Pan-European Sarcoma Trials: Moving Forward in a Climate of Increasing Economic and Regulatory Pressure

Advances in sarcoma treatment are largely based on investigator-initiated, multicentric and interdisciplinary clinical trials. The EU's Good Clinical Practice Directive 2001/20/EC, effective since 2004, was meant to harmonize the conditions for clinical trials across Europe, but, instead, the challenge of initiating and running multinational, noncommercial clinical trials has become greater than ever. Institutions participating in existing noncommercial Pan-European studies are struggling to cope with increased administrative and financial burdens, and few new studies are initiated any more. The aim of a conference entitled “Pan-European Sarcoma Trials: Moving Forward in a Climate of Increasing Economic and Regulatory Pressure,” held in Stuttgart, Germany, 30 November–2 December 2006 as part of the European Science Foundation's ECT-program, was not only to provide an overview of currently active and planned multinational studies on osteo-, Ewing's, and soft tissue sarcoma, but also to draw on areas of synergy between various established sarcoma groups in Europe to define plausible survival strategies for collaborative, interdisciplinary, patient-oriented research

The influence of tumor- and treatment-related factors on the development of local recurrence in osteosarcoma after adequate surgery. An analysis of 1355 patients treated on neoadjuvant Cooperative Osteosarcoma Study Group protocols

Background: Local recurrence (LR) in osteosarcoma is associated with very poor prognosis. We sought to evaluate which factors correlate with LR in patients who achieved complete surgical remission with adequate margins. Patients and methods: We analyzed 1355 patients with previously untreated high-grade central osteosarcoma of the extremities, the shoulder and the pelvis registered in neoadjuvant Cooperative Osteosarcoma Study Group trials between 1986 and 2005. Seventy-six patients developed LR. Results: Median follow-up was 5.56 years. No participation in a study, pelvic tumor site, limb-sparing surgery, soft tissue infiltration beyond the periosteum, poor response to neoadjuvant chemotherapy, failure to complete the planned chemotherapy protocol and biopsy at a center other than the one performing the tumor resection were significantly associated with a higher LR rate. No differences were found for varying surgical margin widths. Surgical treatment at centers with small patient volume and additional surgery in the primary tumor area, other than biopsy and tumor resection, were significantly associated with a higher rate of ablative surgery. Conclusions: Patient enrollment in clinical trials and performing the biopsy at experienced institutions capable of undertaking the tumor resection without compromising the oncological and functional outcome should be pursued in the futur

Generation of synthetic EEG data for training algorithms supporting the diagnosis of major depressive disorder

IntroductionMajor depressive disorder (MDD) is the most common mental disorder worldwide, leading to impairment in quality and independence of life. Electroencephalography (EEG) biomarkers processed with machine learning (ML) algorithms have been explored for objective diagnoses with promising results. However, the generalizability of those models, a prerequisite for clinical application, is restricted by small datasets. One approach to train ML models with good generalizability is complementing the original with synthetic data produced by generative algorithms. Another advantage of synthetic data is the possibility of publishing the data for other researchers without risking patient data privacy. Synthetic EEG time-series have not yet been generated for two clinical populations like MDD patients and healthy controls.MethodsWe first reviewed 27 studies presenting EEG data augmentation with generative algorithms for classification tasks, like diagnosis, for the possibilities and shortcomings of recent methods. The subsequent empirical study generated EEG time-series based on two public datasets with 30/28 and 24/29 subjects (MDD/controls). To obtain baseline diagnostic accuracies, convolutional neural networks (CNN) were trained with time-series from each dataset. The data were synthesized with generative adversarial networks (GAN) consisting of CNNs. We evaluated the synthetic data qualitatively and quantitatively and finally used it for re-training the diagnostic model.ResultsThe reviewed studies improved their classification accuracies by between 1 and 40% with the synthetic data. Our own diagnostic accuracy improved up to 10% for one dataset but not significantly for the other. We found a rich repertoire of generative models in the reviewed literature, solving various technical issues. A major shortcoming in the field is the lack of meaningful evaluation metrics for synthetic data. The few studies analyzing the data in the frequency domain, including our own, show that only some features can be produced truthfully.DiscussionThe systematic review combined with our own investigation provides an overview of the available methods for generating EEG data for a classification task, their possibilities, and shortcomings. The approach is promising and the technical basis is set. For a broad application of these techniques in neuroscience research or clinical application, the methods need fine-tuning facilitated by domain expertise in (clinical) EEG research

Lipase isoforms and amylase isoenzymes: assays and application in the diagnosis of acute pancreatitis

Abstract Pancreatic juice and serum from patients with acute pancreatitis contain three enzymes that have lipolytic activity: L1 and L2, which are pancreatic isoenzymes or isoforms of lipase (EC 3.1.1.3), and L3, which is probably pancreatic carboxyl ester lipase, also known as cholesterol esterase (EC 3.1.1.13). These enzymes are readily separated electrophoretically on agarose and can be developed with an overlay of Kodak Ektachem lipase slide material. The latter acts as a dry-reagent developing substrate, with the enzymes producing blue bands in the slide material. We found L1 in about one-half of normal persons, L2 in none, and L3 in all. We assayed for amylase (EC 3.2.1.1), amylase isoenzymes, lipase, and lipase isoforms in the sera of 100 patients with suspected acute pancreatitis. L2 lipase has the greatest diagnostic efficiency for the diagnosis of pancreatitis, compared with total amylase, P3 amylase, and total lipase. Lipase and L2 could replace amylase, an inefficient test, for the diagnosis of patients with suspected acute pancreatitis. In patients receiving organ transplants, a serum amylase value of greater than 300 U/L or a lipase of greater than 1000 U/L discriminated well between patients with and without complications and (or) acute rejection.</jats:p