160 resultados para Classification Protocols


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Vulvar cancer is a rare disease and its screening is depending on the quality and the relevance of our clinical examination. Incidence of vulvar cancer and especially precancerous lesions, vulvar intraepithelial neoplasias (VIN), increased during these last years. The new terminology of vulvar intraepithelial neoplasia will help us to identify high risk groups which could develop a cancer: usual and differentiated VIN. An early diagnosis is essential to propose an adequate treatment. Management is a major point according to the rising incidence of these lesions in younger women. Until we can observe a benefit from the vaccination against human papillomavirus, we must increase the quality of screening by a careful examination of the vulva.

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INTRODUCTION: The 2004 version of the World Health Organization classification subdivides thymic epithelial tumors into A, AB, B1, B2, and B3 (and rare other) thymomas and thymic carcinomas (TC). Due to a morphological continuum between some thymoma subtypes and some morphological overlap between thymomas and TC, a variable proportion of cases may pose problems in classification, contributing to the poor interobserver reproducibility in some studies. METHODS: To overcome this problem, hematoxylin-eosin-stained and immunohistochemically processed sections of prototypic, "borderland," and "combined" thymomas and TC (n = 72) were studied by 18 pathologists at an international consensus slide workshop supported by the International Thymic Malignancy Interest Group. RESULTS: Consensus was achieved on refined criteria for decision making at the A/AB borderland, the distinction between B1, B2, and B3 thymomas and the separation of B3 thymomas from TCs. "Atypical type A thymoma" is tentatively proposed as a new type A thymoma variant. New reporting strategies for tumors with more than one histological pattern are proposed. CONCLUSION: These guidelines can set the stage for reproducibility studies and the design of a clinically meaningful grading system for thymic epithelial tumors.

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BACKGROUND: Diffuse large B-cell lymphomas (DLBCLs) arising in specific extranodal sites have peculiar clinicopathologic features. PATIENTS AND METHODS: We analyzed a cohort of 187 primary Waldeyer's ring (WR) DLBCLs retrieved from GELA protocols using anthracyclin-based polychemotherapy. RESULTS: Most patients (92%) had stage I-II disease. A germinal center B-cell-like (GCB) immunophenotype was observed in 61%, and BCL2 expression in 55%, of WR DLBCLs. BCL2, BCL6, IRF4 and MYC breakpoints were observed in, respectively, 3 of 42 (7%), 9 of 36 (25%), 2 of 26 (8%) and 4 of 40 (10%) contributive cases. A variable follicular pattern was evidenced in 30 of 68 (44%) large biopsy specimens. The 5-year progression-free survival (PFS) and the overall survival (OS) of 153 WR DLBCL patients with survival information were 69.5% and 77.8%, respectively. The GCB immunophenotype correlated with a better OS (P = 0.0015), while BCL2 expression predicted a worse OS (P = 0.037), an effect overcome by the GCB/non-GCB classification. Compared with matched nodal DLBCLs, WR DLBCLs with no age-adjusted international prognostic index factor disclosed a better 5-year PFS rate (77.5% versus 70.7%; P = 0.03). CONCLUSIONS: WR DLBCLs display distinct clinicopathologic features compared with conventional DLBCLs, with usual localized-stage disease, common follicular features and a high frequency of GCB immunophenotype contrasting with a low rate of BCL2 rearrangements. In addition, they seem to be associated with a better outcome than their nodal counterpart.

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PURPOSE: Acute myeloid leukemia (AML) with inv(3)(q21q26.2)/t(3;3)(q21;q26.2) [inv(3)/t(3;3)] is recognized as a distinctive entity in the WHO classification. Risk assignment and clinical and genetic characterization of AML with chromosome 3q abnormalities other than inv(3)/t(3;3) remain largely unresolved. PATIENTS AND METHODS: Cytogenetics, molecular genetics, therapy response, and outcome analysis were performed in 6,515 newly diagnosed adult AML patients. Patients were treated on Dutch-Belgian Hemato-Oncology Cooperative Group/Swiss Group for Clinical Cancer Research (HOVON/SAKK; n = 3,501) and German-Austrian Acute Myeloid Leukemia Study Group (AMLSG; n = 3,014) protocols. EVI1 and MDS1/EVI1 expression was determined by real-time quantitative polymerase chain reaction. RESULTS: 3q abnormalities were detected in 4.4% of AML patients (288 of 6,515). Four distinct groups were defined: A: inv(3)/t(3;3), 32%; B: balanced t(3q26), 18%; C: balanced t(3q21), 7%; and D: other 3q abnormalities, 43%. Monosomy 7 was the most common additional aberration in groups (A), 66%; (B), 31%; and (D), 37%. N-RAS mutations and dissociate EVI1 versus MDS1/EVI1 overexpression were associated with inv(3)/t(3;3). Patients with inv(3)/t(3;3) and balanced t(3q21) at diagnosis presented with higher WBC and platelet counts. In multivariable analysis, only inv(3)/t(3;3), but not t(3q26) and t(3q21), predicted reduced relapse-free survival (hazard ratio [HR], 1.99; P < .001) and overall survival (HR, 1.4; P = .006). This adverse prognostic impact of inv(3)/t(3;3) was enhanced by additional monosomy 7. Group D 3q aberrant AML also had a poor outcome related to the coexistence of complex and/or monosomal karyotypes and cryptic inv(3)/t(3;3). CONCLUSION: Various categories of 3q abnormalities in AML can be distinguished according to their clinical, hematologic, and genetic features. AML with inv(3)/t(3;3) represents a distinctive subgroup with unfavorable prognosis.

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111 patients with acute leukemia, including 29 children, were classified according to the surface markers and cytochemistry of their blasts. The acute leukemias were separated into two majors groups (lymphoid and non-lymphoid) depending on the presence or absence of specific lymphoid markers. On the basis of these criteria a correlation of 94% with the hematological diagnosis was obtained. Acute lymphoblastic leukemia (ALL) was divisible into three sub-groups: 11 cases expressing T-cell specific markers were classified as T-ALL and 33 cases expressing the common ALL antigen (CALLA) as c-ALL. 18 of the latter expressed an additional marker, DSA (Daudi surface antigen), splitting c-ALL cases in two subgroups. Cytochemistry of the cases lacking specific surface markers (n = 67) served to diagnose 41 acute myeloid leukemia (AML) cases and 8 monoblastic leukemias. The remaining 18 cases could not be classified. The presence of absence of HLD-DR (Ia) antigens served to subdivide AML into two major subgroups. The prognostic significance of these new diagnostic splits is under active study.

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BACKGROUND: Extensive research exists estimating the effect hazardous alcohol¦use on morbidity and mortality, but little research quantifies the association between¦alcohol consumption and utility scores in patients with alcohol dependence.¦In the context of comparative research, the World Health Organisation (WHO)¦proposed to categorise the risk for alcohol-related acute and chronic harm according¦to patients' average daily alcohol consumption. OBJECTIVES: To estimate utility¦scores associated with each category of the WHO drinking risk-level classification¦in patients with alcohol dependence (AD). METHODS: We used data from¦CONTROL, an observational cohort study including 143 AD patients from the Alcohol¦Treatment Center at Lausanne University Hospital, followed for 12 months.¦Average daily alcohol consumption was assessed monthly using the Timeline Follow-¦back method and patients were categorised according to the WHO drinking¦risk-level classification: abstinent, low, medium, high and very high. Other measures¦as sociodemographic characteristics and utility scores derived from the EuroQoL¦5-Dimensions questionnaire (EQ-5D) were collected every three months.¦Mixed models for repeated measures were used to estimate mean utility scores¦associated with WHO drinking risk-level categories. RESULTS: A total of 143 patients¦were included and the 12-month follow-up permitting the assessment of¦1318 person-months. At baseline the mean age of the patients was 44.6 (SD 11.8)¦and the majority of patients was male (63.6%). Using repeated measures analysis,¦utility scores decreased with increasing drinking levels, ranging from 0.80 in abstinent¦patients to 0.62 in patients with very high risk drinking level (p_0.0001).¦CONCLUSIONS: In this sample of patients with alcohol dependence undergoing¦specialized care, utility scores estimated from the EQ-5D appeared to substantially¦and consistently vary according to patients' WHO drinking level.

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CD34/QBEND10 immunostaining has been assessed in 150 bone marrow biopsies (BMB) including 91 myelodysplastic syndromes (MDS), 16 MDS-related AML, 25 reactive BMB, and 18 cases where RA could neither be established nor ruled out. All cases were reviewed and classified according to the clinical and morphological FAB criteria. The percentage of CD34-positive (CD34 +) hematopoietic cells and the number of clusters of CD34+ cells in 10 HPF were determined. In most cases the CD34+ cell count was similar to the blast percentage determined morphologically. In RA, however, not only typical blasts but also less immature hemopoietic cells lying morphologically between blasts and promyelocytes were stained with CD34. The CD34+ cell count and cluster values were significantly higher in RA than in BMB with reactive changes (p&lt;0.0001 for both), in RAEB than in RA (p=0.0006 and p=0.0189, respectively), in RAEBt than in RAEB (p=0.0001 and p=0.0038), and in MDS-AML than in RAEBt (p&lt;0.0001 and p=0.0007). Presence of CD34+ cell clusters in RA correlated with increased risk of progression of the disease. We conclude that CD34 immunostaining in BMB is a useful tool for distinguishing RA from other anemias, assessing blast percentage in MDS cases, classifying them according to FAB, and following their evolution.

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BACKGROUND: Several studies have established Glioblastoma Multiforme (GBM) prognostic and predictive models based on age and Karnofsky Performance Status (KPS), while very few studies evaluated the prognostic and predictive significance of preoperative MR-imaging. However, to date, there is no simple preoperative GBM classification that also correlates with a highly prognostic genomic signature. Thus, we present for the first time a biologically relevant, and clinically applicable tumor Volume, patient Age, and KPS (VAK) GBM classification that can easily and non-invasively be determined upon patient admission. METHODS: We quantitatively analyzed the volumes of 78 GBM patient MRIs present in The Cancer Imaging Archive (TCIA) corresponding to patients in The Cancer Genome Atlas (TCGA) with VAK annotation. The variables were then combined using a simple 3-point scoring system to form the VAK classification. A validation set (N = 64) from both the TCGA and Rembrandt databases was used to confirm the classification. Transcription factor and genomic correlations were performed using the gene pattern suite and Ingenuity Pathway Analysis. RESULTS: VAK-A and VAK-B classes showed significant median survival differences in discovery (P = 0.007) and validation sets (P = 0.008). VAK-A is significantly associated with P53 activation, while VAK-B shows significant P53 inhibition. Furthermore, a molecular gene signature comprised of a total of 25 genes and microRNAs was significantly associated with the classes and predicted survival in an independent validation set (P = 0.001). A favorable MGMT promoter methylation status resulted in a 10.5 months additional survival benefit for VAK-A compared to VAK-B patients. CONCLUSIONS: The non-invasively determined VAK classification with its implication of VAK-specific molecular regulatory networks, can serve as a very robust initial prognostic tool, clinical trial selection criteria, and important step toward the refinement of genomics-based personalized therapy for GBM patients.

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A semisupervised support vector machine is presented for the classification of remote sensing images. The method exploits the wealth of unlabeled samples for regularizing the training kernel representation locally by means of cluster kernels. The method learns a suitable kernel directly from the image and thus avoids assuming a priori signal relations by using a predefined kernel structure. Good results are obtained in image classification examples when few labeled samples are available. The method scales almost linearly with the number of unlabeled samples and provides out-of-sample predictions.

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The research considers the problem of spatial data classification using machine learning algorithms: probabilistic neural networks (PNN) and support vector machines (SVM). As a benchmark model simple k-nearest neighbor algorithm is considered. PNN is a neural network reformulation of well known nonparametric principles of probability density modeling using kernel density estimator and Bayesian optimal or maximum a posteriori decision rules. PNN is well suited to problems where not only predictions but also quantification of accuracy and integration of prior information are necessary. An important property of PNN is that they can be easily used in decision support systems dealing with problems of automatic classification. Support vector machine is an implementation of the principles of statistical learning theory for the classification tasks. Recently they were successfully applied for different environmental topics: classification of soil types and hydro-geological units, optimization of monitoring networks, susceptibility mapping of natural hazards. In the present paper both simulated and real data case studies (low and high dimensional) are considered. The main attention is paid to the detection and learning of spatial patterns by the algorithms applied.

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Myasthenia gravis (MG) can be difficult to treat despite an available therapeutic armamentarium. Our aim was to analyze the factors leading to unsatisfactory outcome (UO). To this end we used the Myasthenia Gravis Foundation of America classification system. Forty one patients with autoimmune MG were followed prospectively from January 2003 to December 2007. Outcomes were assessed throughout follow-up and at a final visit. 'Unchanged', 'worse', 'exacerbation' and 'died of MG' post-intervention status were considered UOs. During follow-up, UO rates reached 54% and were related to undertreatment (41%), poor treatment compliance (23%), infections (23%), and adverse drug effects (13%). The UO rate at final study assessment was 20%. UO during follow-up was significantly (P = 0.004) predictive of UOs at final assessment. When care was provided by neuromuscular (NM) specialists, patients had significantly better follow-up scores (P = 0.01). At final assessment UO rates were 7% and significantly better in patients treated by NM specialists, compared to other physicians where UO rates reached 27%. UO was a frequent finding occurring in more than half our patients during follow-up. Nearly two-thirds of the UOs could have been prevented by appropriate therapeutic adjustments and improved compliance. The differential UO rates at follow-up, their dependency on the degree to which the management was specialized and their correlation with final outcomes suggest that specialized MG care improves outcomes.

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The paper deals with the development and application of the generic methodology for automatic processing (mapping and classification) of environmental data. General Regression Neural Network (GRNN) is considered in detail and is proposed as an efficient tool to solve the problem of spatial data mapping (regression). The Probabilistic Neural Network (PNN) is considered as an automatic tool for spatial classifications. The automatic tuning of isotropic and anisotropic GRNN/PNN models using cross-validation procedure is presented. Results are compared with the k-Nearest-Neighbours (k-NN) interpolation algorithm using independent validation data set. Real case studies are based on decision-oriented mapping and classification of radioactively contaminated territories.

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Colorectal cancer (CRC) is a major cause of cancer mortality. Whereas some patients respond well to therapy, others do not, and thus more precise, individualized treatment strategies are needed. To that end, we analyzed gene expression profiles from 1,290 CRC tumors using consensus-based unsupervised clustering. The resultant clusters were then associated with therapeutic response data to the epidermal growth factor receptor-targeted drug cetuximab in 80 patients. The results of these studies define six clinically relevant CRC subtypes. Each subtype shares similarities to distinct cell types within the normal colon crypt and shows differing degrees of 'stemness' and Wnt signaling. Subtype-specific gene signatures are proposed to identify these subtypes. Three subtypes have markedly better disease-free survival (DFS) after surgical resection, suggesting these patients might be spared from the adverse effects of chemotherapy when they have localized disease. One of these three subtypes, identified by filamin A expression, does not respond to cetuximab but may respond to cMET receptor tyrosine kinase inhibitors in the metastatic setting. Two other subtypes, with poor and intermediate DFS, associate with improved response to the chemotherapy regimen FOLFIRI in adjuvant or metastatic settings. Development of clinically deployable assays for these subtypes and of subtype-specific therapies may contribute to more effective management of this challenging disease.