Bloomdickerson5458

ostatectomy in combination of PSA. V.BACKGROUND The recommended target low-density lipoprotein cholesterol (LDL-C) level for coronary artery disease (CAD) patients has been lowered from 100 to 70 mg/dL in several clinical guidelines for secondary prevention. We aimed to assess whether initiating statin treatment in CAD patients with baseline LDL-C 70-100 mg/dL in Taiwan could be cost-effective. METHODS A Markov model was developed to simulate a hypothetical cohort of CAD patients with a baseline LDL-C level of 90 mg/dL. The incidence and recurrence of MI and stroke related to specific LDL-C levels as well as the statin effect, mortality rate, and health state utilities were obtained from the literature. The direct medical costs and rate of fatal events were derived from the national claims database. The incremental cost-effectiveness ratio (ICER) per quality-adjusted life years (QALYs) was calculated, and sensitivity analyses were performed. RESULTS Moderate-intensity statin use, a treatment regimen expected to achieve LDL less then 70 mg/dL in the base case, resulted in a net gain of 562 QALYs but with an additional expenditure of $11.4 million per 10,000 patients over ten years. The ICER was $20,288 per QALY gained. The probabilities of being cost-effective at willingness-to-pay thresholds of one and three gross domestic product per capita ($24,329 in 2017) per QALY were 51.1% and 94.2%, respectively. Annual drug cost was the most influential factor on the ICER. CONCLUSION Lowering the target LDL-C level from 100 to 70 mg/dL among treatment-naïve CAD patients could be cost-effective given the health benefits of preventing cardiovascular events and deaths. V.BACKGROUND There is an ongoing effort to identify a biomarker which predicts metastatic progression of renal cell carcinoma (RCC). OBJECTIVE To evaluate the utility of the cell cycle progression (CCP) score biomarker in predicting metastasis in RCC after local resection of pathologic T1 disease. DESIGN, SETTING, AND PARTICIPANTS Pathologic T1 tumors at the University of Iowa were reviewed in patients who had a radical or partial nephrectomy between 1995 and 2010. Patients with known or suspected metastasis, who had received chemotherapy, or who developed metastasis within 60 days of surgery were excluded. Final analysis included 163 patients with RCC who developed metastasis or a new primary within 5 years after surgery or had been followed for 5 years without developing metastasis. INTERVENTION(S) Expression levels of 31 cell cycle genes and 15 control genes from the tumor were measured and reported as a CCP score. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS The sensitivity, specificity, positive predictive value, and negative predictive value for the development of a metastasis or new primary within 5 years of resection was calculated for varying CCP score cutoffs. RESULTS AND LIMITATIONS A total of 4 (2.5%) patients developed metastasis and 7 (4.3%) developed a new primary renal tumor. A CCP score of >-0.25 had a 100% sensitivity and 43% specificity for predicting metastatic progression. A CCP score of >-0.7 had a 100% sensitivity and 20% specificity for predicting the development of a new renal primary. CONCLUSIONS The CCP score has potential prognostic value in predicting metastatic progression and might be a useful tool for the management of patients with RCC. PATIENT SUMMARY In this study we looked at the utility of a particular gene expression profile from kidney tumors. We found that this gene expression test has the potential to identify tumors at risk of metastasis and thus could be a useful tool in the management of patients with kidney tumors. BACKGROUND MicroRNAs play an important role as modulators of gene expression in several biological processes and are closely related to development and cell differentiation regulation. Previous works have revealed a potential predictive role for miRNAs in different tumor types. This study aims to analyze the ability of miRNAs in segregating metastatic renal cell carcinoma patients according to their responses to tyrosine kinase inhibitors (TKIs). METHODS Extreme responders were considered in the study and were defined as those patients that either had a long-term response (LR) (progression-free survival ˃11 months) or those that were primary refractory (PR) (progression as best response). The expression of 754 miRNAs was analyzed in tumor tissue of these 2 sets of patients. RESULTS In a study cohort (n = 15) 4 miRNAs were significantly associated with patient response and differentially expressed in PR vs. LR (up-regulated in PR vs. AZD2171 ic50 LR miR-425-5p, down-regulated in PR vs. LR miR-139-3p, let-7d and let-7e). Further analysis in a validation cohort (n = 36) revealed similar results. CONCLUSION The present data strength the potential role of miRNAs as a tool to predict treatment outcomes in patients with metastatic renal cell carcinoma treated with TKIs. BACKGROUND Highly sensitive and specific urinary biomarkers for the early detection of bladder cancer (BC) to improve the performance of urinary cytology are needed. OBJECTIVE To investigate the usefulness of methylation markers in voided urine to identify BC presence and grade. DESIGN, SETTINGS, AND PARTICIPANTS Using genome-wide methylation strategies in Toronto, Canada and Liège, Belgium, we have identified differentially methylated genes (TWIST1, RUNX3, GATA4, NID2, and FOXE1) in low-grade vs. high-grade BC tissue and urine. We accrued urine samples from 313 patients using a 21 ratio in a case-control setting from Toronto, Canada, Halifax, Canada, and Zurich, Switzerland. We studied the usefulness of these 5 methylated genes to identify BC and discriminate cancer grade in voided urine specimens. Urinary cell sediment DNA was evaluated using qPCR-based MethyLight assay. Multivariable logistic regression prediction models were created. RESULTS AND LIMITATIONS We included 211 BC patients (180 nonmuscle invasstage but is worth further studying for instance in BC surveillance or screening in high-risk populations. Finite element analysis (FEA) and computational fluid dynamics (CFD) are generally insufficient independently to model the physics of the cardiovascular system. Individually, they are unable to resolve the interplay between the solid and fluid domains, and the interplay is integral to the functioning of the system. The use of fluid-structure interaction (FSI) methods overcomes these shortcomings by providing the means to couple the fluid and structural domains. In the last decade, the utilization of FSI has greatly increased in cardiovascular engineering. In this study, we conducted a systematic review process of more than 1000 journal articles to investigate the implementation of One-Way and Two-Way FSI for cardiovascular applications. We explored the utility of FSI to study aneurysms, the hemodynamics of patient anatomies, native and prosthetic heart valve dynamics, flow and hemodynamics of blood pumps, and atherosclerosis. Computational resource requirements, implementation strategies and future directions of FSI for cardiovascular applications are also discussed.