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916 active trials for Prostate Cancer

Role of Lymphnode Dissection in Men With Prostate Cancer Treated With Radical Prostatectomy

Currently, lymph node dissection is standard of care during prostatectomy of intermediate risk tumors at the Martini Clinic. It allows the assessment of possible but unlikely lymph nodes metastases. In case of lymph node metastasis, depending on the number of affected lymph nodes, an adjuvant radiation with or without additional hormone therapy may be discussed in order to stop or delay further progression of the disease. Since the procedure carries additional risks, it is controversial. The risks include prolonged surgery duration, injury of vessels and nerves, as well as disorders of lymphatic circulation after surgery. Moreover, formation of lymphoceles (accumulation of lymph fluid in the tissue) are common, which may result in soft tissue swelling, thrombosis, inflammation and additional surgical procedures. Therefore, the aim of this study is to evaluate whether the removal of the lymph nodes during prostatectomy positively influences the course of the disease in patients with intermediate risk prostate cancer, or if the lymph node dissection does not have any influence on the recurrence of the disease and therefore further therapies. In this case, the omission of lymph node dissection may avoid an unnecessary expansion of the operation and the potentially associated side effects linked to it. This is particularly of interest considering the rapidly advancing technical possibilities, both in imaging and in the treatment of prostate cancer, since this enables an earlier and more individual intervention in the case of recurrence.

HamburgStart: October 2019
ONCOlogy-targeted NLP-powered Federated Hyper-archItecture and Data Sharing Framework for Health Data Reusability

ONCO-FIRE proposes to build a novel hyper-architecture and a common data model (CDM) for oncology, as well as a rich, modular toolset enabling significantly increased interoperability, exploitability, use and reuse of diverse, multi-modal health data available in electronic Health Records (EHR) and cancer big data repositories to the benefit of health professionals, healthcare providers and researchers; this will eventually lead to more efficient and cost-effective health care procedures and workflows that support improved care delivery to cancer patients encompassing support for cancer early prediction, diagnosis, and follow-up. The applicability, usefulness and usability of the proposed hyper-architecture, CDM and toolset for oncology and the high exploitability of health data will be demonstrated in diverse data exploitation scenarios related to breast and prostate cancer involving a number of Virtual Assistants (VAs) and advanced services offering to health care professionals (HCPs), hospital administration/healthcare providers and researchers data-driven decision-support and easy navigation across large amounts of cancer-related information. Through the above mentioned outcomes and the (meta)data interoperability achieved, ONCO-FIRE contributes to the exploitation of large volumes, highly heterogeneous (meta)data in EHR and data repositories including imaging data, structured data (e.g. demographics, laboratory, pathological data), as well as diverse formats of unstructured clinical reports and notes (e.g. text, pdf), including (but not limited to) temporal information related to the patient care pathway and genomics data currently "hidden" in unstructured medical reports, and more. Importantly, ONCO-FIRE interconnects, following a federated approach, large, distributed cancer imaging repositories, currently used for AI tools training and validation, with patient registries and EHRs of cancer-related data and supports exploitation of relevant unstructured data through novel Natural Language Processing (NLP) tools. The ultimate goal is to establish a patient-centric, federated multi-source and interoperable data-sharing ecosystem, where healthcare providers, clinical experts, citizens and researchers contribute, access and reuse multimodal health data, thereby making a significant contribution to the creation of the European Health Data Space.

Start: June 2023