian cancer(OC) and ovarian lymphoma(OL).
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, Costa Contina street n. 19, 66054, Vasto, Chieti, Italy.
Aim: o point out how novel analysis tools of AI can make sense of the data acquired during OL and OC diagnosis and treatment in an effort to help improve and standardize the patient pathway for these disease.
Material And Methods: ultilizing programmed detection of heterogeneus OL and OC habitats through radiomics and correlate to imaging based tumor grading plus a literature review.
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