The records of 208.777 (100%) clinical trials registered at ClinicalTrials.gov were downloaded on the 19th of February 2016. Phase II and III trials including patients with glioblastoma were selected for further classification and analysis. Based on the disease settings, trials were classified into three groups: newly diagnosed glioblastoma, recurrent disease and trials with no differentiation according to disease setting. Furthermore, we categorized trials according to the experimental interventions, the primary sponsor, the source of financial support and trial design elements. Trends were evaluated using the autoregressive integrated moving average model. Two hundred sixteen (0.1%) trials were selected for further analysis. Academic centers (investigator initiated trials) were recorded as primary sponsors in 56.9% of trials, followed by industry 25.9%. Industry was the leading source of monetary support for the selected trials in 44.4%, followed by 25% of trials with primarily academic financial support. The number of newly initiated trials between 2005 and 2015 shows a positive trend, mainly through an increase in phase II trials, whereas phase III trials show a negative trend. The vast majority of trials evaluate forms of different systemic treatments (91.2%). In total, one hundred different molecular entities or biologicals were identified. Of those, 60% were involving drugs specifically designed for central nervous system malignancies. Trials that specifically address radiotherapy, surgery, imaging and other therapeutic or diagnostic methods appear to be rare. Current research in glioblastoma is mainly driven or sponsored by industry, academic medical oncologists and neuro-oncologists, with the majority of trials evaluating forms of systemic therapies. Few trials reach phase III. Imaging, radiation therapy and surgical procedures are underrepresented in current trials portfolios. Optimization in research portfolio for glioblastoma is needed.

Objective: To validate ultrasonographic criteria for examination of the major salivary glands in the diagnosis of primary Sjögren's syndrome (SS). Method: A total of 209 consecutive patients with rheumatic diseases were selected according to the American–European Consensus Group (AECG) classification criteria for SS. One hundred and fifteen patients had primary SS, 44 had secondary SS, and 50 had sicca symptoms, and 36 subjects served as asymptomatic controls. This cohort was analysed for size, echogenicity, parenchymal inhomogeneity, focal changes, and posterior borders of the major salivary glands by ultrasonography (US). A novel US score for parenchymal inhomogeneity (0–12) was assigned and its diagnostic accuracy evaluated. Results: Ultrasonographic abnormalities of salivary glands were detected in 107/115 (93.0%) patients with primary SS, in 12/44 (27.3%) with secondary SS, in 25/50 (50.0%) with sicca symptoms, and in 4/36 (11.1%) asymptomatic controls. Area under the receiver operating characteristic curve (AUC-ROC) for US inhomogeneity score was highly significant [0.96 ± 0.01; 95% confidence interval (CI) 0.94–0.99, p < 0.000] for primary SS, with a sensitivity to specificity ratio of 91/83 for parotid and 93/90 for submandibular glands. Setting the cut-off US inhomogeneity score at 6 resulted in the best ratio of specificity (90.0%) to sensitivity (95.1%), with a positive predictive value of 72% and a negative predictive value of 96%. A US inhomogeneity score ≥ 6 was closely correlated with positive biopsy (p < 0.000) and scintigraphy findings (p < 0.000). Conclusions: We demonstrate the high diagnostic value of a novel US score for parenchymal inhomogeneity (0–12) that could serve as a useful single US criterion in the evaluation of salivary gland involvement in primary SS.

Unlike large population studies about cardiovascular components and how they adapt to intensive physical activity, there is less research into the causes of enlargement of the respiratory system in athletes (e.g. vital capacity, maximum flow rates and pulmonary diffusion capacity). The purpose of this research was to study and compare pulmonary function in different types of sports and compare them with controls in order to find out which sports improve lung function the most. Pulmonary functional capacities, vital capacity (VC), forced vital capacity (FVC), forced expiratory volume in one second (FEV1) and maximum voluntary ventilation (MVV) of 493 top athletes belonging to 15 different sports disciplines and of 16 sedentary individuals were studied. Pulmonary function test was performed according to ATS/ERS guidelines. Basketball, water polo players and rowers had statistically higher vital capacity (VC), forced vital capacity (FVC), forced expiratory volume in one second (FEV1) than the healthy sedentary control individuals. Football and volleyball players had lower VC while FVC was higher in the football group compared to controls. Peak expiratory flow was lower in boxing, kayak, rugby, handball, taekwondo and tennis. The maximum voluntary ventilation (MVV) was significantly higher in water polo players and rowers. Boxers had statistically lower MVV than the controls. Players of other sports did not differ from the control group. The study suggests that specific type of training used in basketball, water polo or rowing could have potential for improving pulmonary function and rehabilitation.

To evaluate siMS score and siMS risk score, novel continuous metabolic syndrome scores as methods for quantification of metabolic status and risk. Developed siMS score was calculated using formula: siMS score = 2*Waist/Height + Gly/5.6 + Tg/1.7 + TA_systolic/130—HDL/1.02 or 1.28 (for male or female subjects, respectively). siMS risk score was calculated using formula: siMS risk score = siMS score * age/45 or 50 (for male or female subjects, respectively) * family history of cardio/cerebro-vascular events (event = 1.2, no event = 1). A sample of 528 obese and non-obese participants was used to validate siMS score and siMS risk score. Scores calculated as sum of z-scores (each component of metabolic syndrome regressed with age and gender) and sum of scores derived from principal component analysis (PCA) were used for evaluation of siMS score. Variants were made by replacing glucose with HOMA in calculations. Framingham score was used for evaluation of siMS risk score. Correlation between siMS score with sum of z-scores and weighted sum of factors of PCA was high (r = 0.866 and r = 0.822, respectively). Correlation between siMS risk score and log transformed Framingham score was medium to high for age groups 18+,30+ and 35+ (0.835, 0.707 and 0.667, respectively). siMS score and siMS risk score showed high correlation with more complex scores. Demonstrated accuracy together with superior simplicity and the ability to evaluate and follow-up individual patients makes siMS and siMS risk scores very convenient for use in clinical practice and research as well.

Nodular follicular lesions of thyroid gland comprise benign and malignant neoplasms, as well as some forms of hyperplasia. “Follicular” refers to origin of cells and in the same time to growth pattern - building follicles. Nodular follicular thyroid lesions have in common many morphological features, therefore attempts were made to define additional criteria for distinction between follicular adenoma, follicular carcinoma and follicular variant of papillary carcinoma. Increasing number of immunohistochemical markers is in the continual process of evaluation. Tissue microarrays incorporating, total 201 cases, out of which 122 malignant and 79 benign follicular lesions, including neoplastic and non-neoplastic, were constructed and immunostained with antibodies to CD56, CK19, Galectin-3, HBME-1. Tissue cores were exclusively being acquired from tumour/lesion on interface with normal thyroid tissue. A systematic review of literature was done for period from the year 2001 to present time. All analysed markers may make a difference between benign lesions/tumours from differentiated thyroid carcinomas (p = <0.01, for all markers). Expression of all markers is significantly higher in papillary carcinoma than in follicular adenoma (p < 0.01). Statistically significant difference in expression of Galectin-3 and CD56 between follicular carcinoma and follicular adenoma was registered (p = 0.043; p = 0.028, respectively). The only marker which expression showed statistically significant difference between adenoma and carcinoma of Hurthle cells was Galectin 3 (p = 0.041). CK19 and HBME-1 were significantly expressed more in papillary carcinoma as compared to follicular carcinoma. Galectin 3 is most sensitive marker for malignancy, while loss of expression of CD56 is very specific for malignancy. Expected co-expression for combination of markers in diagnosis of follicular lesions decreases sensitivity and increases specificity for malignancy.