A multiple time scale survival model with a cure fraction

Many recent survival studies propose modeling data with a cure fraction, i.e., data in which part of the population is not susceptible to the event of interest. This event may occur more than once for the same individual (recurrent event). We then have a scenario of recurrent event data in the presence of a cure fraction, which may appear in various areas such as oncology, finance, industries, among others. This paper proposes a multiple time scale survival model to analyze recurrent events using a cure fraction. The objective is analyzing the efficiency of certain interventions so that the studied event will not happen again in terms of covariates and censoring. All estimates were obtained using a sampling-based approach, which allows information to be input beforehand with lower computational effort. Simulations were done based on a clinical scenario in order to observe some frequentist properties of the estimation procedure in the presence of small and moderate sample sizes. An application of a well-known set of real mammary tumor data is provided.

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.

The polysurvival model with long-term survivors

Long-term survival models have historically been considered for analyzing time-to-event data with long-term survivors fraction. However, situations in which a fraction (1 - p) of systems is subject to failure from independent competing causes of failure, while the remaining proportion p is cured or has not presented the event of interest during the time period of the study, have not been fully considered in the literature. In order to accommodate such situations, we present in this paper a new long-term survival model. Maximum likelihood estimation procedure is discussed as well as interval estimation and hypothesis tests. A real dataset illustrates the methodology.

A Bayesian destructive weighted Poisson cure rate model and an application to a cutaneous melanoma data

In this article, we propose a new Bayesian flexible cure rate survival model, which generalises the stochastic model of Klebanov et al. [Klebanov LB, Rachev ST and Yakovlev AY. A stochastic-model of radiation carcinogenesis - latent time distributions and their properties. Math Biosci 1993; 113: 51-75], and has much in common with the destructive model formulated by Rodrigues et al. [Rodrigues J, de Castro M, Balakrishnan N and Cancho VG. Destructive weighted Poisson cure rate models. Technical Report, Universidade Federal de Sao Carlos, Sao Carlos-SP. Brazil, 2009 (accepted in Lifetime Data Analysis)]. In our approach, the accumulated number of lesions or altered cells follows a compound weighted Poisson distribution. This model is more flexible than the promotion time cure model in terms of dispersion. Moreover, it possesses an interesting and realistic interpretation of the biological mechanism of the occurrence of the event of interest as it includes a destructive process of tumour cells after an initial treatment or the capacity of an individual exposed to irradiation to repair altered cells that results in cancer induction. In other words, what is recorded is only the damaged portion of the original number of altered cells not eliminated by the treatment or repaired by the repair system of an individual. Markov Chain Monte Carlo (MCMC) methods are then used to develop Bayesian inference for the proposed model. Also, some discussions on the model selection and an illustration with a cutaneous melanoma data set analysed by Rodrigues et al. [Rodrigues J, de Castro M, Balakrishnan N and Cancho VG. Destructive weighted Poisson cure rate models. Technical Report, Universidade Federal de Sao Carlos, Sao Carlos-SP. Brazil, 2009 (accepted in Lifetime Data Analysis)] are presented.

Higher incidence of death in multi-vessel coronary artery disease patients associated with polymorphisms in chromosome 9p21

Background: We investigated whether 9p21 polymorphisms are associated with cardiovascular events in a group of 611 patients enrolled in the Medical, Angioplasty or Surgery Study II (MASS II), a randomized trial comparing treatments for patients with coronary artery disease (CAD) and preserved left ventricular function. Methods: The participants of the MASS II were genotyped for 9p21 polymorphisms (rs10757274, rs2383206, rs10757278 and rs1333049). Survival curves were calculated with the Kaplan-Meier method and compared with the log-rank statistic. We assessed the relationship between baseline variables and the composite end-point of death, death from cardiac causes and myocardial infarction using a Cox proportional hazards survival model. Results: We observed significant differences between patients within each polymorphism genotype group for baseline characteristics. The frequency of diabetes was lower in patients carrying GG genotype for rs10757274, rs2383206 and rs10757278 (29.4%, 32.8%, 32.0%) compared to patients carrying AA or AG genotypes (49.1% and 39.2%, p = 0.01; 52.4% and 40.1%, p = 0.01; 47.8% and 37.9%, p = 0.04; respectively). Significant differences in genotype frequencies between double and triple vessel disease patients were observed for the rs10757274, rs10757278 and rs1333049. Finally, there was a higher incidence of overall mortality in patients with the GG genotype for rs2383206 compared to patients with AA and AG genotypes (19.5%, 11.9%, 11.0%, respectively; p = 0.04). Moreover, the rs2383206 was still significantly associated with a 1.75-fold increased risk of overall mortality (p = 0.02) even after adjustment of a Cox multivariate model for age, previous myocardial infarction, diabetes, smoking and type of coronary anatomy. Conclusions: Our data are in accordance to previous evidence that chromosome 9p21 genetic variation may constitute a genetic modulator in the cardiovascular system in different scenarios. In patients with established CAD, we observed an association between the rs2383206 and higher incidence of overall mortality and death from cardiac causes in patients with multi-vessel CAD.

Stigma and higher rates of psychiatric re-hospitalization: Sao Paulo public mental health system

Objective: The aim of this study was to assess re-hospitalization rates of individuals with psychosis and bipolar disorder and to study determinants of readmission. Methods: Prospective observational study, conducted in Sao Paulo, Brazil. One hundred-sixty-nine individuals with bipolar and psychotic disorder in need of hospitalization in the public mental health system were followed for 12 months after discharge. Their families were contacted by telephone and interviews were conducted at 1, 2, 6 and 12 months post-discharge to evaluate readmission rates and factors related. Results: One-year re-hospitalization rate was of 42.6%. Physical restraint during hospital stay was a risk factor (OR = 5.4-10.5) for readmission in most models. Not attending consultations after discharge was related to the 12-month point readmission (OR = 8.5, 95% CI 2.3-31.2) and to the survival model (OR = 3.2, 95% CI 1.5-7.2). Number of previous admissions was a risk factor for the survival model (OR = 6.6-11.9). Family's agreement with permanent hospitalization of individuals with mental illness was the predictor associated to readmission in all models (OR = 3.5-10.9) and resulted in shorter survival time to readmission; those readmitted were stereotyped as dangerous and unhealthy. Conclusions: Family's stigma towards mental illness might contribute to the increase in readmission rates of their relatives with psychiatric disorders. More studies should be conducted to depict mechanisms by which stigma increases re-hospitalization rates.

Lung cancer symptoms and pulse oximetry in the prognostic assessment of patients with lung cancer

Abstract Background Medical oncologists continue to use performance status as a proxy for quality of life (QOL) measures, as completion of QOL instruments is perceived as time consuming, may measure aspects of QOL not affected by cancer therapy, and interpretation may be unclear. The pulse oximeter is widely used in clinical practice to predict cardiopulmonary morbidity after lung resection in cancer patients, but little is known on its role outside the surgical setting. We evaluated whether the Lung Cancer Symptom Scale and pulse oximetry may contribute to the evaluation of lung cancer patients who received standard anticancer therapy. Methods We enrolled forty-one consecutive, newly diagnosed, patients with locally advanced or metastatic lung cancer in this study. We developed a survival model with the variables gender, age, histology, clinical stage, Karnofsky performance status, wasting, LCSS symptom scores, average symptom burden index, and pulse oximetry (SpO2). Results Patient and observer-rated scores were correlated, except for the fatigue subscale. The median SpO2 was 95% (range: 86 to 98), was unrelated to symptom scores, and was weakly correlated with observer cough scores. In a multivariate survival model, SpO2 > 90% and patient scores on the LCSS appetite and fatigue subscales were independent predictors of survival. Conclusion LCSS fatigue and appetite rating, and pulse oximetry should be studied further as prognostic factors in lung cancer patients.

Association between UCP2 A55V polymorphism and risk of cardiovascular events in patients with multi-vessel coronary arterial disease

Background UCP2 (uncoupling protein 2) plays an important role in cardiovascular diseases and recent studies have suggested that the A55V polymorphism can cause UCP2 dysfunction. The main aim was to investigate the association of A55V polymorphism with cardiovascular events in a group of 611 patients enrolled in the Medical, Angioplasty or Surgery Study II (MASS II), a randomized trial comparing treatments for patients with coronary artery disease and preserved left ventricular function. Methods The participants of the MASS II were genotyped for the A55V polymorphism using allele-specific PCR assay. Survival curves were calculated with the Kaplan–Meier method and evaluated with the log-rank statistic. The relationship between baseline variables and the composite end-point of cardiac death, acute myocardial infarction (AMI), refractory angina requiring revascularization and cerebrovascular accident were assessed using a Cox proportional hazards survival model. Results There were no significant differences for baseline variables according genotypes. After 2 years of follow-up, dysglycemic patients harboring the VV genotype had higher occurrence of AMI (p=0.026), Death+AMI (p=0.033), new revascularization intervention (p=0.009) and combined events (p=0.037) as compared with patients carrying other genotypes. This association was not evident in normoglycemic patients. Conclusions These findings support the hypothesis that A55V polymorphism is associated with UCP2 functional alterations that increase the risk of cardiovascular events in patients with previous coronary artery disease and dysglycemia.

Stigma and higher rates of psychiatric re-hospitalization: São Paulo public mental health system

OBJECTIVE: The aim of this study was to assess re-hospitalization rates of individuals with psychosis and bipolar disorder and to study determinants of readmission. METHODS: Prospective observational study, conducted in São Paulo, Brazil. One hundred-sixty-nine individuals with bipolar and psychotic disorder in need of hospitalization in the public mental health system were followed for 12 months after discharge. Their families were contacted by telephone and interviews were conducted at 1, 2, 6 and 12 months post-discharge to evaluate readmission rates and factors related. RESULTSOne-year re-hospitalization rate was of 42.6%. Physical restraint during hospital stay was a risk factor (OR = 5.4-10.5) for readmission in most models. Not attending consultations after discharge was related to the 12-month point readmission (OR = 8.5, 95%CI 2.3-31.2) and to the survival model (OR = 3.2, 95%CI 1.5-7.2). Number of previous admissions was a risk factor for the survival model (OR = 6.6-11.9). Family's agreement with permanent hospitalization of individuals with mental illness was the predictor associated to readmission in all models (OR = 3.5-10.9) and resulted in shorter survival time to readmission; those readmitted were stereotyped as dangerous and unhealthy. CONCLUSIONS: Family's stigma towards mental illness might contribute to the increase in readmission rates of their relatives with psychiatric disorders. More studies should be conducted to depict mechanisms by which stigma increases re-hospitalization rates.

THE LOG-BURR XII REGRESSION MODEL FOR GROUPED SURVIVAL DATA

The log-Burr XII regression model for grouped survival data is evaluated in the presence of many ties. The methodology for grouped survival data is based on life tables, where the times are grouped in k intervals, and we fit discrete lifetime regression models to the data. The model parameters are estimated by maximum likelihood and jackknife methods. To detect influential observations in the proposed model, diagnostic measures based on case deletion, so-called global influence, and influence measures based on small perturbations in the data or in the model, referred to as local influence, are used. In addition to these measures, the total local influence and influential estimates are also used. We conduct Monte Carlo simulation studies to assess the finite sample behavior of the maximum likelihood estimators of the proposed model for grouped survival. A real data set is analyzed using a regression model for grouped data.

Stripe-tetragonal phase transition in the two-dimensional Ising model with dipole interactions: Partition function zeros approach

We have performed multicanonical simulations to study the critical behavior of the two-dimensional Ising model with dipole interactions. This study concerns the thermodynamic phase transitions in the range of the interaction delta where the phase characterized by striped configurations of width h = 1 is observed. Controversial results obtained from local update algorithms have been reported for this region, including the claimed existence of a second-order phase transition line that becomes first order above a tricritical point located somewhere between delta = 0.85 and 1. Our analysis relies on the complex partition function zeros obtained with high statistics from multicanonical simulations. Finite size scaling relations for the leading partition function zeros yield critical exponents. that are clearly consistent with a single second-order phase transition line, thus excluding such a tricritical point in that region of the phase diagram. This conclusion is further supported by analysis of the specific heat and susceptibility of the orientational order parameter.

A general threshold stress hybrid hazard model for lifetime data

In this paper we propose a hybrid hazard regression model with threshold stress which includes the proportional hazards and the accelerated failure time models as particular cases. To express the behavior of lifetimes the generalized-gamma distribution is assumed and an inverse power law model with a threshold stress is considered. For parameter estimation we develop a sampling-based posterior inference procedure based on Markov Chain Monte Carlo techniques. We assume proper but vague priors for the parameters of interest. A simulation study investigates the frequentist properties of the proposed estimators obtained under the assumption of vague priors. Further, some discussions on model selection criteria are given. The methodology is illustrated on simulated and real lifetime data set.

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.

Stickiness in a bouncer model: A slowing mechanism for Fermi acceleration

Some phase space transport properties for a conservative bouncer model are studied. The dynamics of the model is described by using a two-dimensional measure preserving mapping for the variables' velocity and time. The system is characterized by a control parameter epsilon and experiences a transition from integrable (epsilon = 0) to nonintegrable (epsilon not equal 0). For small values of epsilon, the phase space shows a mixed structure where periodic islands, chaotic seas, and invariant tori coexist. As the parameter epsilon increases and reaches a critical value epsilon(c), all invariant tori are destroyed and the chaotic sea spreads over the phase space, leading the particle to diffuse in velocity and experience Fermi acceleration (unlimited energy growth). During the dynamics the particle can be temporarily trapped near periodic and stable regions. We use the finite time Lyapunov exponent to visualize this effect. The survival probability was used to obtain some of the transport properties in the phase space. For large epsilon, the survival probability decays exponentially when it turns into a slower decay as the control parameter epsilon is reduced. The slower decay is related to trapping dynamics, slowing the Fermi Acceleration, i.e., unbounded growth of the velocity.

Development, characterization, and in vitro trials of chloroaluminum phthalocyanine-magnetic nanoemulsion to hyperthermia and photodynamic therapies on glioblastoma as a biological model

A glioblastoma multiforme (GBM) is the highest grade glioma tumor (grade IV) and is the most malignant form of astrocytomas. Grade IV tumors, which are the most malignant and aggressive, affect people between the ages of 45 and 70 years. A GBM exhibits remarkable characteristics that include excessive proliferation, necrosis, genetic instability, and chemoresistance. Because of these characteristics, GBMs are difficult to treat and have a poor prognosis with a median survival of less than one year. New methods to achieve widespread distribution of therapeutic agents across infiltrative gliomas significantly improve brain tumor therapy. Photodynamic therapy (PDT) and hyperthermia (HPT) are well-established tumor therapies with minimal side effects while acting synergistically. This study introduces a new promising nanocarrier for the synergistic application of PDT and magnetic hyperthermia therapy against human glioma cell line T98 G, with cellular viability reduction down to as low as 17% compared with the control. (C) 2012 American Institute of Physics. [doi:10.1063/1.3671775]