Different Approaches for Modeling Grouped Survival Data: A Mango Tree Study

Interval-censored survival data, in which the event of interest is not observed exactly but is only known to occur within some time interval, occur very frequently. In some situations, event times might be censored into different, possibly overlapping intervals of variable widths; however, in other situations, information is available for all units at the same observed visit time. In the latter cases, interval-censored data are termed grouped survival data. Here we present alternative approaches for analyzing interval-censored data. We illustrate these techniques using a survival data set involving mango tree lifetimes. This study is an example of grouped survival data.

Log-modified Weibull regression models with censored data: Sensitivity and residual analysis

This paper proposes a regression model considering the modified Weibull distribution. This distribution can be used to model bathtub-shaped failure rate functions. Assuming censored data, we consider maximum likelihood and Jackknife estimators for the parameters of the model. We derive the appropriate matrices for assessing local influence on the parameter estimates under different perturbation schemes and we also present some ways to perform global influence. Besides, for different parameter settings, sample sizes and censoring percentages, various simulations are performed and the empirical distribution of the modified deviance residual is displayed and compared with the standard normal distribution. These studies suggest that the residual analysis usually performed in normal linear regression models can be straightforwardly extended for a martingale-type residual in log-modified Weibull regression models with censored data. Finally, we analyze a real data set under log-modified Weibull regression models. A diagnostic analysis and a model checking based on the modified deviance residual are performed to select appropriate models. (c) 2008 Elsevier B.V. All rights reserved.

On estimation and influence diagnostics for zero-inflated negative binomial regression models

The zero-inflated negative binomial model is used to account for overdispersion detected in data that are initially analyzed under the zero-Inflated Poisson model A frequentist analysis a jackknife estimator and a non-parametric bootstrap for parameter estimation of zero-inflated negative binomial regression models are considered In addition an EM-type algorithm is developed for performing maximum likelihood estimation Then the appropriate matrices for assessing local influence on the parameter estimates under different perturbation schemes and some ways to perform global influence analysis are derived In order to study departures from the error assumption as well as the presence of outliers residual analysis based on the standardized Pearson residuals is discussed The relevance of the approach is illustrated with a real data set where It is shown that zero-inflated negative binomial regression models seems to fit the data better than the Poisson counterpart (C) 2010 Elsevier B V All rights reserved

Regression models for grouped survival data: Estimation and sensitivity analysis

In this study, regression models are evaluated for grouped survival data when the effect of censoring time is considered in the model and the regression structure is modeled through four link functions. The methodology for grouped survival data is based on life tables, and the times are grouped in k intervals so that ties are eliminated. Thus, the data modeling is performed by considering the discrete models of lifetime regression. The model parameters are estimated by using the maximum likelihood and jackknife methods. To detect influential observations in the proposed models, diagnostic measures based on case deletion, which are denominated 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 those measures, the local influence and the total influential estimate are also employed. Various simulation studies are performed and compared to the performance of the four link functions of the regression models for grouped survival data for different parameter settings, sample sizes and numbers of intervals. Finally, a data set is analyzed by using the proposed regression models. (C) 2010 Elsevier B.V. All rights reserved.

Parametric correlation functions to model the structure of permanent environmental (co)variances in milk yield random regression models

The objective of the present study was to estimate milk yield genetic parameters applying random regression models and parametric correlation functions combined with a variance function to model animal permanent environmental effects. A total of 152,145 test-day milk yields from 7,317 first lactations of Holstein cows belonging to herds located in the southeastern region of Brazil were analyzed. Test-day milk yields were divided into 44 weekly classes of days in milk. Contemporary groups were defined by herd-test-day comprising a total of 2,539 classes. The model included direct additive genetic, permanent environmental, and residual random effects. The following fixed effects were considered: contemporary group, age of cow at calving (linear and quadratic regressions), and the population average lactation curve modeled by fourth-order orthogonal Legendre polynomial. Additive genetic effects were modeled by random regression on orthogonal Legendre polynomials of days in milk, whereas permanent environmental effects were estimated using a stationary or nonstationary parametric correlation function combined with a variance function of different orders. The structure of residual variances was modeled using a step function containing 6 variance classes. The genetic parameter estimates obtained with the model using a stationary correlation function associated with a variance function to model permanent environmental effects were similar to those obtained with models employing orthogonal Legendre polynomials for the same effect. A model using a sixth-order polynomial for additive effects and a stationary parametric correlation function associated with a seventh-order variance function to model permanent environmental effects would be sufficient for data fitting.

Random regression models to estimate test-day milk yield genetic parameters Holstein cows in Southeastern Brazil

A total of 152,145 weekly test-day milk yield records from 7317 first lactations of Holstein cows distributed in 93 herds in southeastern Brazil were analyzed. Test-day milk yields were classified into 44 weekly classes of DIM. The contemporary groups were defined as herd-year-week of test-day. The model included direct additive genetic, permanent environmental and residual effects as random and fixed effects of contemporary group and age of cow at calving as covariable, linear and quadratic effects. Mean trends were modeled by a cubic regression on orthogonal polynomials of DIM. Additive genetic and permanent environmental random effects were estimated by random regression on orthogonal Legendre polynomials. Residual variances were modeled using third to seventh-order variance functions or a step function with 1, 6,13,17 and 44 variance classes. Results from Akaike`s and Schwarz`s Bayesian information criterion suggested that a model considering a 7th-order Legendre polynomial for additive effect, a 12th-order polynomial for permanent environment effect and a step function with 6 classes for residual variances, fitted best. However, a parsimonious model, with a 6th-order Legendre polynomial for additive effects and a 7th-order polynomial for permanent environmental effects, yielded very similar genetic parameter estimates. (C) 2008 Elsevier B.V. All rights reserved.

A Log-Linear Regression Model for the Beta-Weibull Distribution

We introduce the log-beta Weibull regression model based on the beta Weibull distribution (Famoye et al., 2005; Lee et al., 2007). We derive expansions for the moment generating function which do not depend on complicated functions. The new regression model represents a parametric family of models that includes as sub-models several widely known regression models that can be applied to censored survival data. We employ a frequentist analysis, a jackknife estimator, and a parametric bootstrap for the parameters of the proposed model. We derive the appropriate matrices for assessing local influences on the parameter estimates under different perturbation schemes and present some ways to assess global influences. Further, for different parameter settings, sample sizes, and censoring percentages, several simulations are performed. In addition, the empirical distribution of some modified residuals are displayed and compared with the standard normal distribution. These studies suggest that the residual analysis usually performed in normal linear regression models can be extended to a modified deviance residual in the proposed regression model applied to censored data. We define martingale and deviance residuals to evaluate the model assumptions. The extended regression model is very useful for the analysis of real data and could give more realistic fits than other special regression models.

Paclitaxel associated with cholesterol-rich nanoemulsions promotes atherosclerosis regression in the rabbit

A cholesterol-rich nanoemulsion (LDE) that resembles LDL binds to the LDL receptors and after injection into the blood stream may concentrate in cells with LDL receptor overexpression, as occurs in neoplasias and other proliferative processes. Thus, LDE can be used as vehicle to target drugs against those cells. The current study was designed to verify in rabbits whether LDE concentrates in the lesioned rabbit artery and whether a paclitaxel derivative, paclitaxel oleate, associated to LDE could reduce the atherosclerotic lesions. Sixteen male New Zealand rabbits were fed a 1% cholesterol diet for 60 days. Starting from day 30 under cholesterol feeding, eight animals were treated with four weekly intravenous injections of LDE-paclitaxel (4 mg/kg) and eight with four weekly intravenous saline solution injections for additional 30 days. On day 60, the animals were sacrificed for analysis. The uptake of LDE labeled with [C-14]-cholesteryl oleate by the aortic arch of cholesterol-fed rabbits was twice as much that observed in animals fed only regular chow. LDE-paclitaxel reduced the lesion areas of cholesterol-fed animals by 60% and intima-media ratio fourfold and inhibited the macrophage migration and the smooth muscle cell proliferation and invasion of the intima. LDE-paclitaxel treatment had no toxicity. In conclusion, LDE-paclitaxel produced pronounced atherosclerosis regression without toxicity and has shown remarkable potential in cardiovascular therapeutics. (c) 2008 Published by Elsevier Ireland Ltd.

Exploratory Approach to the use of Techniques of Regression Analysis and Pooled Analysis in Studies of Consumer Behavior

This paper is part of a large study to assess the adequacy of the use of multivariate statistical techniques in theses and dissertations of some higher education institutions in the area of marketing with theme of consumer behavior from 1997 to 2006. The regression and conjoint analysis are focused on in this paper, two techniques with great potential of use in marketing studies. The objective of this study was to analyze whether the employement of these techniques suits the needs of the research problem presented in as well as to evaluate the level of success in meeting their premisses. Overall, the results suggest the need for more involvement of researchers in the verification of all the theoretical precepts of application of the techniques classified in the category of investigation of dependence among variables.

Multicollinearity and financial constraint in investment decisions: a Bayesian generalized ridge regression

This paper addresses the investment decisions considering the presence of financial constraints of 373 large Brazilian firms from 1997 to 2004, using panel data. A Bayesian econometric model was used considering ridge regression for multicollinearity problems among the variables in the model. Prior distributions are assumed for the parameters, classifying the model into random or fixed effects. We used a Bayesian approach to estimate the parameters, considering normal and Student t distributions for the error and assumed that the initial values for the lagged dependent variable are not fixed, but generated by a random process. The recursive predictive density criterion was used for model comparisons. Twenty models were tested and the results indicated that multicollinearity does influence the value of the estimated parameters. Controlling for capital intensity, financial constraints are found to be more important for capital-intensive firms, probably due to their lower profitability indexes, higher fixed costs and higher degree of property diversification.

Coronary Artery Stenoses: Accuracy of 64-Detector Row CT Angiography in Segments with Mild, Moderate, or Severe Calcification-A Subanalysis of the CORE-64 Trial

Purpose: To evaluate the influence of cross-sectional arc calcification on the diagnostic accuracy of computed tomography (CT) angiography compared with conventional coronary angiography for the detection of obstructive coronary artery disease (CAD). Materials and Methods: Institutional Review Board approval and written informed consent were obtained from all centers and participants for this HIPAA-compliant study. Overall, 4511 segments from 371 symptomatic patients (279 men, 92 women; median age, 61 years [interquartile range, 53-67 years]) with clinical suspicion of CAD from the CORE-64 multi-center study were included in the analysis. Two independent blinded observers evaluated the percentage of diameter stenosis and the circumferential extent of calcium (arc calcium). The accuracy of quantitative multidetector CT angiography to depict substantial (>50%) stenoses was assessed by using quantitative coronary angiography (QCA). Cross-sectional arc calcium was rated on a segment level as follows: noncalcified or mild (<90 degrees), moderate (90 degrees-180 degrees), or severe (>180 degrees) calcification. Univariable and multivariable logistic regression, receiver operation characteristic curve, and clustering methods were used for statistical analyses. Results: A total of 1099 segments had mild calcification, 503 had moderate calcification, 338 had severe calcification, and 2571 segments were noncalcified. Calcified segments were highly associated (P < .001) with disagreement between CTA and QCA in multivariable analysis after controlling for sex, age, heart rate, and image quality. The prevalence of CAD was 5.4% in noncalcified segments, 15.0% in mildly calcified segments, 27.0% in moderately calcified segments, and 43.0% in severely calcified segments. A significant difference was found in area under the receiver operating characteristic curves (noncalcified: 0.86, mildly calcified: 0.85, moderately calcified: 0.82, severely calcified: 0.81; P < .05). Conclusion: In a symptomatic patient population, segment-based coronary artery calcification significantly decreased agreement between multidetector CT angiography and QCA to detect a coronary stenosis of at least 50%.

Effect of Isolated Fractions of Harpagophytum procumbens DC (Devil`s Claw) on COX-1, COX-2 Activity and Nitric Oxide Production on Whole-Blood Assay

The present study evaluates the effect of isolated fractions of Harpagophytum procumbens (devil`s claw) on cyclooxygenase (COX-1 and COX-2) activities and NO production using a whole blood assay. The activity of COX-1 was quantified as platelet thromboxane B(2) production in blood clotting and COX-2 as prostaglandin E(2) production in LPS-stimulated whole blood. Total NO(2)(-)/NO(3)(-) concentration was determined by Griess reaction in LPS stimulated blood. Assays were performed by incubation of isolated fractions obtained by flash chromatography monitored with HPLC, TLC and identified by (1)HNMR, containing different amounts of harpagoside with blood from healthy donors. Indomethacin and etoricoxib were the positive controls of COX-1 and COX-2 Inhibition. Data shows that fraction containing the highest concentration of harpagoside inhibited indistinctively COX-1 and COX-2 (37.2 and 29.5% respectively) activity and greatly inhibited NO production (66%). In contrast the fraction including iridoid pool increased COX-2 and did not alter NO and COX-1 activities. The fraction containing cinnamic acid was able to reduce only NO production (67%). Our results demonstrated that the harpagoside fraction is the main responsible for the effect of devils claw on these enzyme activities. However, other components from devil`s claw crude extract could antagonize or increase the synthesis of inflammatory mediators. Copyright (C) 2010 John Wiley & Sons, Ltd.

Glycemia and prognosis of patients with chronic heart failure-Subanalysis of the Long-term Prospective Randomized Controlled Study Using Repetitive Education at Six-Month Intervals and Monitoring for Adherence in Heart Failure Outpatients (REMADHE) trial

Background Heart failure and diabetes often occur simultaneously in patients, but the prognostic value of glycemia in chronic heart failure is debatable. We evaluated the role of glycemia on prognosis of heart failure. Methods Outpatients with chronic heart failure from the Long-term Prospective Randomized Controlled Study Using Repetitive Education at Six-Month Intervals and Monitoring for Adherence in Heart Failure Outpatients (REMADHE) trial were grouped according to the presence of diabetes and level of glycemia. All-cause mortality/heart transplantation and unplanned hospital admission were evaluated. Results Four hundred fifty-six patients were included (135 [29.5%] female, 124 [27.2%] with diabetes mellitus, age of w50.2 +/- 11.4 years, and left-ventricle ejection fraction of 34.7% +/- 10.5%). During follow-up (3.6 +/- 2.2 years), 27 (5.9%) patients were submitted to heart transplantation and 202 (44.2%) died; survival was similar in patients with and without diabetes mellitus. When patients with and without diabetes were categorized according to glucose range (glycemia <= 100 mg/dL [5.5 mmol/L]), as well as when distributed in quintiles of glucose, the survival was significantly worse among patients with lower levels of glycemia. This finding persisted in Cox proportional hazards regression model that included gender, etiology, left ventricle ejection fraction, left ventricle diastolic diameter, creatinine level and beta-blocker therapy, and functional status (hazard ratio 1.45, 95% CI 1.09-1.69, P = .039). No difference regarding unplanned hospital admission was found. Conclusion We report on an inverse association between glycemia and mortality in outpatients with chronic heart failure. These results point to a new pathophysiologic understanding of the interactions between diabetes mellitus, hyperglycemia, and heart disease. (Am Heart J 2010; 159: 90-7.)

Association between ADAMTS13 polymorphisms and risk of cardiovascular events in chronic coronary disease

Introduction: Association between ADAMTS13 levels and cardiovascular events has been described recently. However, no genetic study of ADAMTS13 in coronary patients has been described. Materials and Methods: Based on related populations frequencies and functional studies, we tested three ADAMTS13 polymorphisms: C1342G (Q448E), C1852G (P618A) and C2699T (A900V) in a group of 560 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. The incidence of the 5-year end-points of death and death from cardiac causes, myocardial infarction, refractory angina requiring revascularization and cerebrovascular accident was determined for each polymorphim`s allele, genotype and haplotype. Risk was assessed with the use of logistic regression and Cox proportional-hazards model and multivariable adjustment was employed for possible confounders. Results: Clinical characteristics and received treatment of each genotype group were similar at baseline. In an adjusted model for cardiovascular risk variables, we were able to observe a significant association between ADAMTS13 900V variant and an increased risk of death (OR: 1,92 CI: 1,14-3,23, p = 0,015) or death from cardiac cause (OR: 2,67, CI: 1,59-4,49, p = 0,0009). No association between events and ADAMTS13 Q448E or P618A was observed. Conclusions: This first report studying the association between ADAMTS13 genotypes and cardiovascular events provides evidence for the association between ADAMTS13 900V variant and an increased risk of death in a population with multi-vessel CAD. (C) 2009 Elsevier Ltd. All rights reserved.

Factors affecting management decisions in rectal cancer in clinical practice: results from a national survey

Management of rectal cancer has become increasingly complex and a multidisciplinary approach is considered of key importance for improving outcomes. A national survey among specialists involved in this multidisciplinary setting was performed. A web-based survey containing 11 questions regarding rectal cancer management was sent to surgeons and medical oncologists registered by their corresponding societies as members. Statistical analysis was performed using the chi-square and Fisher`s exact tests for all categorical variables according to response to individual questions. Multivariate analysis was performed using Cox`s logistic regression. Overall, 418 email recipients responded the survey. Local staging was performed without either magnetic resonance imaging or endorectal ultrasound by 64% of responders. Seventy-two percent considered that final management decision should be made after neoadjuvant chemoradiation therapy. Additionally, 46% considered that an alternative procedure (local excision or observation) was appropriate in a patient with a complete clinical response. Colorectal surgeons were more frequently in favor of longer intervals after completion of chemoradiation therapy (P = 0.001) and of alternative management procedures after a complete clinical response (P = 0.02). After multivariate analysis, the choice of a watch and wait approach after a complete clinical response following neoadjuvant chemoradiation therapy was significantly more frequent among surgeons (OR 3.5, 95% CI 1.8-7.1). Surgeons seem to be more in favor of tailoring management of rectal cancer according to tumor response after neoadjuvant chemoradiation therapy, with longer intervals after chemoradiation therapy, decisions about treatment strategy being made after chemoradiation therapy instead of before, and the use of alternative surgical procedures after a complete clinical response following neoadjuvant therapy.