Genetic progress in sunflower crop in Rio Grande do Sul State, Brazil.

The sunflower has adaptability to growing regions with different climatic and soil characteristics, showing drought tolerance and high-quality oil production. The State of Rio Grande do Sul is the third largest sunflower producer in Brazil, with research related to the sunflower breeding initiated after the decade of 1950. The aim of this study was to evaluate the genetic progress for grain yield, oil content, and oil yield of sunflower (Helianthus annuus L.) in the State of Rio Grande do Sul. Data of grain yield, oil content, and oil yield obtained from 58 sunflower cultivar yield trials in 19 municipalities in Rio Grande do Sul during the period from 2005 to 2014 were used. Genetic progress was studied according to the methodology proposed by Vencovsky and data from sunflower cultivar yield trials were used. Annual genetic progress of sunflower during the period of 10 years (2005-2014) was 132.46 kg⋅ha-1⋅year-1 for grain yield, -0.17%/year for oil content, and 48.11 kg⋅ha-1⋅year-1 for oil yield. The sunflower-breeding programs in the State of Rio Grande do Sul were efficient for the traits grain yield and oil yield and presented no efficiency for oil content.

Genetic progress in homogeneous regions of wheat cultivation in Rio Grande do Sul State, Brazil.

The State of Rio Grande do Sul (RS) stands out as the largest wheat producer in Brazil. Wheat is the most emphasized winter cereal in RS, attracting public and private investments directed to wheat genetic breeding. The study of genetic progress should be performed routinely at breeding programs to study the behavior of cultivars developed for homogeneous regions of cultivation. The objectives of this study were: 1) to evaluate the genetic progress of wheat grain yield in RS; 2) to evaluate the influence of cultivar competition trial stratification in homogeneous regions of cultivation on the study of genetic progress. Grain yield data of 122 wheat cultivars evaluated in 137 trials arranged in randomized block design with three or four replications were used. Field trials were carried out in 23 locations in RS divided into two homogeneous regions during the period from 2002 to 2013. Genetic progress for RS and homogeneous regions was studied utilizing the method proposed by Vencovsky. Annual genetic progress for wheat grain yield during the period of 12 years in the State of RS was 2.86%, oscillating between homogeneous regions of cultivation. The difference of annual genetic progress in region 1 (1.82%) in relation to region 2 (4.38%) justifies the study of genetic progress by homogeneous regions of cultivation.

REML/BLUP and sequential path analysis in estimating genotypic values and interrelationships among simple maize grain yield-related traits.

Methodologies using restricted maximum likelihood/best linear unbiased prediction (REML/BLUP) in combination with sequential path analysis in maize are still limited in the literature. Therefore, the aims of this study were: i) to use REML/BLUP-based procedures in order to estimate variance components, genetic parameters, and genotypic values of simple maize hybrids, and ii) to fit stepwise regressions considering genotypic values to form a path diagram with multi-order predictors and minimum multicollinearity that explains the relationships of cause and effect among grain yield-related traits. Fifteen commercial simple maize hybrids were evaluated in multi-environment trials in a randomized complete block design with four replications. The environmental variance (78.80%) and genotype-vs-environment variance (20.83%) accounted for more than 99% of the phenotypic variance of grain yield, which difficult the direct selection of breeders for this trait. The sequential path analysis model allowed the selection of traits with high explanatory power and minimum multicollinearity, resulting in models with elevated fit (R2 > 0.9 and ε < 0.3). The number of kernels per ear (NKE) and thousand-kernel weight (TKW) are the traits with the largest direct effects on grain yield (r = 0.66 and 0.73, respectively). The high accuracy of selection (0.86 and 0.89) associated with the high heritability of the average (0.732 and 0.794) for NKE and TKW, respectively, indicated good reliability and prospects of success in the indirect selection of hybrids with high-yield potential through these traits. The negative direct effect of NKE on TKW (r = -0.856), however, must be considered. The joint use of mixed models and sequential path analysis is effective in the evaluation of maize-breeding trials.

Genetic progress in oat associated with fungicide use in Rio Grande do Sul, Brazil.

The State of Rio Grande do Sul (RS) is the largest producer of oat in Brazil with the aid of consolidated breeding programs, which are constantly releasing new cultivars. The main objectives of this study were to: 1) evaluate the annual genetic progress in grain yield and hectoliter weight of the oat cultivars in RS, with and without fungicide use on aerial parts of plants; and 2) evaluate the efficiency of oat breeding programs in introducing disease-resistant genes in the released cultivars through network yield trials conducted with and without fungicide use on aerial plant parts. The data on grain yield and hectoliter weight were obtained from 89 competition field trials of oat cultivars carried out from 2007 to 2014 in nine municipalities of RS. Of the total 89 trials, 44 were carried out with fungicide application on aerial plant parts and 45 were carried out without fungicide application. The annual genetic progress in oat cultivars was studied using the methodology proposed by Vencovsky (1988). The annual genetic progress in oat grain yield was 1.02% with fungicide use and 4.02% without fungicide use during the eight-year study period in RS. The annual genetic progress with respect to the hectoliter weight was 0.08% for trials with fungicide use and 0.71% for trials without fungicide use. Performing network yield trials with and without fungicide use on the aerial plants parts is a feasible method to evaluate the efficiency of oat breeding programs in introducing disease-resistant genes in the released cultivars.

Sample sizes to estimate mean values for tassel traits in maize genotypes.

Tassel traits are important in maize breeding programs aiming to reduce the size and number of branches and maintain satisfactory pollen production in order to increase grain yield. The objectives of this study were to determine the sample size (number of tassels) required to estimate the mean values for tassel traits in maize genotypes and to verify the variability of sample size among genotypes. Twenty maize genotypes were evaluated in an experiment carried out in a randomized block design with three replicates. Twenty tassels were randomly collected in each plot, for a total of 1200 tassels. In each tassel, the following traits were measured: peduncle dry matter, branching space dry matter, central spike dry matter, tassel dry matter, peduncle length, branching space length, central spike length, tassel length, tassel dry matter to tassel length ratio, number of primary branches, number of secondary branches, and tassel branch number. Measures of central tendency and variability were calculated, analysis of variance and mean comparison tests were performed, normality was verified, and the sample size was determined. In order to estimate the means with the same precision, the sample size for weight traits was greater than that for length traits. For tassel traits, 11, 20, and 43 tassels are sufficient to estimate the mean with a precision of 40, 30, and 20%, respectively, of the estimated mean at a 95% confidence level. These data show that there is sample size variability among maize genotypes.

Increased frequency of HLA-DR2 in patients with paroxysmal nocturnal hemoglobinuria and the PNH/aplastic anemia syndrome.

Many autoimmune diseases are associated with HLA alleles, and such a relationship also has been reported for aplastic anemia (AA). AA and paroxysmal nocturnal hemoglobinuria (PNH) are related clinically, and glycophosphoinositol (GPI)-anchored protein (AP)-deficient cells can be found in many patients with AA. The hypothesis was considered that expansion of a PNH clone may be a marker of immune-mediated disease and its association with HLA alleles was examined. The study involved patients with a primary diagnosis of AA, patients with myelodysplastic syndrome (MDS), and patients with primary PNH. Tests of proportions were used to compare allelic frequencies. For patients with a PNH clone (defined by the presence of GPI-AP-deficient granulocytes), regardless of clinical manifestations, there was a higher than normal incidence of HLA-DR2 (58% versus 28%; z = 4.05). The increased presence of HLA-DR2 was found in all frankly hemolytic PNH and in PNH associated with bone marrow failure (AA/PNH and MDS/PNH). HLA-DR2 was more frequent in AA/PNH (56%) than in AA without a PNH clone (37%; z = 3.36). Analysis of a second cohort of patients with bone marrow failure treated with immunosuppression showed that HLA-DR2 was associated with a hematologic response (50% of responders versus 34% of nonresponders; z = 2.69). Both the presence of HLA-DR2 and the PNH clone were independent predictors of response but the size of PNH clone did not correlate with improvement in blood count. The results suggest that clonal expansion of GPI-AP-deficient cells is linked to HLA and likely related to an immune mechanism.

Electrical storm presages nonsudden death: the antiarrhythmics versus implantable defibrillators (AVID) trial.

BACKGROUND: Electrical storm, multiple temporally related episodes of ventricular tachycardia (VT) or ventricular fibrillation (VF), is a frequent problem among recipients of implantable cardioverter defibrillators (ICDs). However, insufficient data exist regarding its prognostic significance. METHODS AND RESULTS: This analysis includes 457 patients who received an ICD in the Antiarrhythmics Versus Implantable Defibrillators (AVID) trial and who were followed for 31 +/- 13 months. Electrical storm was defined as > or = 3 separate episodes of VT/VF within 24 hours. Characteristics and survival of patients surviving electrical storm (n = 90), those with VT/VF unrelated to electrical storm (n = 184), and the remaining patients (n = 183) were compared. The 3 groups differed in terms of ejection fraction, index arrhythmia, revascularization status, and baseline medication use. Survival was evaluated using time-dependent Cox modeling. Electrical storm occurred 9.2 +/- 11.5 months after ICD implantation, and most episodes (86%) were due to VT. Electrical storm was a significant risk factor for subsequent death, independent of ejection fraction and other prognostic variables (relative risk [RR], 2.4; 95% confidence interval [CI], 1.3 to 4.2; P = 0.003), but VT/VF unrelated to electrical storm was not (RR, 1.0; 95% CI, 0.6 to 1.7; P = 0.9). The risk of death was greatest 3 months after electrical storm (RR, 5.4; 95% Cl, 2.4 to 12.3; P = 0.0001) and diminished beyond this time (RR, 1.9; 95% CI, 1.0 to 3.6; P=0.04). CONCLUSIONS: Electrical storm is an important, independent marker for subsequent death among ICD recipients, particularly in the first 3 months after its occurrence. However, the development of VT/VF unrelated to electrical storm does not seem to be associated with an increased risk of subsequent death.

Patients at lower risk of arrhythmia recurrence: a subgroup in whom implantable defibrillators may not offer benefit. Antiarrhythmics Versus Implantable Defibrillator (AVID) Trial Investigators.

OBJECTIVES: The goal of this study was to identify subgroups of arrhythmia patients who do not benefit from use of the implantable cardiac defibrillator (ICD). BACKGROUND: Treatment of serious ventricular arrhythmias has evolved toward more common use of the ICD. Since estimates of the cost per year of life saved by ICD therapy vary from $25,000 to perhaps $125,000, it is important to identify patient subgroups that do not benefit from the ICD. METHODS: Data for 491 ICD patients enrolled in the Antiarrhythmics Versus Implantable Defibrillators Study were used to create a hazards model relating baseline factors to time to first recurrent arrhythmia. The model was used to predict the hazard for recurrent arrhythmia among all trial patients. A priori cut points provided lower and higher recurrent arrhythmia risk strata. For each stratum the incremental years of life due to ICD versus antiarrhythmic drug therapy were calculated. RESULTS: Factors that predicted recurrent arrhythmia were: ventricular tachycardia as the index arrhythmia, history of cerebrovascular disease, lower left ventricular ejection fraction, a history of any tachyarrhythmia before the index event and the absence of revascularization after the index event. Survival times (over a follow-up of three years) were identical in each arm of the lowest risk sextile (survival advantage 0.03 +/- 0.12 [se] years), while the survival advantage for patients above the first sextile was 0.27 +/- 0.07 (se) years (two-sided p = 0.05). CONCLUSIONS: Patients presenting with an isolated episode of ventricular fibrillation in the absence of cerebrovascular disease or history of prior arrhythmia who have undergone revascularization or who have moderately preserved left ventricular function (left ventricular ejection fraction > 0.27) are not likely to benefit from ICD therapy compared with amiodarone therapy.

Testing for treatment and interaction effects in semi-parametric analysis of covariance.

Semi-parametric regression models assume that the effects of covariates on the mean response are additive. We propose a test of additivity when there is one continuous covariate and a group indicator. At p fixed points, the differences of the within-group kernel estimates of the means are calculated, and the likelihood ratio test that the p differences have a constant mean is formed. The kernel bandwidth and the location of the p fixed points are chosen to give the test good power. Performance of the proposed test is compared with parametric and non-parametric tests of additivity. Published in 2001 by John Wiley & Sons, Ltd.

Meta-analysis of the implantable cardioverter defibrillator secondary prevention trials. AVID, CASH and CIDS studies. Antiarrhythmics vs Implantable Defibrillator study. Cardiac Arrest Study Hamburg . Canadian Implantable Defibrillator Study.

AIMS: Three randomized trials of implantable cardioverter defibrillator (ICD) therapy vs medical treatment for the prevention of death in survivors of ventricular fibrillation or sustained ventricular tachycardia have been reported with what might appear to be different results. The present analysis was performed to obtain the most precise estimate of the efficacy of the ICD, compared to amiodarone, for prolonging survival in patients with malignant ventricular arrhythmia. METHODS AND RESULTS: Individual patient data from the Antiarrhythmics vs Implantable Defibrillator (AVID) study, the Cardiac Arrest Study Hamburg (CASH) and the Canadian Implantable Defibrillator Study (CIDS) were merged into a master database according to a pre-specified protocol. Proportional hazard modelling of individual patient data was used to estimate hazard ratios and to investigate subgroup interactions. Fixed effect meta-analysis techniques were also used to evaluate treatment effects and to assess heterogeneity across studies. The classic fixed effects meta-analysis showed that the estimates of ICD benefit from the three studies were consistent with each other (P heterogeneity=0.306). It also showed a significant reduction in death from any cause with the ICD; with a summary hazard ratio (ICD:amiodarone) of 0.72 (95% confidence interval 0.60, 0.87;P=0.0006). For the outcome of arrhythmic death, the hazard ratio was 0.50 (95% confidence interval 0.37, 0.67;P<0.0001). Survival was extended by a mean of 4.4 months by the ICD over a follow-up period of 6 years. Patients with left ventricular ejection fraction < or = 35% derived significantly more benefit from ICD therapy than those with better preserved left ventricular function. Patients treated before the availability of non-thoracotomy ICD implants derived significantly less benefit from ICD therapy than those treated in the non-thoracotomy era. CONCLUSION: Results from the three trials of the ICD vs amiodarone are consistent with each other. There is a 28% reduction in the relative risk of death with the ICD that is due almost entirely to a 50% reduction in arrhythmic death.

Modeling repeated count data subject to informative dropout.

In certain diseases, outcome is the number of morbid events over the course of follow-up. In epilepsy, e.g., daily seizure counts are often used to reflect disease severity. Follow-up of patients in clinical trials of such diseases is often subject to censoring due to patients dying or dropping out. If the sicker patients tend to be censored in such trials, estimates of the treatment effect that do not incorporate the censoring process may be misleading. We extend the shared random effects approach of Wu and Carroll (1988, Biometrics 44, 175-188) to the setting of repeated counts of events. Three strategies are developed. The first is a likelihood-based approach for jointly modeling the count and censoring processes. A shared random effect is incorporated to introduce dependence between the two processes. The second is a likelihood-based approach that conditions on the dropout times in adjusting for informative dropout. The third is a generalized estimating equations (GEE) approach, which also conditions on the dropout times but makes fewer assumptions about the distribution of the count process. Estimation procedures for each of the approaches are discussed, and the approaches are applied to data from an epilepsy clinical trial. A simulation study is also conducted to compare the various approaches. Through analyses and simulations, we demonstrate the flexibility of the likelihood-based conditional model for analyzing data from the epilepsy trial.

Quantitative insulin sensitivity check index: a simple, accurate method for assessing insulin sensitivity in humans.

Insulin resistance plays an important role in the pathophysiology of diabetes and is associated with obesity and other cardiovascular risk factors. The "gold standard" glucose clamp and minimal model analysis are two established methods for determining insulin sensitivity in vivo, but neither is easily implemented in large studies. Thus, it is of interest to develop a simple, accurate method for assessing insulin sensitivity that is useful for clinical investigations. We performed both hyperinsulinemic isoglycemic glucose clamp and insulin-modified frequently sampled iv glucose tolerance tests on 28 nonobese, 13 obese, and 15 type 2 diabetic subjects. We obtained correlations between indexes of insulin sensitivity from glucose clamp studies (SI(Clamp)) and minimal model analysis (SI(MM)) that were comparable to previous reports (r = 0.57). We performed a sensitivity analysis on our data and discovered that physiological steady state values [i.e. fasting insulin (I(0)) and glucose (G(0))] contain critical information about insulin sensitivity. We defined a quantitative insulin sensitivity check index (QUICKI = 1/[log(I(0)) + log(G(0))]) that has substantially better correlation with SI(Clamp) (r = 0.78) than the correlation we observed between SI(MM) and SI(Clamp). Moreover, we observed a comparable overall correlation between QUICKI and SI(Clamp) in a totally independent group of 21 obese and 14 nonobese subjects from another institution. We conclude that QUICKI is an index of insulin sensitivity obtained from a fasting blood sample that may be useful for clinical research.

Predictors of mortality and mortality from cardiac causes in the bypass angioplasty revascularization investigation (BARI) randomized trial and registry. For the BARI Investigators.

BACKGROUND: The impact of percutaneous transluminal coronary angioplasty (PTCA) and coronary artery bypass grafting (CABG) on long-term mortality rates in the presence of various demographic, clinical, and angiographic factors is uncertain in the population of patients suitable for both procedures. METHODS AND RESULTS: In the Bypass Angioplasty Revascularization Investigation (BARI) randomized trial and registry, 3610 patients who were eligible to receive PTCA and CABG were revascularized between 1989 and 1992. Multivariate Cox models were used to identify factors associated with 5-year mortality and cardiac mortality, with particular attention to factors that interact with treatment. Diabetic patients receiving insulin had higher mortality and cardiac mortality rates with PTCA compared with CABG (relative risk [RR] 1.78 and 2.63, respectively, P<0.001), and patients with ST elevation had higher cardiac mortality rates with CABG than with PTCA (RR 4.08, P<0.001). Factors most strongly associated with high overall mortality rates were insulin-treated diabetes, congestive heart failure, kidney failure, and older age. Black race was also associated with higher mortality rates (RR 1.49, P=0.019). CONCLUSIONS: A set of variables was identified that could be used to help select a revascularization procedure and to evaluate risk of long-term mortality in the population of patients considering revascularization.

Beta-blocker use and survival in patients with ventricular fibrillation or symptomatic ventricular tachycardia: the Antiarrhythmics Versus Implantable Defibrillators (AVID) trial.

OBJECTIVES: To evaluate whether use of beta-adrenergic blocking agents, alone or in combination with specific antiarrhythmic therapy, is associated with improved survival in persons with ventricular fibrillation (VF) or symptomatic ventricular tachycardia (VT). BACKGROUND: The ability of beta-blockers to alter the mortality of patients with VF or VT receiving contemporary medical management is not well defined. METHODS: Survival of 1,016 randomized and 2,101 eligible, nonrandomized patients with VF or symptomatic VT followed in the Antiarrhythmics Versus Implantable Defibrillators (AVID) trial through December 31, 1996 was assessed using Cox proportional hazards analysis. RESULTS: The 817 (28%) patients discharged from hospital receiving beta-blockers had less ventricular dysfunction, fewer symptoms of heart failure and a different pattern of medication use compared with patients not receiving beta-blockers. Before adjustment for important prognostic variables, beta-blockade was not significantly associated with survival in randomized or in eligible, nonrandomized patients treated with specific antiarrhythmic therapy. After adjustment, beta-blockade remained unrelated to survival in randomized or in eligible, nonrandomized patients treated with amiodarone alone (n = 1142; adjusted relative risk [RR] = 0.96; 95% confidence interval [CI] 0.64-1.45; p = 0.85) or a defibrillator alone (n = 1347; adjusted RR = 0.88; 95% CI 0.55 to 1.40; p = 0.58). In contrast, beta-blockade was independently associated with improved survival in eligible, nonrandomized patients who were not treated with specific antiarrhythmic therapy (n = 412; adjusted RR = 0.47; 95% CI 0.25 to 0.88; p = 0.018). CONCLUSIONS: Beta-blocker use was independently associated with improved survival in patients with VF or symptomatic VT who were not treated with specific antiarrhythmic therapy, but a protective effect was not prominent in patients already receiving amiodarone or a defibrillator.

Valid inference in random effects meta-analysis.

The standard approach to inference for random effects meta-analysis relies on approximating the null distribution of a test statistic by a standard normal distribution. This approximation is asymptotic on k, the number of studies, and can be substantially in error in medical meta-analyses, which often have only a few studies. This paper proposes permutation and ad hoc methods for testing with the random effects model. Under the group permutation method, we randomly switch the treatment and control group labels in each trial. This idea is similar to using a permutation distribution for a community intervention trial where communities are randomized in pairs. The permutation method theoretically controls the type I error rate for typical meta-analyses scenarios. We also suggest two ad hoc procedures. Our first suggestion is to use a t-reference distribution with k-1 degrees of freedom rather than a standard normal distribution for the usual random effects test statistic. We also investigate the use of a simple t-statistic on the reported treatment effects.

A simple permutation-type method for testing circular uniformity with correlated angular measurements.

A simple method is provided for testing uniformity on the circle that allows dependence among repeated angular measurements on the same subject. Our null hypothesis is that the distribution of repeated angles is unaffected by rotation. This null can be evaluated with any test of uniformity by using a null reference distribution obtained by simulation, where each subject's vector of angles is rotated by a random amount. A new weighted version of the univariate Rayleigh test of circular uniformity is proposed.

A multivariate test of interaction for use in clinical trials.

An important issue in clinical trials is whether the effect of treatment is essentially homogeneous as a function of baseline covariates. Covariates that have the potential for an interaction with treatment may be suspected on the basis of treatment mechanism or may be known risk factors, as it is often thought that the sickest patients may benefit most from treatment. If disease severity is more accurately determined by a collection of baseline covariates rather than a single risk factor, methods that examine each covariate in turn for interaction may be inadequate. We propose a procedure whereby treatment interaction is examined along a single severity index that is a linear combination of baseline covariates. Formally, we derive a likelihood ratio test based on the null beta0 = beta1 versus the alternative abeta0 = beta1, where X'beta(k) (k = 0, 1) corresponds to the severity index in arm k and X is a vector of baseline covariates. While our explicit test requires a Gaussian response, it can be readily implemented whenever the estimates of beta0,beta1 are approximately multivariate normal. For example, it is appropriate for large clinical trials where beta(k) is based on a logisitic or Cox regression of response on X.

Use of summary measures to adjust for informative missingness in repeated measures data with random effects.

We discuss how to apply the conditional informative missing model of Wu and Bailey (1989, Biometrics 45, 939-955) to the setting where the probability of missing a visit depends on the random effects of the primary response in a time-dependent fashion. This includes the case where the probability of missing a visit depends on the true value of the primary response. Summary measures for missingness that are weighted sums of the indicators of missed visits are derived for these situations. These summary measures are then incorporated as covariates in a random effects model for the primary response. This approach is illustrated by analyzing data collected from a trial of heroin addicts where missed visits are informative about drug test results. Simulations of realistic experiments indicate that these time-dependent summary measures also work well under a variety of informative censoring models. These summary measures can achieve large reductions in estimation bias and mean squared errors relative to those obtained by using other summary measures.

Repeated probit regression when covariates are measured with error.

This paper develops a model for repeated binary regression when a covariate is measured with error. The model allows for estimating the effect of the true value of the covariate on a repeated binary response. The choice of a probit link for the effect of the error-free covariate, coupled with normal measurement error for the error-free covariate, results in a probit model after integrating over the measurement error distribution. We propose a two-stage estimation procedure where, in the first stage, a linear mixed model is used to fit the repeated covariate. In the second stage, a model for the correlated binary responses conditional on the linear mixed model estimates is fit to the repeated binary data using generalized estimating equations. The approach is demonstrated using nutrient safety data from the Diet Intervention of School Age Children (DISC) study.