Mixture Cure Survival Models with Dependent Censoring

A number of authors have studies the mixture survival model to analyze survival data with nonnegligible cure fractions. A key assumption made by these authors is the independence between the survival time and the censoring time. To our knowledge, no one has studies the mixture cure model in the presence of dependent censoring. To account for such dependence, we propose a more general cure model which allows for dependent censoring. In particular, we derive the cure models from the perspective of competing risks and model the dependence between the censoring time and the survival time using a class of Archimedean copula models. Within this framework, we consider the parameter estimation, the cure detection, and the two-sample comparison of latency distribution in the presence of dependent censoring when a proportion of patients is deemed cured. Large sample results using the martingale theory are obtained. We applied the proposed methodologies to the SEER prostate cancer data.

Nonparametric estimation of time-dependent ROC curves conditional on a continuous covariate

The receiver-operating characteristic (ROC) curve is the most widely used measure for evaluating the performance of a diagnostic biomarker when predicting a binary disease outcome. The ROC curve displays the true positive rate (or sensitivity) and the false positive rate (or 1-specificity) for different cut-off values used to classify an individual as healthy or diseased. In time-to-event studies, however, the disease status (e.g. death or alive) of an individual is not a fixed characteristic, and it varies along the study. In such cases, when evaluating the performance of the biomarker, several issues should be taken into account: first, the time-dependent nature of the disease status; and second, the presence of incomplete data (e.g. censored data typically present in survival studies). Accordingly, to assess the discrimination power of continuous biomarkers for time-dependent disease outcomes, time-dependent extensions of true positive rate, false positive rate, and ROC curve have been recently proposed. In this work, we present new nonparametric estimators of the cumulative/dynamic time-dependent ROC curve that allow accounting for the possible modifying effect of current or past covariate measures on the discriminatory power of the biomarker. The proposed estimators can accommodate right-censored data, as well as covariate-dependent censoring. The behavior of the estimators proposed in this study will be explored through simulations and illustrated using data from a cohort of patients who suffered from acute coronary syndrome.

Statistical analysis of survey-based event history data with application to modeling of unemployment duration

Longitudinal surveys are increasingly used to collect event history data on person-specific processes such as transitions between labour market states. Surveybased event history data pose a number of challenges for statistical analysis. These challenges include survey errors due to sampling, non-response, attrition and measurement. This study deals with non-response, attrition and measurement errors in event history data and the bias caused by them in event history analysis. The study also discusses some choices faced by a researcher using longitudinal survey data for event history analysis and demonstrates their effects. These choices include, whether a design-based or a model-based approach is taken, which subset of data to use and, if a design-based approach is taken, which weights to use. The study takes advantage of the possibility to use combined longitudinal survey register data. The Finnish subset of European Community Household Panel (FI ECHP) survey for waves 1–5 were linked at person-level with longitudinal register data. Unemployment spells were used as study variables of interest. Lastly, a simulation study was conducted in order to assess the statistical properties of the Inverse Probability of Censoring Weighting (IPCW) method in a survey data context. The study shows how combined longitudinal survey register data can be used to analyse and compare the non-response and attrition processes, test the missingness mechanism type and estimate the size of bias due to non-response and attrition. In our empirical analysis, initial non-response turned out to be a more important source of bias than attrition. Reported unemployment spells were subject to seam effects, omissions, and, to a lesser extent, overreporting. The use of proxy interviews tended to cause spell omissions. An often-ignored phenomenon classification error in reported spell outcomes, was also found in the data. Neither the Missing At Random (MAR) assumption about non-response and attrition mechanisms, nor the classical assumptions about measurement errors, turned out to be valid. Both measurement errors in spell durations and spell outcomes were found to cause bias in estimates from event history models. Low measurement accuracy affected the estimates of baseline hazard most. The design-based estimates based on data from respondents to all waves of interest and weighted by the last wave weights displayed the largest bias. Using all the available data, including the spells by attriters until the time of attrition, helped to reduce attrition bias. Lastly, the simulation study showed that the IPCW correction to design weights reduces bias due to dependent censoring in design-based Kaplan-Meier and Cox proportional hazard model estimators. The study discusses implications of the results for survey organisations collecting event history data, researchers using surveys for event history analysis, and researchers who develop methods to correct for non-sampling biases in event history data.

Analyzing Panel Count Data with Informative Observation Times

In this paper, we study panel count data with informative observation times. We assume nonparametric and semiparametric proportional rate models for the underlying recurrent event process, where the form of the baseline rate function is left unspecified and a subject-specific frailty variable inflates or deflates the rate function multiplicatively. The proposed models allow the recurrent event processes and observation times to be correlated through their connections with the unobserved frailty; moreover, the distributions of both the frailty variable and observation times are considered as nuisance parameters. The baseline rate function and the regression parameters are estimated by maximizing a conditional likelihood function of observed event counts and solving estimation equations. Large sample properties of the proposed estimators are studied. Numerical studies demonstrate that the proposed estimation procedures perform well for moderate sample sizes. An application to a bladder tumor study is presented to illustrate the use of the proposed methods.

Modeling grouped survival data with time-dependent covariates

In this article, proportional hazards and logistic models for grouped survival data were extended to incorporate time-dependent covariates. The extension was motivated by a forestry experiment designed to compare five different water stresses in Eucalyptus grandis seedlings. The response was the seedling lifetime. The data set was grouped since there were just three occasions in which the seedlings was visited by the researcher. In each of these occasions also the shoot height was measured and therefore it is a time-dependent covariate. Both extended models were used in this example, and the results were very similar.

Effects of informative censoring on the hazard function: Application to the proportional hazards regression model

The standard analyses of survival data involve the assumption that survival and censoring are independent. When censoring and survival are related, the phenomenon is known as informative censoring. This paper examines the effects of an informative censoring assumption on the hazard function and the estimated hazard ratio provided by the Cox model.^ The limiting factor in all analyses of informative censoring is the problem of non-identifiability. Non-identifiability implies that it is impossible to distinguish a situation in which censoring and death are independent from one in which there is dependence. However, it is possible that informative censoring occurs. Examination of the literature indicates how others have approached the problem and covers the relevant theoretical background.^ Three models are examined in detail. The first model uses conditionally independent marginal hazards to obtain the unconditional survival function and hazards. The second model is based on the Gumbel Type A method for combining independent marginal distributions into bivariate distributions using a dependency parameter. Finally, a formulation based on a compartmental model is presented and its results described. For the latter two approaches, the resulting hazard is used in the Cox model in a simulation study.^ The unconditional survival distribution formed from the first model involves dependency, but the crude hazard resulting from this unconditional distribution is identical to the marginal hazard, and inferences based on the hazard are valid. The hazard ratios formed from two distributions following the Gumbel Type A model are biased by a factor dependent on the amount of censoring in the two populations and the strength of the dependency of death and censoring in the two populations. The Cox model estimates this biased hazard ratio. In general, the hazard resulting from the compartmental model is not constant, even if the individual marginal hazards are constant, unless censoring is non-informative. The hazard ratio tends to a specific limit.^ Methods of evaluating situations in which informative censoring is present are described, and the relative utility of the three models examined is discussed. ^

The number and timing of time -dependent covariate measurements for the Cox regression model

The problem of analyzing data with updated measurements in the time-dependent proportional hazards model arises frequently in practice. One available option is to reduce the number of intervals (or updated measurements) to be included in the Cox regression model. We empirically investigated the bias of the estimator of the time-dependent covariate while varying the effect of failure rate, sample size, true values of the parameters and the number of intervals. We also evaluated how often a time-dependent covariate needs to be collected and assessed the effect of sample size and failure rate on the power of testing a time-dependent effect.^ A time-dependent proportional hazards model with two binary covariates was considered. The time axis was partitioned into k intervals. The baseline hazard was assumed to be 1 so that the failure times were exponentially distributed in the ith interval. A type II censoring model was adopted to characterize the failure rate. The factors of interest were sample size (500, 1000), type II censoring with failure rates of 0.05, 0.10, and 0.20, and three values for each of the non-time-dependent and time-dependent covariates (1/4,1/2,3/4).^ The mean of the bias of the estimator of the coefficient of the time-dependent covariate decreased as sample size and number of intervals increased whereas the mean of the bias increased as failure rate and true values of the covariates increased. The mean of the bias of the estimator of the coefficient was smallest when all of the updated measurements were used in the model compared with two models that used selected measurements of the time-dependent covariate. For the model that included all the measurements, the coverage rates of the estimator of the coefficient of the time-dependent covariate was in most cases 90% or more except when the failure rate was high (0.20). The power associated with testing a time-dependent effect was highest when all of the measurements of the time-dependent covariate were used. An example from the Systolic Hypertension in the Elderly Program Cooperative Research Group is presented. ^

Treadmill Training Increases Sirt-1 And Pgc-1 α Protein Levels And Ampk Phosphorylation In Quadriceps Of Middle-aged Rats In An Intensity-dependent Manner.

The present study investigated the effects of running at 0.8 or 1.2 km/h on inflammatory proteins (i.e., protein levels of TNF- α , IL-1 β , and NF- κ B) and metabolic proteins (i.e., protein levels of SIRT-1 and PGC-1 α , and AMPK phosphorylation) in quadriceps of rats. Male Wistar rats at 3 (young) and 18 months (middle-aged rats) of age were divided into nonexercised (NE) and exercised at 0.8 or 1.2 km/h. The rats were trained on treadmill, 50 min per day, 5 days per week, during 8 weeks. Forty-eight hours after the last training session, muscles were removed, homogenized, and analyzed using biochemical and western blot techniques. Our results showed that: (a) running at 0.8 km/h decreased the inflammatory proteins and increased the metabolic proteins compared with NE rats; (b) these responses were lower for the inflammatory proteins and higher for the metabolic proteins in young rats compared with middle-aged rats; (c) running at 1.2 km/h decreased the inflammatory proteins and increased the metabolic proteins compared with 0.8 km/h; (d) these responses were similar between young and middle-aged rats when trained at 1.2 km. In summary, the age-related increases in inflammatory proteins, and the age-related declines in metabolic proteins can be reversed and largely improved by treadmill training.

Toll-like Receptor 4 Activation Promotes Cardiac Arrhythmias By Decreasing The Transient Outward Potassium Current (ito) Through An Irf3-dependent And Myd88-independent Pathway.

Cardiac arrhythmias are one of the main causes of death worldwide. Several studies have shown that inflammation plays a key role in different cardiac diseases and Toll-like receptors (TLRs) seem to be involved in cardiac complications. In the present study, we investigated whether the activation of TLR4 induces cardiac electrical remodeling and arrhythmias, and the signaling pathway involved in these effects. Membrane potential was recorded in Wistar rat ventricle. Ca(2+) transients, as well as the L-type Ca(2+) current (ICaL) and the transient outward K(+) current (Ito), were recorded in isolated myocytes after 24 h exposure to the TLR4 agonist, lipopolysaccharide (LPS, 1 μg/ml). TLR4 stimulation in vitro promoted a cardiac electrical remodeling that leads to action potential prolongation associated with arrhythmic events, such as delayed afterdepolarization and triggered activity. After 24 h LPS incubation, Ito amplitude, as well as Kv4.3 and KChIP2 mRNA levels were reduced. The Ito decrease by LPS was prevented by inhibition of interferon regulatory factor 3 (IRF3), but not by inhibition of interleukin-1 receptor-associated kinase 4 (IRAK4) or nuclear factor kappa B (NF-κB). Extrasystolic activity was present in 25% of the cells, but apart from that, Ca(2+) transients and ICaL were not affected by LPS; however, Na(+)/Ca(2+) exchanger (NCX) activity was apparently increased. We conclude that TLR4 activation decreased Ito, which increased AP duration via a MyD88-independent, IRF3-dependent pathway. The longer action potential, associated with enhanced Ca(2+) efflux via NCX, could explain the presence of arrhythmias in the LPS group.

Endocytosis Of Tight Junctions Caveolin Nitrosylation Dependent Is Improved By Cocoa Via Opioid Receptor On Rpe Cells In Diabetic Conditions.

Retinal pigment epithelium cells, along with tight junction (TJ) proteins, constitute the outer blood retinal barrier (BRB). Contradictory findings suggest a role for the outer BRB in the pathogenesis of diabetic retinopathy (DR). The aim of this study was to investigate whether the mechanisms involved in these alterations are sensitive to nitrosative stress, and if cocoa or epicatechin (EC) protects from this damage under diabetic (DM) milieu conditions. Cells of a human RPE line (ARPE-19) were exposed to high-glucose (HG) conditions for 24 hours in the presence or absence of cocoa powder containing 0.5% or 60.5% polyphenol (low-polyphenol cocoa [LPC] and high-polyphenol cocoa [HPC], respectively). Exposure to HG decreased claudin-1 and occludin TJ expressions and increased extracellular matrix accumulation (ECM), whereas levels of TNF-α and inducible nitric oxide synthase (iNOS) were upregulated, accompanied by increased nitric oxide levels. This nitrosative stress resulted in S-nitrosylation of caveolin-1 (CAV-1), which in turn increased CAV-1 traffic and its interactions with claudin-1 and occludin. This cascade was inhibited by treatment with HPC or EC through δ-opioid receptor (DOR) binding and stimulation, thereby decreasing TNF-α-induced iNOS upregulation and CAV-1 endocytosis. The TJ functions were restored, leading to prevention of paracellular permeability, restoration of resistance of the ARPE-19 monolayer, and decreased ECM accumulation. The detrimental effects on TJs in ARPE-19 cells exposed to DM milieu occur through a CAV-1 S-nitrosylation-dependent endocytosis mechanism. High-polyphenol cocoa or EC exerts protective effects through DOR stimulation.

Sci1 Is A Component Of The Auxin-dependent Control Of Cell Proliferation In Arabidopsis Upper Pistil.

To characterize the recently described SCI1 (stigma/style cell cycle inhibitor 1) gene relationship with the auxin pathway, we have taken the advantage of the Arabidopsis model system and its available tools. At first, we have analyzed the At1g79200 T-DNA insertion mutants and constructed various transgenic plants. The loss- and gain-of-function plants displayed cell number alterations in upper pistils that were controlled by the amino-terminal domain of the protein. These data also confirmed that this locus holds the functional homolog (AtSCI1) of the Nicotiana tabacum SCI1 gene. Then, we have provided some evidences the auxin synthesis/signaling pathways are required for downstream proper AtSCI1 control of cell number: (a) its expression is downregulated in yuc2yuc6 and npy1 auxin-deficient mutants, (b) triple (yuc2yuc6sci1) and double (npy1sci1) mutants mimicked the auxin-deficient phenotypes, with no synergistic interactions, and (c) the increased upper pistil phenotype in these last mutants, which is a consequence of an increased cell number, was able to be complemented by AtSCI1 overexpression. Taken together, our data strongly suggests SCI1 as a component of the auxin signaling transduction pathway to control cell proliferation/differentiation in stigma/style, representing a molecular effector of this hormone on pistil development.

Enhanced Endothelium-dependent Relaxation Of Rat Pulmonary Artery Following β-adrenergic Overstimulation: Involvement Of The No/cgmp/vasp Pathway.

The aim of this study was to investigate whether β-adrenoceptor (β-AR) overstimulation induced by in vivo treatment with isoproterenol (ISO) alters vascular reactivity and nitric oxide (NO) production and signaling in pulmonary arteries. Vehicle or ISO (0.3mgkg(-1)day(-1)) was administered daily to male Wistar rats. After 7days, the jugular vein was cannulated to assess right ventricular (RV) systolic pressure (SP) and end diastolic pressure (EDP). The extralobar pulmonary arteries were isolated to evaluate the relaxation responses, protein expression (Western blot), NO production (diaminofluorescein-2 fluorescence), and cyclic guanosine 3',5'-monophosphate (cGMP) levels (enzyme immunoassay kit). ISO treatment induced RV hypertrophy; however, no differences in RV-SP and EDP were observed. The pulmonary arteries from the ISO-treated group showed enhanced relaxation to acetylcholine that was abolished by the NO synthase (NOS) inhibitor N(ω)-nitro-l-arginine methyl ester (l-NAME); whereas relaxation elicited by sodium nitroprusside, ISO, metaproterenol, mirabegron, or KCl was not affected by ISO treatment. ISO-treated rats displayed enhanced endothelial NOS (eNOS) and vasodilator-stimulated phosphoprotein (VASP) expression in the pulmonary arteries, while phosphodiesterase-5 protein expression decreased. ISO treatment increased NO and cGMP levels and did not induce eNOS uncoupling. The present data indicate that β-AR overactivation enhances the endothelium-dependent relaxation of pulmonary arteries. This effect was linked to an increase in eNOS-derived NO production, cGMP formation and VASP content and to a decrease in phosphodiesterase-5 expression. Therefore, elevated NO bioactivity through cGMP/VASP signaling could represent a protective mechanism of β-AR overactivation on pulmonary circulation.