Long term survival analysis: the curability of breast cancer.
ABSTRACT Methods of survival analysis for long-term follow-up studies are illustrated by a study of mortality in 3878 breast cancer patients in Edinburgh followed for up to 20 years. The problems of life tables, advantages of hazard plots and difficulties in statistical modelling are demonstrated by studying the relationship between survival and both clinical stage and initial menopausal status at diagnosis. To assess the 'curability' of breast cancer, mortality by year of follow-up is compared with expected mortality using Scottish age-specific death rates. Techniques for analysing such relative survival data include age-corrected life tables, ratio of observed to expected deaths and excess death rates. Finally, an additive hazard model is developed to incorporate covariates in the analysis of relative survival and curability.
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ABSTRACT: The consequences of introducing random effects have been a major issue in models for survival analysis. Survival models that incorporate random effects provide a useful framework for determining the effectiveness of interventions. In this paper we shall present a general approach of incorporating the random environmental effect in both univariate and multivariate models. The reliability measures, namely, the failure rate, the survival function and the mean residual life function are compared with or without the environmental effect. Examples are presented to illustrate the results.01/1998;
Article: Dormancy in breast cancer.[Show abstract] [Hide abstract]
ABSTRACT: Tumor dormancy describes a prolonged quiescent state in which tumor cells are present, but disease progression is not yet clinically apparent. Breast cancer is especially known for long asymptomatic periods, up to 25 years, with no evidence of the disease, followed by a relapse. Factors that determine the cell's decision to enter a dormant state and that control its duration remain unclear. In recent years, considerable progress has been made in understanding how tumor cells circulating in the blood interact and extravasate into secondary sites and which factors might determine whether these cells survive, remain dormant, or become macrometastases. The mechanisms of tumor cell dormancy are still not clear. Two different hypotheses are currently discussed: tumor cells persist either by completely withdrawing from the cell cycle or by continuing to proliferate at a slow rate that is counterbalanced by cell death. Because dormant disseminated tumor cells may be the founders of metastasis, one hypothesis is that dormant tumor cells, or at least a fraction of them, share stem cell-like characteristics that may be responsible for their long half-lives and their suggested resistance to standard chemotherapy. Therefore, knowledge of the biology of tumor cell dormancy may be the basis from which to develop innovative targeted therapies to control or eliminate this tumor cell fraction. In this review, we discuss biological mechanisms and clinical implications of tumor dormancy in breast cancer patients.Breast Cancer: Targets and Therapy 01/2012; 4:183-191.
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ABSTRACT: Survival data stand out as a special statistical field. This paper tries to describe what survival data is and what makes it so special. Survival data concerns times to some events. A key point is the successive observation of time, which on the one hand leads to sometimes not being observed so that all that is known is that they exceed some given times (censoring), and on the other hand implies that predictions regarding the future course should be conditional on the present status (truncation). In the simplest case, this condition is that the individual is alive. The successive conditioning makes the hazard function, which describes the probability of an event happening during a short interval given that the individual is alive today, the most relevant concept. Here we discuss parametric as well as non-parametric methods. Examples are presented in a way that can be followed without the help of computers.Indian journal of surgical oncology. 09/2012; 3(3):208-14.