Statistical design and analysis of pharmacogenetic trials

Pharmacogenetic trials investigate the effect of genotype on treatment response. When there are two or more treatment groups and two or more genetic groups, investigation of gene-treatment interactions is of key interest. However, calculation of the power to detect such interactions is complicated because this depends not only on the treatment effect size within each genetic group, but also on the number of genetic groups, the size of each genetic group, and the type of genetic effect that is both present and tested for. The scale chosen to measure the magnitude of an interaction can also be problematic, especially for the binary case. Elston et al. proposed a test for detecting the presence of gene-treatment interactions for binary responses, and gave appropriate power calculations. This paper shows how the same approach can also be used for normally distributed responses. We also propose a method for analysing and performing sample size calculations based on a generalized linear model (GLM) approach. The power of the Elston et al. and GLM approaches are compared for the binary and normal case using several illustrative examples. While more sensitive to errors in model specification than the Elston et al. approach, the GLM approach is much more flexible and in many cases more powerful. Copyright © 2005 John Wiley & Sons, Ltd.

Statistical modeling suggests that antiandrogens in effluents from wastewater treatment works contribute to widespread sexual disruption in fish living in English rivers.

BACKGROUND: The widespread occurrence of feminized male fish downstream of some wastewater treatment works has led to substantial interest from ecologists and public health professionals. This concern stems from the view that the effects observed have a parallel in humans, and that both phenomena are caused by exposure to mixtures of contaminants that interfere with reproductive development. The evidence for a "wildlife-human connection" is, however, weak: Testicular dysgenesis syndrome, seen in human males, is most easily reproduced in rodent models by exposure to mixtures of antiandrogenic chemicals. In contrast, the accepted explanation for feminization of wild male fish is that it results mainly from exposure to steroidal estrogens originating primarily from human excretion. OBJECTIVES: We sought to further explore the hypothesis that endocrine disruption in fish is multi-causal, resulting from exposure to mixtures of chemicals with both estrogenic and antiandrogenic properties. METHODS: We used hierarchical generalized linear and generalized additive statistical modeling to explore the associations between modeled concentrations and activities of estrogenic and antiandrogenic chemicals in 30 U.K. rivers and feminized responses seen in wild fish living in these rivers. RESULTS: In addition to the estrogenic substances, antiandrogenic activity was prevalent in almost all treated sewage effluents tested. Further, the results of the modeling demonstrated that feminizing effects in wild fish could be best modeled as a function of their predicted exposure to both anti-androgens and estrogens or to antiandrogens alone. CONCLUSION: The results provide a strong argument for a multicausal etiology of widespread feminization of wild fish in U.K. rivers involving contributions from both steroidal estrogens and xeno-estrogens and from other (as yet unknown) contaminants with antiandrogenic properties. These results may add farther credence to the hypothesis that endocrine-disrupting effects seen in wild fish and in humans are caused by similar combinations of endocrine-disrupting chemical cocktails.

Fluctuating abundance of humpback whales (Megaptera novaeangliae) in a calving ground off coastal Brazil

The humpback whale (Megaptera novaeangliae) population that uses Abrolhos Bank, off the east coast of Brazil as a breeding ground is increasing. To describe temporal changes in the relative abundance of humpback whales around Abrolhos, seven years (1998-2004) of whale count data were collected during July through to November. During one-hour-scans, observers determined group size within 9.3 km (5 n.m.) of a land-based observing station. A total Of 930 scans, comprising 7996 sightings of adults and 2044 calves were analysed using generalized linear models that included variables for time of day, day of the season, years and two-way interactions as possible predictors. The pattern observed was the gradual build-up and decline in whale counts within seasons. Patterns and peaks of adult and calf counts varied among years. Although fluctuation was observed, there was generally an increasing trend in adult counts among years. Calf counts increased only in 2004. These fluctuations may have been caused by some environmental conditions in humpback whales` summering grounds and also by changes in spatial-temporal concentrations in Abrolhos Bank. The general pattern observed within the study area mirrored what was observed in the whole Abrolhos Bank. Knowledge of the consistency with which humpback whales use this important nursing area should prove beneficial for designing future monitoring programmes especially related to whale watching activities around Abrolhos Archipelago.

Transformed symmetric models

For the first time, we introduce a class of transformed symmetric models to extend the Box and Cox models to more general symmetric models. The new class of models includes all symmetric continuous distributions with a possible non-linear structure for the mean and enables the fitting of a wide range of models to several data types. The proposed methods offer more flexible alternatives to Box-Cox or other existing procedures. We derive a very simple iterative process for fitting these models by maximum likelihood, whereas a direct unconditional maximization would be more difficult. We give simple formulae to estimate the parameter that indexes the transformation of the response variable and the moments of the original dependent variable which generalize previous published results. We discuss inference on the model parameters. The usefulness of the new class of models is illustrated in one application to a real dataset.

Genetic Heteroscedasticity for Domestic Animal Traits

Animal traits differ not only in mean, but also in variation around the mean. For instance, one sire’s daughter group may be very homogeneous, while another sire’s daughters are much more heterogeneous in performance. The difference in residual variance can partially be explained by genetic differences. Models for such genetic heterogeneity of environmental variance include genetic effects for the mean and residual variance, and a correlation between the genetic effects for the mean and residual variance to measure how the residual variance might vary with the mean. The aim of this thesis was to develop a method based on double hierarchical generalized linear models for estimating genetic heteroscedasticity, and to apply it on four traits in two domestic animal species; teat count and litter size in pigs, and milk production and somatic cell count in dairy cows. The method developed is fast and has been implemented in software that is widely used in animal breeding, which makes it convenient to use. It is based on an approximation of double hierarchical generalized linear models by normal distributions. When having repeated observations on individuals or genetic groups, the estimates were found to be unbiased. For the traits studied, the estimated heritability values for the mean and the residual variance, and the genetic coefficients of variation, were found in the usual ranges reported. The genetic correlation between mean and residual variance was estimated for the pig traits only, and was found to be favorable for litter size, but unfavorable for teat count.

Fitting conditional and simultaneous autoregressive spatial models in hglm

We present a new version (> 2.0) of the hglm package for fitting hierarchical generalized linear models (HGLMs) with spatially correlated random effects. CAR() and SAR() families for conditional and simultaneous autoregressive random effects were implemented. Eigen decomposition of the matrix describing the spatial structure (e.g., the neighborhood matrix) was used to transform the CAR/SAR random effects into an independent, but eteroscedastic, Gaussian random effect. A linear predictor is fitted for the random effect variance to estimate the parameters in the CAR and SAR models. This gives a computationally efficient algorithm for moderately sized problems.

Análise das relações da curva de crescimento e eficiência produtiva de vacas da raça Holandesa

O objetivo neste trabalho foi analisar as relações entre parâmetros da curva de crescimento (peso à maturidade e taxa de maturação) e medidas da eficiência produtiva de 333 vacas da raça Holandesa nascidas de 1992 a 2002. Dados de idade ao primeiro parto, produção de leite e duração da primeira lactação, primeiro intervalo de partos e produção de leite por dia de intervalo de partos foram analisados por meio de um modelo linear generalizado com o efeito fixo de grupo contemporâneo (ano-estação de nascimento), os efeitos aleatórios de pai da vaca e erro e os efeitos lineares e quadráticos do peso à maturidade e da taxa de maturação. Nas análises de longevidade e de duração da vida útil, incluiu-se o efeito fixo de motivo de descarte da vaca. Houve efeitos linear e quadrático da taxa de maturação sobre a maioria das características, exceto o primeiro intervalo de partos e a produção de leite por dia de intervalo de partos. As estimativas das taxas de maturação ótimas variaram de 0,0896 a 0,1187 kg/kg de peso vivo/mês. O peso à maturidade influenciou a longevidade de forma linear e quadrática. A combinação ótima foi de 701 kg de peso à maturidade e 0,0934 kg/kg de peso vivo/mês de taxa de maturação. O peso à maturidade correlacionou-se de forma desfavorável com a duração da primeira lactação (-0,11). Coeficientes de correlação significativos foram obtidos entre taxa de maturação e idade ao primeiro parto (-0,22), produção de leite na primeira lactação (0,18), duração da primeira lactação (0,18) e longevidade (0,14), o que confirma a hipótese de que vacas com taxas de maturação mais rápidas apresentam maior eficiência produtiva.

Late administration of a specific COX-2 inhibitor does not treat and/or prevent progression of gastric tumors in rats submitted to duodenogastric reflux procedure

PURPOSE:To assess whether late introduction of a specific COX-2 inhibitor (Meloxicam) can treat and/or prevent the progression of tumors in the stomach of rats submitted to duodenogastric reflux. METHODS: Seventy five male Wistar rats, weighing 150 grams, were submitted to the induction of duodenogastric reflux through the pylorus. At 36 weeks of follow-up were established three experimental groups: DGR36 sacrificed immediately, DGR54 and DGR54MLX both sacrificed at 54th week of follow-up . The animals of the latter group were fed with a rat chow premixed with Meloxicam (2.0 mg/ kg feed; 0.3 mg / kg bw / day) and the other two with standard rat chow. The lesions found in the pyloric mucosa and gastrojejunal anastomosis were analyzed macroscopically and histologically. For statistical analysis was adjusted a generalized linear model assuming a binomial distribution with LOGIT link function. RESULTS: No significant differences were found when comparing the incidences of benign tumor lesions (Adenomatous Hyperplasia), p=0.4915, or malignant (Mucinous Adenocarcinoma), p=0.2731, among groups. CONCLUSION: Late introduction of specific COX-2 inhibitor (Meloxicam) did not treat and was not able to prevent the progression of tumoral lesions induced by duodenogastric reflux in the rat stomachs.

Effects of sex and locality on the abundance of lice on the wild rodent Oligoryzomys nigripes

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Interação entre grau de perda auditiva e o incômodo com zumbidos em trabalhadores com história de exposição ao ruído

Hearing loss and tinnitus impact the lives of workers in every instance of their lives. Aim: this paper aims to investigate the existence of a dose-response relationship between hearing loss and tinnitus by determining whether higher levels of hearing loss can be associated with increased tinnitus-related discomfort. Materials and method: this cross-sectional case study assessed 284 workers exposed to occupational noise through pure tone audiometry. Test results were categorized as defined by Merluzzi. Individuals complaining of tinnitus answered the adapted and validated Brazilian Portuguese version of the Tinnitus Handicap Inventory. A generalized linear model was adjusted for binomial data to test the interaction between these factors. Results: over 60% of the ears analyzed had hearing loss, while more than 46% of them had tinnitus. Tinnitus prevalence and risk rates increased as pure tone audiometry results got worse. The association between both, considering all hearing loss degrees, was statistically significant. Conclusion: the results point to a statistical association between hearing loss and tinnitus; the greater the hearing loss, the greater the discomfort introduced by tinnitus. 2009 © Revista Brasileira de Otorrinolaringologia.

Detection of cavitated approximal surfaces using cone beam CT and intraoral receptors

Objectives: The aim of this study was to compare cone beam CT (CBCT) in a small field of view (FOV) with a solid-state sensor and a photostimulable phosphor plate system for detection of cavitated approximal surfaces. Methods: 257 non-filled approximal surfaces from human permanent premolars and molars were recorded by two intraoral digital receptors, a storage phosphor plate (Digora Optime, Soredex) and a solid-state CMOS sensor (Digora Toto, Soredex), and scanned in a cone beam CT unit (3D Accuitomo FPD80, Morita) with a FOV of 4 cm and a voxel size of 0.08 mm. Image sections were carried out in the axial and mesiodistal tooth planes. Six observers recorded surface cavitation in all images. Validation of the true absence or presence of surface cavitation was performed by inspecting the surfaces under strong light with the naked eye. Differences in sensitivity, specificity and agreement were estimated by analysing the binary data in a generalized linear model using an identity link function. Results: A significantly higher sensitivity was obtained by all observers with CBCT (p,0.001), which was not compromised by a lower specificity. Therefore, a significantly higher overall agreement was obtained with CBCT (p,0.001). There were no significant differences between the Digora Optime phosphor plate system and the Digora Toto CMOS sensor for any parameter. Conclusions: CBCT was much more accurate in the detection of surface cavitation in approximal surfaces than intraoral receptors. The differences are interpreted as clinically significant. A CBCT examination performed for other reasons should also be assessed for approximal surface cavities in teeth without restorations. © 2013 The British Institute of Radiology.

Regressão Simplex aplicada a delineamentos de mistura e utilização do Algoritmo Boosting

In the composition of this work are present two parts. The first part contains the theory used. The second part contains the two articles. The first article examines two models of the class of generalized linear models for analyzing a mixture experiment, which studied the effect of different diets consist of fat, carbohydrate, and fiber on tumor expression in mammary glands of female rats, given by the ratio mice that had tumor expression in a particular diet. Mixture experiments are characterized by having the effect of collinearity and smaller sample size. In this sense, assuming normality for the answer to be maximized or minimized may be inadequate. Given this fact, the main characteristics of logistic regression and simplex models are addressed. The models were compared by the criteria of selection of models AIC, BIC and ICOMP, simulated envelope charts for residuals of adjusted models, odds ratios graphics and their respective confidence intervals for each mixture component. It was concluded that first article that the simplex regression model showed better quality of fit and narrowest confidence intervals for odds ratio. The second article presents the model Boosted Simplex Regression, the boosting version of the simplex regression model, as an alternative to increase the precision of confidence intervals for the odds ratio for each mixture component. For this, we used the Monte Carlo method for the construction of confidence intervals. Moreover, it is presented in an innovative way the envelope simulated chart for residuals of the adjusted model via boosting algorithm. It was concluded that the Boosted Simplex Regression model was adjusted successfully and confidence intervals for the odds ratio were accurate and lightly more precise than the its maximum likelihood version.

Dinâmica populacional, anautogenia e dependência da ansiedade em moscas-varejeiras: experimentação e teoria populacional

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Modelagem estatística do frete da madeira no Uruguai

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Efeito da participação e do desligamento de programa de mudança no estilo de vida sobre o nível de atividade e aptidão física, percepção de saúde e presença de síndrome metabólica em adultos da comunidade de Botucatu - SP

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)