The GYMSSA trial: a prospective randomized trial comparing gastrectomy, metastasectomy plus systemic therapy versus systemic therapy alone

<p>Abstract</p> <p>Background</p> <p>The standard of care for metastatic gastric cancer (MGC) is systemic chemotherapy which leads to a median survival of 6-15 months. Survival beyond 3 years is rare. For selected groups of patients with limited MGC, retrospective studies have shown improved overall survival following gastrectomy and metastasectomies including peritoneal stripping with continuous hyperthermic peritoneal perfusion (CHPP), liver resection, and pulmonary resection. Median survival after liver resection for MGC is up to 34 months, with a five year survival rate of 24.5%. Similarly, reported median survival after pulmonary resection of MGC is 21 months with long term survival of greater than 5 years a possibility. Several case reports and small studies have documented evidence of long-term survival in select individuals who undergo CHPP for MGC.</p> <p>Design</p> <p>The GYMSSA trial is a prospective randomized trial for patients with MGC. It is designed to compare two therapeutic approaches: gastrectomy with metastasectomy plus systemic chemotherapy (GYMS) versus systemic chemotherapy alone (SA). Systemic therapy will be composed of the FOLFOXIRI regimen. The aim of the study is to evaluate overall survival and potential selection criteria to determine those patients who may benefit from surgery plus systemic therapy. The study will be conducted by the Surgery Branch at the National Cancer Institute (NCI), National Institutes of Health (NIH) in Bethesda, Maryland. Surgeries and followup will be done at the NCI, and chemotherapy will be given by either the local oncologist or the medical oncology branch at NCI.</p> <p>Trial Registration</p> <p>ClinicalTrials.gov ID. NCT00941655</p

Operational Ontology for Oncology (O3): A Professional Society-Based, Multistakeholder, Consensus-Driven Informatics Standard Supporting Clinical and Research Use of Real-World Data From Patients Treated for Cancer

PURPOSE: The ongoing lack of data standardization severely undermines the potential for automated learning from the vast amount of information routinely archived in electronic health records (EHRs), radiation oncology information systems, treatment planning systems, and other cancer care and outcomes databases. We sought to create a standardized ontology for clinical data, social determinants of health, and other radiation oncology concepts and interrelationships. METHODS AND MATERIALS: The American Association of Physicists in Medicine\u27s Big Data Science Committee was initiated in July 2019 to explore common ground from the stakeholders\u27 collective experience of issues that typically compromise the formation of large inter- and intra-institutional databases from EHRs. The Big Data Science Committee adopted an iterative, cyclical approach to engaging stakeholders beyond its membership to optimize the integration of diverse perspectives from the community. RESULTS: We developed the Operational Ontology for Oncology (O3), which identified 42 key elements, 359 attributes, 144 value sets, and 155 relationships ranked in relative importance of clinical significance, likelihood of availability in EHRs, and the ability to modify routine clinical processes to permit aggregation. Recommendations are provided for best use and development of the O3 to 4 constituencies: device manufacturers, centers of clinical care, researchers, and professional societies. CONCLUSIONS: O3 is designed to extend and interoperate with existing global infrastructure and data science standards. The implementation of these recommendations will lower the barriers for aggregation of information that could be used to create large, representative, findable, accessible, interoperable, and reusable data sets to support the scientific objectives of grant programs. The construction of comprehensive real-world data sets and application of advanced analytical techniques, including artificial intelligence, holds the potential to revolutionize patient management and improve outcomes by leveraging increased access to information derived from larger, more representative data sets

Image-Guided Adrenal and Renal Biopsy

Image-guided biopsy is a safe and well-established technique that is familiar to most interventional radiologists. Improvements in image guidance, biopsy tools, and biopsy techniques now routinely allow for safe biopsy of renal and adrenal lesions that traditionally were considered difficult to reach or technically challenging. Image-guided biopsy is used to establish the definitive tissue diagnosis in adrenal mass lesions that cannot be fully characterized with imaging or laboratory tests alone. It is also used to establish definitive diagnosis in some cases of renal parenchymal disease and has an expanding role in diagnosis and characterization of renal masses before treatment. Although basic principles and techniques for image-guided needle biopsy are similar regardless of organ, this paper highlights some technical considerations, indications, and complications that are unique to the adrenal gland and kidney because of their anatomic location and physiological features. © 2010 Elsevier Inc

Percutaneous needle placement using laser guidance: A practical solution

In interventional radiology, various navigation technologies have emerged aiming to improve the accuracy of device deployment and potentially the clinical outcomes of minimally invasive procedures. While these technologies\u27 performance has been explored extensively, their impact on daily clinical practice remains undetermined due to the additional cost and complexity, modification of standard devices (e.g. electromagnetic tracking), and different levels of experience among physicians. Taking these factors into consideration, a robotic laser guidance system for percutaneous needle placement is developed. The laser guidance system projects a laser guide line onto the skin entry point of the patient, helping the physician to align the needle with the planned path of the preoperative CT scan. To minimize changes to the standard workflow, the robot is integrated with the CT scanner via optical tracking. As a result, no registration between the robot and CT is needed. The robot can compensate for the motion of the equipment and keep the laser guide line aligned with the biopsy path in real-time. Phantom experiments showed that the guidance system can benefit physicians at different skill levels, while clinical studies showed improved accuracy over conventional freehand needle insertion. The technology is safe, easy to use, and does not involve additional disposable costs. It is our expectation that this technology can be accepted by interventional radiologists for CT guided needle placement procedures. © 2013 SPIE