Câncer de boca e orofaringe: tendências e análise de sobrevida em Natal (RN)

Introduction: Mouth cancer is classified as having one of the ten highest cancer incidences in the world. In Brazil, the incidence and mortality rates of oral cancer are among the highest in the world. Intraoral cancer (tongue, gum, floor of the mouth, and other non-specified parts of the mouth), the accumulated survival rate after five years is less than 50%. Objectives: Estimate the accumulated survival probability after five years and adjust the Cox regression model for mouth and oropharyngeal cancers, according to age range, sex, morphology, and location, for the city of Natal. Describe the mortality and incidence coefficients of oral and oropharyngeal cancer and their tendencies in the city of Natal, between 1980 and 2001 and between 1997 and 2001, respectively. Methods: Survival data of patients registered between 1997 and 2001 was obtained from the Population-based Cancer Record of Natal. Differences between the survival curves were tested using the log-rank test. The Cox proportional risk model was used to estimate risk ratios. The simple linear regression model was used for tendency analyses of the mortality and incidence coefficients. Results: The probability after five years was 22.9%. The patients with undifferentiated malignant neoplasia were 4.7 times more at risk of dying than those with epidermoid carcinoma, whereas the patients with oropharyngeal cancer had 2.0 times more at risk of dying than those with mouth cancer. The mouth cancer mortality and incidence coefficients for Natal were 4.3 and 2.9 per 100 000 inhabitants, respectively. The oropharyngeal cancer mortality and incidence coefficients were, respectively, 1.1 and 0.7 per 100 000 87 inhabitants. Conclusions: A low survival rate after five years was identified. Patients with oropharyngeal cancer had a greater risk of dying, independent of the factors considered in this study. Also independent of other factors, undifferentiated malignant neoplasia posed a greater risk of death. The magnitudes of the incidence coefficients found are not considered elevated, whereas the magnitudes of the mortality coefficients are high

Estimação em modelos de tempo de falha acelerado para dados de sobrevivência correlacionados

We presented in this work two methods of estimation for accelerated failure time models with random e_ects to process grouped survival data. The _rst method, which is implemented in software SAS, by NLMIXED procedure, uses an adapted Gauss-Hermite quadrature to determine marginalized likelihood. The second method, implemented in the free software R, is based on the method of penalized likelihood to estimate the parameters of the model. In the _rst case we describe the main theoretical aspects and, in the second, we briey presented the approach adopted with a simulation study to investigate the performance of the method. We realized implement the models using actual data on the time of operation of oil wells from the Potiguar Basin (RN / CE).

Análise de resíduos em modelos de tempo de falha acelerado com efeito aleatório

We present residual analysis techniques to assess the fit of correlated survival data by Accelerated Failure Time Models (AFTM) with random effects. We propose an imputation procedure for censored observations and consider three types of residuals to evaluate different model characteristics. We illustrate the proposal with the analysis of AFTM with random effects to a real data set involving times between failures of oil well equipment

Predição em modelos de tempo de falha acelerado com efeito aleatório para avaliação de riscos de falha em poços petrolíferos

We considered prediction techniques based on models of accelerated failure time with random e ects for correlated survival data. Besides the bayesian approach through empirical Bayes estimator, we also discussed about the use of a classical predictor, the Empirical Best Linear Unbiased Predictor (EBLUP). In order to illustrate the use of these predictors, we considered applications on a real data set coming from the oil industry. More speci - cally, the data set involves the mean time between failure of petroleum-well equipments of the Bacia Potiguar. The goal of this study is to predict the risk/probability of failure in order to help a preventive maintenance program. The results show that both methods are suitable to predict future failures, providing good decisions in relation to employment and economy of resources for preventive maintenance.

Testes em modelos weibull na forma estendida de Marshall-Olkin

In survival analysis, the response is usually the time until the occurrence of an event of interest, called failure time. The main characteristic of survival data is the presence of censoring which is a partial observation of response. Associated with this information, some models occupy an important position by properly fit several practical situations, among which we can mention the Weibull model. Marshall-Olkin extended form distributions other a basic generalization that enables greater exibility in adjusting lifetime data. This paper presents a simulation study that compares the gradient test and the likelihood ratio test using the Marshall-Olkin extended form Weibull distribution. As a result, there is only a small advantage for the likelihood ratio test