950 resultados para AFT Models for Crash Duration Survival Analysis


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Background Clinical relevance of tumor infiltrating lymphocytes (TILs) in breast cancer is controversial. Here, we used a tumor microarray including a large series of ductal and lobular breast cancers with long term follow up data, to analyze clinical impact of TIL expressing specific phenotypes and distribution of TILs within different tumor compartments and in different histological subtypes. Methods A tissue microarray (TMA) including 894 ductal and 164 lobular breast cancers was stained with antibodies recognizing CD4, FOXP3, and IL-17 by standard immunohistochemical techniques. Lymphocyte counts were correlated with clinico-pathological parameters and survival. Results CD4+ lymphocytes were more prevalent than FOXP3+ TILs whereas IL-17+ TILs were rare. Increased numbers of total CD4+ and FOXP3+ TIL were observed in ductal, as compared with lobular carcinomas. High grade (G3) and estrogen receptor (ER) negative ductal carcinomas displayed significantly (p < 0.001) higher CD4+ and FOXP3+ lymphocyte infiltration while her2/neu over-expression in ductal carcinomas was significantly (p < 0.001) associated with higher FOXP3+ TIL counts. In contrast, lymphocyte infiltration was not linked to any clinico-pathological parameters in lobular cancers. In univariate but not in multivariate analysis CD4+ infiltration was associated with significantly shorter survival in patients bearing ductal, but not lobular cancers. However, a FOXP3+/CD4+ ratio > 1 was associated with improved overall survival even in multivariate analysis (p = 0.033). Conclusions Ductal and lobular breast cancers appear to be infiltrated by different lymphocyte subpopulations. In ductal cancers increased CD4+ and FOXP3+ TIL numbers are associated with more aggressive tumor features. In survival analysis, absolute numbers of TILs do not represent major prognostic indicators in ductal and lobular breast cancer. Remarkably however, a ratio > 1 of total FOXP3+/CD4+ TILs in ductal carcinoma appears to represent an independent favorable prognostic factor.

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As lightweight and slender structural elements are more frequently used in the design, large scale structures become more flexible and susceptible to excessive vibrations. To ensure the functionality of the structure, dynamic properties of the occupied structure need to be estimated during the design phase. Traditional analysis method models occupants simply as an additional mass; however, research has shown that human occupants could be better modeled as an additional degree-of- freedom. In the United Kingdom, active and passive crowd models are proposed by the Joint Working Group as a result of a series of analytical and experimental research. It is expected that the crowd models would yield a more accurate estimation to the dynamic response of the occupied structure. However, experimental testing recently conducted through a graduate student project at Bucknell University indicated that the proposed passive crowd model might be inaccurate in representing the impact on the structure from the occupants. The objective of this study is to provide an assessment of the validity of the crowd models proposed by JWG through comparing the dynamic properties obtained from experimental testing data and analytical modeling results. The experimental data used in this study was collected by Firman in 2010. The analytical results were obtained by performing a time-history analysis on a finite element model of the occupied structure. The crowd models were created based on the recommendations from the JWG combined with the physical properties of the occupants during the experimental study. During this study, SAP2000 was used to create the finite element models and to implement the analysis; Matlab and ME¿scope were used to obtain the dynamic properties of the structure through processing the time-history analysis results from SAP2000. The result of this study indicates that the active crowd model could quite accurately represent the impact on the structure from occupants standing with bent knees while the passive crowd model could not properly simulate the dynamic response of the structure when occupants were standing straight or sitting on the structure. Future work related to this study involves improving the passive crowd model and evaluating the crowd models with full-scale structure models and operating data.

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AIMS: Although an added diagnostic and prognostic value of the global coronary artery calcification (CAC) score as an adjunct to single-photon emission computed tomography (SPECT)-myocardial perfusion image (MPI) has been repeatedly documented, none of the previous studies took advantage of the anatomic information provided by the unenhanced cardiac CT. Therefore, no co-registration has so far been used to match a myocardial perfusion defect with calcifications in the subtending coronary artery. To evaluate the prognostic value of integrating SPECT-MPI with CAC images were obtained from non-enhanced cardiac computed tomography (CT) for attenuation correction to predict major adverse cardiac events (MACE). METHODS AND RESULTS: Follow-up was obtained in 462 patients undergoing a 1-day stress/rest (99m)Tc-teterofosmin SPECT and non-enhanced cardiac CT for attenuation correction. Survival free of MACE was determined using the Kaplan-Meier method. After integrating MPI and CT findings, patients were divided into three groups (i) MPI defect matched by calcification (CAC ≥ 1) in the subtending coronary artery (ii) unmatched MPI and CT finding (iii) normal finding by MPI and CT. At a mean follow-up of 34.5 ± 13 months, a MACE was observed in 80 patients (33 death, 6 non-fatal myocardial infarction, 9 hospitalizations due to unstable angina, and 32 revascularizations). Survival analysis revealed the most unfavourable outcome (P < 0.001 log-rank test) for patients with a matched finding. CONCLUSION: In the present study, a novel approach using a combined integration of cardiac SPECT-CAC imaging allows for refined risk stratification, as a matched defect emerged as an independent predictor of MACE.

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PURPOSE: The cyclin D1 (CCND1) A870G gene polymorphism is linked to the outcome in patients with resectable non-small cell lung cancer (NSCLC). Here, we investigated the impact of this polymorphism on smoking-induced cancer risk and clinical outcome in patients with NSCLC stages I-IV. METHODS: CCND1 A870G genotype was determined by polymerase chain reaction (PCR) and restriction fragment length polymorphism analysis (RFLP) of DNA extracted from blood. The study included 244 NSCLC patients and 187 healthy control subjects. RESULTS: Patient characteristics were: 70% male, 77% smokers, 43% adenocarcinoma, and 27% squamous cell carcinoma. Eighty-one percent of the patients had stages III-IV disease. Median age at diagnosis was 60 years and median survival was 13 months. Genotype frequencies of patients and controls both conformed to the Hardy Weinberg equilibrium. The GG genotype significantly correlated with a history of heavy smoking (>or=40 py, P=0.02), and patients with this genotype had a significantly higher cigarette consumption than patients with AA/AG genotypes (P=0.007). The GG genotype also significantly correlated with tumor response or stabilization after a platinum-based first-line chemotherapy (P=0.04). Survival analysis revealed no significant differences among the genotypes. CONCLUSION: Evidence was obtained that the CCND1 A870G gene polymorphism modulates smoking-induced lung cancer risk. Further studies are required to explore the underlying molecular mechanisms and to test the value of this gene polymorphism as a predictor for platinum-sensitivity in NSCLC patients.

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Studies of chronic life-threatening diseases often involve both mortality and morbidity. In observational studies, the data may also be subject to administrative left truncation and right censoring. Since mortality and morbidity may be correlated and mortality may censor morbidity, the Lynden-Bell estimator for left truncated and right censored data may be biased for estimating the marginal survival function of the non-terminal event. We propose a semiparametric estimator for this survival function based on a joint model for the two time-to-event variables, which utilizes the gamma frailty specification in the region of the observable data. Firstly, we develop a novel estimator for the gamma frailty parameter under left truncation. Using this estimator, we then derive a closed form estimator for the marginal distribution of the non-terminal event. The large sample properties of the estimators are established via asymptotic theory. The methodology performs well with moderate sample sizes, both in simulations and in an analysis of data from a diabetes registry.

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This paper considers a wide class of semiparametric problems with a parametric part for some covariate effects and repeated evaluations of a nonparametric function. Special cases in our approach include marginal models for longitudinal/clustered data, conditional logistic regression for matched case-control studies, multivariate measurement error models, generalized linear mixed models with a semiparametric component, and many others. We propose profile-kernel and backfitting estimation methods for these problems, derive their asymptotic distributions, and show that in likelihood problems the methods are semiparametric efficient. While generally not true, with our methods profiling and backfitting are asymptotically equivalent. We also consider pseudolikelihood methods where some nuisance parameters are estimated from a different algorithm. The proposed methods are evaluated using simulation studies and applied to the Kenya hemoglobin data.