3 resultados para CONDOR-Ia
Resumo:
Novel biomarkers are required to improve prognostic predictions obtained with lung cancer staging systems. This study of 62 surgically-treated Non-Small Cell Lung Cancer (NSCLC) patients had two objectives: i) to compare the predictive value of T-stage classifications between the 6(th) and 7(th) editions of the Tumor, Node, and Metastasis staging system (TNM); and ii) to examine the association of Pkp1 and/or Krt15 gene expression with survival and outcomes. Multivariate and Kaplan-Meier survival analyses were performed, examining the relationship of survival with T-stage, recurrence, and TNM-stage (by each TNM edition) and with the single/combined expression of Pkp1 and/or Krt15 genes. Five-year survival rates only significantly differed as a function of T-stage in patients without recurrence when estimated using the 6(th) edition of the TNM classification and only in patients in pathologic TNM-stage IA using the 7(th). Overall survival for patients with elevated expression of both genes was 13.5 months in those with adenocarcinoma and 34.6 months in those with squamous cell carcinoma. Overall survival was 30.4 months in patients with Pkp1 gene upregulation and 30.9 months in those with Krt15 gene upregulation. In conclusion, survival estimations as a function of T-staging differed between the 6(th) and 7(th) editions of TNM. Overall survival differed according to the expression of Pkp1 and/or Krt15 genes, although this relationship did not reach statistical significance.
Resumo:
BACKGROUND Functional brain images such as Single-Photon Emission Computed Tomography (SPECT) and Positron Emission Tomography (PET) have been widely used to guide the clinicians in the Alzheimer's Disease (AD) diagnosis. However, the subjectivity involved in their evaluation has favoured the development of Computer Aided Diagnosis (CAD) Systems. METHODS It is proposed a novel combination of feature extraction techniques to improve the diagnosis of AD. Firstly, Regions of Interest (ROIs) are selected by means of a t-test carried out on 3D Normalised Mean Square Error (NMSE) features restricted to be located within a predefined brain activation mask. In order to address the small sample-size problem, the dimension of the feature space was further reduced by: Large Margin Nearest Neighbours using a rectangular matrix (LMNN-RECT), Principal Component Analysis (PCA) or Partial Least Squares (PLS) (the two latter also analysed with a LMNN transformation). Regarding the classifiers, kernel Support Vector Machines (SVMs) and LMNN using Euclidean, Mahalanobis and Energy-based metrics were compared. RESULTS Several experiments were conducted in order to evaluate the proposed LMNN-based feature extraction algorithms and its benefits as: i) linear transformation of the PLS or PCA reduced data, ii) feature reduction technique, and iii) classifier (with Euclidean, Mahalanobis or Energy-based methodology). The system was evaluated by means of k-fold cross-validation yielding accuracy, sensitivity and specificity values of 92.78%, 91.07% and 95.12% (for SPECT) and 90.67%, 88% and 93.33% (for PET), respectively, when a NMSE-PLS-LMNN feature extraction method was used in combination with a SVM classifier, thus outperforming recently reported baseline methods. CONCLUSIONS All the proposed methods turned out to be a valid solution for the presented problem. One of the advances is the robustness of the LMNN algorithm that not only provides higher separation rate between the classes but it also makes (in combination with NMSE and PLS) this rate variation more stable. In addition, their generalization ability is another advance since several experiments were performed on two image modalities (SPECT and PET).
Resumo:
INTRODUCTION Rilpivirine (RPV) has a better lipid profile than efavirenz (EFV) in naïve patients (1). Switching to RPV may be convenient for many patients, while maintaining a good immunovirological control (2). The aim of this study was to analyze lipid changes in HIV-patients at 24 weeks after switching to Eviplera® (emtricitabine/RPV/tenofovir disoproxil fumarate [FTC/RPV/TDF]). MATERIALS AND METHODS Retrospective, multicentre study of a cohort of asymptomatic HIV-patients who switched from a regimen based on 2 nucleoside reverse transcriptase inhibitors (NRTI)+protease inhibitor (PI)/non nucleoside reverse transcriptase inhibitor (NNRTI) or ritonavir boosted PI monotherapy to Eviplera® during February-December, 2013; all had undetectable HIV viral load for ≥3 months prior to switching. Patients with previous failures on antiretroviral therapy (ART) including TDF and/or FTC/3TC, with genotype tests showing resistance to components of Eviplera®, or who had changed the third drug of the ART during the study period were excluded. Changes in lipid profile and cardiovascular risk (CVR), and efficacy and safety at 24 weeks were analyzed. RESULTS Among 305 patients included in the study, 298 were analyzed (7 cases were excluded due to lack of data). Men 81.2%, mean age 44.5 years, 75.8% of HIV sexually transmitted. 233 (78.2%) patients switched from a regimen based on 2 NRTI+NNRTI (90.5% EFV/FTC/TDF). The most frequent reasons for switching were central nervous system (CNS) adverse events (31.0%), convenience (27.6%) and metabolic disorders (23.2%). At this time, 293 patients have reached 24 weeks: 281 (95.9%) have continued Eviplera®, 6 stopped it (3 adverse events, 2 virologic failures, 1 discontinuation) and 6 have been lost to follow up. Lipid profiles of 283 cases were available at 24 weeks and mean (mg/dL) baseline vs 24 weeks are: total cholesterol (193 vs 169; p=0.0001), HDL-c (49 vs 45; p=0.0001), LDL-c (114 vs 103; p=0.001), tryglycerides (158 vs 115; p=0.0001), total cholesterol to HDL-c ratio (4.2 vs 4.1; p=0.3). CVR decreased (8.7 vs 7.5%; p= 0.0001). CD4 counts were similar to baseline (653 vs 674 cells/µL; p=0.08), and 274 (96.8%) patients maintained viral suppression. CONCLUSIONS At 24 weeks after switching to Eviplera®, lipid profile and CVR improved while maintaining a good immunovirological control. Most subjects switched to Eviplera® from a regimen based on NNRTI, mainly EFV/FTC/TDF. CNS adverse events, convenience and metabolic disorders were the most frequent reasons for switching.