Tests of proportional hazards and proportional odds models for grouped survival data

In this paper, we derive score test statistics to discriminate between proportional hazards and proportional odds models for grouped survival data. These models are embedded within a power family transformation in order to obtain the score tests. In simple cases, some small-sample results are obtained for the score statistics using Monte Carlo simulations. Score statistics have distributions well approximated by the chi-squared distribution. Real examples illustrate the proposed tests.

Modeling grouped survival data with time-dependent covariates

In this article, proportional hazards and logistic models for grouped survival data were extended to incorporate time-dependent covariates. The extension was motivated by a forestry experiment designed to compare five different water stresses in Eucalyptus grandis seedlings. The response was the seedling lifetime. The data set was grouped since there were just three occasions in which the seedlings was visited by the researcher. In each of these occasions also the shoot height was measured and therefore it is a time-dependent covariate. Both extended models were used in this example, and the results were very similar.

Likelihood approximations and discrete models for tied survival data

Ties among event times are often recorded in survival studies. For example, in a two week laboratory study where event times are measured in days, ties are very likely to occur. The proportional hazards model might be used in this setting using an approximated partial likelihood function. This approximation works well when the number of ties is small. on the other hand, discrete regression models are suggested when the data are heavily tied. However, in many situations it is not clear which approach should be used in practice. In this work, empirical guidelines based on Monte Carlo simulations are provided. These recommendations are based on a measure of the amount of tied data present and the mean square error. An example illustrates the proposed criterion.

A Generalized Log-Normal Model for Grouped Survival Data

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Oviposition and survival in females of Procornitermes araujoi under laboratory conditions (Isoptera, Termitidae, Nasutitermitinae)

After an enormous swarming of Procornitermes araujoi when a great number of females were collected, we investigated the occurrence of parthenogenesis beyond oviposition and survival of these females under laboratory conditions. The groups of virgin females were faster in their first oviposition than females of male-female pairs, nevertheless their eggs never hatch. The survival data showed higher longevity in the group of three females when compared with groups of two and four females.

The Conway-Maxwell-Poisson-generalized gamma regression model with long-term survivors

In this paper, we proposed a flexible cure rate survival model by assuming the number of competing causes of the event of interest following the Conway-Maxwell distribution and the time for the event to follow the generalized gamma distribution. This distribution can be used to model survival data when the hazard rate function is increasing, decreasing, bathtub and unimodal-shaped including some distributions commonly used in lifetime analysis as particular cases. Some appropriate matrices are derived in order to evaluate local influence on the estimates of the parameters by considering different perturbations, and some global influence measurements are also investigated. Finally, data set from the medical area is analysed.

Tumor-associated macrophages and the profile of inflammatory cytokines in oral squamous cell carcinoma

Objective: To evaluate and characterize macrophage populations (M1/M2) in the tumor microenvironment of oral cavity squamous cell carcinoma (OCSCC). The relationship between macrophages and clinicopathological factors, such as survival data, lymph node metastasis, tumoral proliferation, and WHO histological grading are also analyzed. Materials and methods: The samples consisted of surgically excised specimens from patients with non-metastatic and metastatic OCSCC and normal oral mucosa (control). Immunohistochemistry, flow cytometry, and qRT-PCR were used to evaluate macrophage populations and the expression of pro- (IL-12, IL-23, and INF-γ) and anti-inflammatory (IL-10 and TGF-β) cytokines. The level required for statistical significance was defined as p < 0.05. Results: The data showed a predominance of M2 phenotype (high percentage of IL-10+TGF-β+) macrophages in the tumor microenvironment of OCSCC. A higher percentage of macrophages expressing TGF-β was seen in the OCSCC group when compared with healthy individuals. The assessment of mRNA expression also presented a greater expression of anti-inflammatory cytokines TGFβ and IL10 in OCSCC when compared with the control group. The percentage of macrophages, demonstrated by immunohistochemistry, was significantly higher in the metastatic OCSCC group than in the non-metastatic and control groups. The log-rank test also showed that the mean survival time for patients with high levels of macrophages was less (44 months) when compared with patients with a low percentage of such cells (93 months). Conclusion: A predominance of the M2 phenotype in the tumor microenvironment of OCSCC could contribute to local immunosuppression, via TGF-β production, and consequently greater lymph node involvement and reduced patient survival time. © 2012 Elsevier Ltd. All rights reserved.

Macrophage migration inhibitory factor and oral cancer

Background: Macrophage migration inhibitory factor (MIF) is a pleiotropic cytokine with pro-inflammatory functions and involved in tumorigenesis. The aim of this study was to evaluate the expression and localization of the macrophage MIF in oral squamous carcinoma (OSC). In addition, the relationship between MIF expression and clinicopathological parameters such as survival data, tobacco use, alcohol habits, TNM stage, tumor graduation, and peritumoral inflammatory infiltrate were evaluated. Methods: Using immunohistochemistry, expression and localization of MIF was detected in 44 specimens of OSC. The absolute number and relative proportions of MIF-positive cells detected were also determined separately for tumor parenchyma vs. stroma. All counts were determined from 10 consecutive high-power fields using an integration graticule. Moreover, some parameters were analyzed separately for lip and intra-oral cancers. Results: Migration inhibitory factor-positive cells were observed in both the tumor parenchyma and in inflammatory cells of all specimens. In contrast, MIF expression was not detected in tumoral nests associated with poorly differentiated tumors. In specimens of lip cancer, a greater number of MIF-positive stromal immune cells were detected than in intra-oral cancer specimens (Mann-Whitney test, P = 0.049). Conclusions: Oral squamous carcinoma cells consistently express MIF independent of their location. Lip tumors presented more MIF-positive peritumoral inflammatory cells, similar to control, suggesting that immunological differences in leukocyte activation exist between in lip and intra-oral cancers. © 2012 John Wiley & Sons A/S.

Detecção do papilomavírus humano (HPV) em carcinoma epidermóide de lábio através da nested PCR e sua correlação com os fatores de risco, características clínicas, anatomopatológicas e de sobrevida

Pós-graduação em Odontologia - FOA

Apoptose no carcinoma de próstata

Pós-graduação em Patologia - FMB

Modelos para dados grupados e sensurados aplicados à área biológica: comparação usando fator de Bayes

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

The FGM bivariate lifetime copula model: a bayesian approach

In this paper, we propose a bivariate distribution for the bivariate survival times based on Farlie-Gumbel-Morgenstern copula to model the dependence on a bivariate survival data. The proposed model allows for the presence of censored data and covariates. For inferential purpose a Bayesian approach via Markov Chain Monte Carlo (MCMC) is considered. Further, some discussions on the model selection criteria are given. In order to examine outlying and influential observations, we present a Bayesian case deletion influence diagnostics based on the Kullback-Leibler divergence. The newly developed procedures are illustrated via a simulation study and a real dataset.

In vitro Survival of Follicles Collected from Domestic Cats' Ovaries at Different Stages of Oestrous Cycle and Cultured with IGF-1

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Predictors of first-year survival in patients with advanced COPD treated using long-term oxygen therapy

Little evidence-based guidance is available to aid clinicians in determining short-term prognoses in very severe COPD patients. Therefore, the present study was designed to provide a prospective assessment (1) of the mortality rates and (2) whether the baseline measurements may be determinants of 1-year mortality in hypoxemic COPD patients receiving long-term oxygen therapy (LTOT).Seventy-eight clinically stable patients with advanced COPD treated using LTOT were enrolled in a prospective cohort study. Outcome variable: first-year mortality. Baseline measurements: categorical variables: age (<60 or >= 60 years); gender; body mass index (<20 or >= 20 kg/m(2)); fat-free mass (FFM) index (<16 [men] and <15kg/m(2) [women]; baseline dyspnea index (BDI) (<= 3 or >3); and corticosteroid use. Continuous variables: smoking history; lung function; FFM; fat mass; hemoglobin; hematocrit; arterial blood gases; forearm muscle strength; St. George's Respiratory Questionnaire (SGRQ); and comorbidity score. By the end of 1-year of follow-up, 12 patients (15.4%) had died. Kaplan-Meier curves showed that BDI <= 3 was the only variable associated with higher mortality. Cox proportional hazards analysis revealed that tower PaO2 and SPO2, higher PaCO2 and SGRQ scores were associated with reduced survival. In the multivariate analysis, BDI remained predictive of mortality (hazard ratio [HR], 0.50; 95% confidence interval [CI], 0.31-0.81), as did PaO2 (HR, 0.49; 95% CI, 0.26-0.95). These data suggest that readily available parameters as dyspnea intensity and hypoxemia severity may be useful in predicting first-year survival rates in advanced COPD patients receiving LTOT (C) 2007 Elsevier Ltd. All rights reserved.

Recurrent copy number gains of ACVR1 and corresponding transcript overexpression are associated with survival in head and neck squamous cell carcinomas

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)