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.

A Bayesian analysis of the Conway-Maxwell-Poisson cure rate model

The purpose of this paper is to develop a Bayesian analysis for the right-censored survival data when immune or cured individuals may be present in the population from which the data is taken. In our approach the number of competing causes of the event of interest follows the Conway-Maxwell-Poisson distribution which generalizes the Poisson distribution. Markov chain Monte Carlo (MCMC) methods are used to develop a Bayesian procedure for the proposed model. Also, some discussions on the model selection and an illustration with a real data set are considered.

Home range, movements and diurnal roosts of the endangered thin-spined porcupine, Chaetomys subspinosus (Rodentia: Erethizontidae), in the Brazilian Atlantic Forest

Chaetomys subspinosus is the sole species within the Chaetomyinae subfamily of Caviomorph rodents. This poorly studied porcupine is restricted to the Atlantic Forest in eastern Brazil, where deforestation and habitat fragmentation threaten its survival. Data on the ranging and roosting behavior of C. subspinosus is fairly scarce as it is difficult to observe these behaviors in nature and, consequently, it is very rarely detected during field surveys. We monitored the home ranges of three radio-tagged females over the course of 1 year (2005-2006) and collected data on several aspects of their natural history including movement patterns and the use of diurnal roosts and latrines. The animals were monitored at Parque Estadual Paulo Cesar Vinha, a nature reserve dominated by restinga forests, a subtype of Atlantic Forest occurring on sandy soil. The estimated home range varied little between individuals and was relatively small (mean = 2.14 ha/individual and 1.09 ha/individual using minimum convex polygon and kernel methods, respectively). The animals travelled an average of 147 m/night (range: 21-324 m/night) between two consecutive day roosts. The day roosts were mostly located on vine and liana tangles in the canopy which also aid in connecting the canopy to adjacent trees or the forest floor. Latrines were mostly located near the ground in places heavily protected by spiny bromeliads or by other tangled vegetation. Our data suggests that C. subspinosus has the smallest range among all Neotropical Erethizontids which is likely due to its small size and strictly folivorous diet. Our data also helps explain why C. subspinosus is so difficult to observe in nature: researchers should focus on arboreal masses of tangled vegetation where individuals will normally rest during the day. (C) 2011 Deutsche Gesellschaft fur Saugetierkunde. Published by Elsevier GmbH. All rights reserved.

The geometric Birnbaum-Saunders regression model with cure rate

In this paper, we propose a cure rate survival model by assuming the number of competing causes of the event of interest follows the Geometric distribution and the time to event follow a Birnbaum Saunders distribution. We consider a frequentist analysis for parameter estimation of a Geometric Birnbaum Saunders model with cure rate. Finally, to analyze a data set from the medical area. (C) 2011 Elsevier B.V. All rights reserved.

A new long-term lifetime distribution induced by a latent complementary risk framework

In this paper, we proposed a new three-parameter long-term lifetime distribution induced by a latent complementary risk framework with decreasing, increasing and unimodal hazard function, the long-term complementary exponential geometric distribution. The new distribution arises from latent competing risk scenarios, where the lifetime associated scenario, with a particular risk, is not observable, rather we observe only the maximum lifetime value among all risks, and the presence of long-term survival. The properties of the proposed distribution are discussed, including its probability density function and explicit algebraic formulas for its reliability, hazard and quantile functions and order statistics. The parameter estimation is based on the usual maximum-likelihood approach. A simulation study assesses the performance of the estimation procedure. We compare the new distribution with its particular cases, as well as with the long-term Weibull distribution on three real data sets, observing its potential and competitiveness in comparison with some usual long-term lifetime distributions.

The negative binomial-beta Weibull regression model to predict the cure of prostate cancer

In this article, for the first time, we propose the negative binomial-beta Weibull (BW) regression model for studying the recurrence of prostate cancer and to predict the cure fraction for patients with clinically localized prostate cancer treated by open radical prostatectomy. The cure model considers that a fraction of the survivors are cured of the disease. The survival function for the population of patients can be modeled by a cure parametric model using the BW distribution. We derive an explicit expansion for the moments of the recurrence time distribution for the uncured individuals. The proposed distribution can be used to model survival data when the hazard rate function is increasing, decreasing, unimodal and bathtub shaped. Another advantage is that the proposed model includes as special sub-models some of the well-known cure rate models discussed in the literature. We derive the appropriate matrices for assessing local influence on the parameter estimates under different perturbation schemes. We analyze a real data set for localized prostate cancer patients after open radical prostatectomy.

Bevacizumab plus oxaliplatin-based chemotherapy as adjuvant treatment for colon cancer (AVANT): a phase 3 randomised controlled trial

Background: Bevacizumab improves the efficacy of oxaliplatin-based chemotherapy in metastatic colorectal cancer. Our aim was to assess the use of bevacizumab in combination with oxaliplatin-based chemotherapy in the adjuvant treatment of patients with resected stage III or high-risk stage II colon carcinoma. Methods: Patients from 330 centres in 34 countries were enrolled into this phase 3, open-label randomised trial. Patients with curatively resected stage III or high-risk stage II colon carcinoma were randomly assigned (1: 1: 1) to receive FOLFOX4 (oxaliplatin 85 mg/m(2), leucovorin 200 mg/m(2), and fluorouracil 400 mg/m(2) bolus plus 600 mg/m(2) 22-h continuous infusion on day 1; leucovorin 200 mg/m(2) plus fluorouracil 400 mg/m(2) bolus plus 600 mg/m(2) 22-h continuous infusion on day 2) every 2 weeks for 12 cycles; bevacizumab 5 mg/kg plus FOLFOX4 (every 2 weeks for 12 cycles) followed by bevacizumab monotherapy 7.5 mg/kg every 3 weeks (eight cycles over 24 weeks); or bevacizumab 7.5 mg/kg plus XELOX (oxaliplatin 130 mg/m(2) on day 1 every 2 weeks plus oral capecitabine 1000 mg/m(2) twice daily on days 1-15) every 3 weeks for eight cycles followed by bevacizumab monotherapy 7.5 mg/kg every 3 weeks (eight cycles over 24 weeks). Block randomisation was done with a central interactive computerised system, stratified by geographic region and disease stage. Surgery with curative intent occurred 4-8 weeks before randomisation. The primary endpoint was disease-free survival, analysed for all randomised patients with stage III disease. This study is registered with ClinicalTrials.gov, number NCT00112918. Findings: Of the total intention-to-treat population (n=3451), 2867 patients had stage III disease, of whom 955 were randomly assigned to receive FOLFOX4, 960 to receive bevacizumab-FOLFOX4, and 952 to receive bevacizumab-XELOX. After a median follow-up of 48 months (range 0-66 months), 237 patients (25%) in the FOLFOX4 group, 280 (29%) in the bevacizumab-FOLFOX4 group, and 253 (27%) in the bevacizumab-XELOX group had relapsed, developed a new colon cancer, or died. The disease-free survival hazard ratio for bevacizumab-FOLFOX4 versus FOLFOX4 was 1.17 (95% CI 0.98-1.39; p=0.07), and for bevacizumab-XELOX versus FOLFOX4 was 1.07 (0.90-1.28; p=0.44). After a minimum follow-up of 60 months, the overall survival hazard ratio for bevacizumab-FOLFOX4 versus FOLFOX4 was 1.27 (1.03-1.57; p=0.02), and for bevacizumab-XELOX versus FOLFOX4 was 1.15 (0.93-1.42; p=0.21). The 573 patients with high-risk stage II cancer were included in the safety analysis. The most common grade 3-5 adverse events were neutropenia (FOLFOX4: 477 [42%] of 1126 patients, bevacizumab-FOLFOX4: 416 [36%] of 1145 patients, and bevacizumab-XELOX: 74 [7%] of 1135 patients), diarrhoea (110 [10%], 135 [12%], and 181 [16%], respectively), and hypertension (12 [1%], 122 [11%], and 116 [10%], respectively). Serious adverse events were more common in the bevacizumab groups (bevacizumab-FOLFOX4: 297 [26%]; bevacizumab-XELOX: 284 [25%]) than in the FOLFOX4 group (226 [20%]). Treatment-related deaths were reported in one patient receiving FOLFOX4, two receiving bevacizumab-FOLFOX4, and five receiving bevacizumab-XELOX. Interpretation: Bevacizumab does not prolong disease-free survival when added to adjuvant chemotherapy in resected stage III colon cancer. Overall survival data suggest a potential detrimental effect with bevacizumab plus oxaliplatin-based adjuvant therapy in these patients. On the basis of these and other data, we do not recommend the use of bevacizumab in the adjuvant treatment of patients with curatively resected stage III colon cancer.

SDHB loss predicts malignancy in pheochromocytomas/sympathethic paragangliomas, but not through hypoxia signalling

Prediction of malignant behaviour of pheochromocytomas/sympathetic paragangliomas (PCCs/PGLs) is very difficult if not impossible on a histopathological basis. In a familial setting, it is well known that succinate dehydrogenase subunit B (SDHB)-associated PCC/PGL very often metastasise. Recently, absence of SDHB expression as measured through immunohistochemistry was shown to be an excellent indicator of the presence of an SDH germline mutation in PCC/PGL. SDHB loss is believed to lead to tumour formation by activation of hypoxia signals. To clarify the potential use of SDHB immunohistochemistry as a marker of malignancy in PCC/PGL and its association with classic hypoxia signalling we examined SDHB, hypoxia inducible factor-1 (Hif-1 ) and its targets CA-9 and GLUT-1 expression on protein level using immunohistochemistry on a tissue micro array on a series of familial and sporadic tumours of 115 patients. Survival data was available for 66 patients. SDHB protein expression was lost in the tumour tissue of 12 of 99 patients. Of those 12 patients, 5 had an SDHB germline mutation, in 4 patients no germline mutation was detected and mutational status remained unknown in parts in 3 patients. Loss of SDHB expression was not associated with increased classic hypoxia signalling as detected by Hif-1 , CA-9 or GLUT-1 staining. Loss of SDHB expression was associated with an adverse outcome. The lack of correlation of SDHB loss with classic hypoxia signals argues against the current hypoxia hypothesis in malignant PCC/PGL. We suggest SDHB protein loss as a marker of adverse outcome both in sporadic and in familial PCC/PGL.

Modeling of red blood cell life-spans in hematologically normal populations

Despite the impact of red blood cell (RBC) Life-spans in some disease areas such as diabetes or anemia of chronic kidney disease, there is no consensus on how to quantitatively best describe the process. Several models have been proposed to explain the elimination process of RBCs: random destruction process, homogeneous life-span model, or a series of 4-transit compartment model. The aim of this work was to explore the different models that have been proposed in literature, and modifications to those. The impact of choosing the right model on future outcomes prediction--in the above mentioned areas--was also investigated. Both data from indirect (clinical data) and direct life-span measurement (biotin-labeled data) methods were analyzed using non-linear mixed effects models. Analysis showed that: (1) predictions from non-steady state data will depend on the RBC model chosen; (2) the transit compartment model, which considers variation in life-span in the RBC population, better describes RBC survival data than the random destruction or homogenous life-span models; and (3) the additional incorporation of random destruction patterns, although improving the description of the RBC survival data, does not appear to provide a marked improvement when describing clinical data.

Quantifying and Comparing the Accuracy of Binary Biomarkers When Predicting a Failure Time Outcome

The positive and negative predictive value are standard measures used to quantify the predictive accuracy of binary biomarkers when the outcome being predicted is also binary. When the biomarkers are instead being used to predict a failure time outcome, there is no standard way of quantifying predictive accuracy. We propose a natural extension of the traditional predictive values to accommodate censored survival data. We discuss not only quantifying predictive accuracy using these extended predictive values, but also rigorously comparing the accuracy of two biomarkers in terms of their predictive values. Using a marginal regression framework, we describe how to estimate differences in predictive accuracy and how to test whether the observed difference is statistically significant.

Current role of surgery for high risk prostate cancer

In this review, the role of surgery in patients with adverse tumor characteristics and a high risk of tumor progression are discussed. In the current PSA era the proportion of patients presenting with high risk prostate cancer (PCa) is estimated to be between 15% and 25% with a 10-year cancer specific survival in the range of 80-90% for those receiving active local treatment. The treatment of high risk prostate cancer is a contemporary challenge. Surgery in this group is gaining popularity since 10-year cancer specific survival data of over 90% has been described. Radical prostatectomy should be combined with extended lymphadenectomy. Adjuvant or salvage therapies may be needed in more than half of patients , guided by pathologic findings and postoperative PSA. Unfortunately there are no randomized controlled trials comparing radical prostatectomy to radiotherapy and no single treatment can be universally recommended. This group of high risk prostate cancer patients should be considered a multi-disciplinary challenge; however, for the properly selected patient, radical prostatectomy either as initial or as the only therapy can be considered an excellent treatment.

Effects of informative censoring on the hazard function: Application to the proportional hazards regression model

The standard analyses of survival data involve the assumption that survival and censoring are independent. When censoring and survival are related, the phenomenon is known as informative censoring. This paper examines the effects of an informative censoring assumption on the hazard function and the estimated hazard ratio provided by the Cox model.^ The limiting factor in all analyses of informative censoring is the problem of non-identifiability. Non-identifiability implies that it is impossible to distinguish a situation in which censoring and death are independent from one in which there is dependence. However, it is possible that informative censoring occurs. Examination of the literature indicates how others have approached the problem and covers the relevant theoretical background.^ Three models are examined in detail. The first model uses conditionally independent marginal hazards to obtain the unconditional survival function and hazards. The second model is based on the Gumbel Type A method for combining independent marginal distributions into bivariate distributions using a dependency parameter. Finally, a formulation based on a compartmental model is presented and its results described. For the latter two approaches, the resulting hazard is used in the Cox model in a simulation study.^ The unconditional survival distribution formed from the first model involves dependency, but the crude hazard resulting from this unconditional distribution is identical to the marginal hazard, and inferences based on the hazard are valid. The hazard ratios formed from two distributions following the Gumbel Type A model are biased by a factor dependent on the amount of censoring in the two populations and the strength of the dependency of death and censoring in the two populations. The Cox model estimates this biased hazard ratio. In general, the hazard resulting from the compartmental model is not constant, even if the individual marginal hazards are constant, unless censoring is non-informative. The hazard ratio tends to a specific limit.^ Methods of evaluating situations in which informative censoring is present are described, and the relative utility of the three models examined is discussed. ^