Testes de hipóteses em modelos de sobrevivência com Fração de cura

Survival models deals with the modeling of time to event data. However in some situations part of the population may be no longer subject to the event. Models that take this fact into account are called cure rate models. There are few studies about hypothesis tests in cure rate models. Recently a new test statistic, the gradient statistic, has been proposed. It shares the same asymptotic properties with the classic large sample tests, the likelihood ratio, score and Wald tests. Some simulation studies have been carried out to explore the behavior of the gradient statistic in fi nite samples and compare it with the classic statistics in diff erent models. The main objective of this work is to study and compare the performance of gradient test and likelihood ratio test in cure rate models. We first describe the models and present the main asymptotic properties of the tests. We perform a simulation study based on the promotion time model with Weibull distribution to assess the performance of the tests in finite samples. An application is presented to illustrate the studied concepts

Modelos de sobrevivência com fração de cura e erro de medida nas covariáveis

In this work, we study the survival cure rate model proposed by Yakovlev et al. (1993), based on a competing risks structure concurring to cause the event of interest, and the approach proposed by Chen et al. (1999), where covariates are introduced to model the risk amount. We focus the measurement error covariates topics, considering the use of corrected score method in order to obtain consistent estimators. A simulation study is done to evaluate the behavior of the estimators obtained by this method for finite samples. The simulation aims to identify not only the impact on the regression coefficients of the covariates measured with error (Mizoi et al. 2007) but also on the coefficients of covariates measured without error. We also verify the adequacy of the piecewise exponential distribution to the cure rate model with measurement error. At the end, model applications involving real data are made

Modelos de sobrevivência com fração de cura e omissão nas covariáveis

In this work we study the survival cure rate model proposed by Yakovlev (1993) that are considered in a competing risk setting. Covariates are introduced for modeling the cure rate and we allow some covariates to have missing values. We consider only the cases by which the missing covariates are categorical and implement the EM algorithm via the method of weights for maximum likelihood estimation. We present a Monte Carlo simulation experiment to compare the properties of the estimators based on this method with those estimators under the complete case scenario. We also evaluate, in this experiment, the impact in the parameter estimates when we increase the proportion of immune and censored individuals among the not immune one. We demonstrate the proposed methodology with a real data set involving the time until the graduation for the undergraduate course of Statistics of the Universidade Federal do Rio Grande do Norte

Frequência e significado clínico da expressão da glicoproteína P e da proteína relacionada a resistência a múltiplas drogas na leucemia mielóide aguda

Despite the advances in the cure rate for acute myeloid leukemia, a considerable number of patients die from their disease due to the occurrence of multidrug resistance (MDR). Overexpression of the transporter proteins P-glycoprotein (Pgp) and multidrug resistance-associated protein (MRP) confer resistance to the treatment these leukemias. OBJECTIVE: To analyze the expression of the Gpp and MRP1 in patients with AML by flow cytometry (FC) and to determine the correlation between expression and demographic and also clinical and laboratorial variables. METHODS: Bone marrow and peripheral blood samples from 346 patients with a diagnosis of AML were assessed for the expression of Pgp and MRP1 by FC. RESULTS: The expression of Pgp and MRP1 was found in 111 (32.1%) and 133 (38.4%) patients, respectively, with greater prevalence in older patients and lower in adolescents, observing also a high incidence in patients with refractory disease, recurrence and secondary in comparison with the cases of de novo AML. Regarding the laboratory findings, we observed a higher correlation statistically significant between the expression of Pgp and MRP1 in AML CD34+ and FAB AML M7, M5A and M2 and lower the M3 subtype, not observed statistically significant correlation between the phenotype MDR and other laboratory data such with hemoglobin, leukocyte count, platelet count, aberrant expression of lymphoid antigens (CD2, CD7 and CD19) and clinical signs related to the disease. CONCLUSIONS: The results showed that the detection of MDR phenotype by flow cytometry can be a molecular marker for prognosis independent patients diagnosed with AML.

Avaliação e correções de testes de hipóteses em modelos de sobrevivência com fração de cura

Survival models deals with the modelling of time to event data. In certain situations, a share of the population can no longer be subjected to the event occurrence. In this context, the cure fraction models emerged. Among the models that incorporate a fraction of cured one of the most known is the promotion time model. In the present study we discuss hypothesis testing in the promotion time model with Weibull distribution for the failure times of susceptible individuals. Hypothesis testing in this model may be performed based on likelihood ratio, gradient, score or Wald statistics. The critical values are obtained from asymptotic approximations, which may result in size distortions in nite sample sizes. This study proposes bootstrap corrections to the aforementioned tests and Bartlett bootstrap to the likelihood ratio statistic in Weibull promotion time model. Using Monte Carlo simulations we compared the nite sample performances of the proposed corrections in contrast with the usual tests. The numerical evidence favors the proposed corrected tests. At the end of the work an empirical application is presented.