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 clássica e Bayesiana em modelos de sobrevida com fração de cura

In Survival Analysis, long duration models allow for the estimation of the healing fraction, which represents a portion of the population immune to the event of interest. Here we address classical and Bayesian estimation based on mixture models and promotion time models, using different distributions (exponential, Weibull and Pareto) to model failure time. The database used to illustrate the implementations is described in Kersey et al. (1987) and it consists of a group of leukemia patients who underwent a certain type of transplant. The specific implementations used were numeric optimization by BFGS as implemented in R (base::optim), Laplace approximation (own implementation) and Gibbs sampling as implemented in Winbugs. We describe the main features of the models used, the estimation methods and the computational aspects. We also discuss how different prior information can affect the Bayesian estimates