Frequentist and Bayesian Hypothesis Testing: An Intuitive Guide for Urologists and Clinicians / Pruebas de hipótesis frecuentista y bayesiana: Una Guía intuitiva para urólogos y clínicos

Given the limitations of frequentist method for null hypothesis significance testing, different authors recommend alternatives such as Bayesian inference. A poor understanding of both statistical frameworks is common among clinicians. The present is a gentle narrative review of the frequentist and Bayesian methods intended for physicians not familiar with mathematics. The frequentist p-value is the probability of finding a value equal to or higher than that observed in a study, assuming that the null hypothesis (H0) is true. The H0 is rejected or not based on a p threshold of 0.05, and this dichotomous approach does not express the probability that the alternative hypothesis (H1) is true. The Bayesian method calculates the probability of H1 and H0 considering prior odds and the Bayes factor (Bf). Prior odds are the researcher's belief about the probability of H1, and the Bf quantifies how consistent the data is concerning H1 and H0. The Bayesian prediction is not dichotomous but is expressed in continuous scales of the Bf and of the posterior odds. The JASP software enables the performance of both frequentist and Bayesian analyses in a friendly and intuitive way, and its application is displayed at the end of the paper. In conclusion, the frequentist method expresses how consistent the data is with H0 in terms of p-values, with no consideration of the probability of H1. The Bayesian model is a more comprehensive prediction because it quantifies in continuous scales the evidence for H1 versus H0 in terms of the Bf and the

Dadas las limitaciones del método de significancia frecuentista basado en la hipótesis nula, diferentes autores recomiendan alternativas como la inferencia bayesiana. Es común entre los médicos una comprensión deficiente de ambos marcos estadísticos. Esta es una revisión narrativa amigable de los métodos frecuentista y bayesiano dirigida quienes no están familiarizados con las matemáticas. El valor de p frecuentista es la probabilidad de encontrar un valor igual o superior al observado en un estudio, asumiendo que la hipótesis nula (H0) es cierta. La H0 se rechaza o no con base en un umbral p de 0.05, y este enfoque dicotómico no expresa la probabilidad de que la hipótesis alternativa (H1) sea verdadera. El método bayesiano calcula la probabilidad de H1 y H0 considerando las probabilidades a priori y el factor de Bayes (fB). Las probabilidades a priori son la creencia del investigador sobre la probabilidad de H1, y el fB cuantifica cuán consistentes son los datos con respecto a H1 y H0. La predicción bayesiana no es dicotómica, sino que se expresa en escalas continuas del fB y de las probabilidades a posteriori. El programa JASP permite realizar análisis frecuentista y bayesiano de una forma simple e intuitiva, y su aplicación se muestra al final del documento. En conclusión, el método frecuentista expresa cuán consistentes son los datos con H0 en términos de valores p, sin considerar la probabilidad de H1. El modelo bayesiano es una predicción más completa porque cuantifica en escalas continuas la evidencia de H1 versus H0 en términos del fB y de las probabilidades a posteriori.

Uso de genomas de SARS-CoV -2 para la estimación del número reproductivo efectivo (Rt) en Perú durante marzo y abril del 2020

La comprensión de la COVID-19, provocada por el coronavirus de tipo 2 (SARS-CoV-2) causante de síndrome respiratorio agudo severo, utilizando un enfoque multidisciplinario, es esencial para mejorar la toma de decisiones basadas en evidencia. Se estimó el número reproductivo efectivo (Rt) en Perú a partir de 113 genomas completos generados por el Instituto Nacional de Salud (INS) del Perú almacenados en la base de datos pública GISAID. La tendencia mostrada por el Rt durante marzo y abril del 2020 fue similar a otras estimaciones epidemiológicas. El Rt disminuyó considerablemente durante la primera quincena de marzo, alcanzando su menor valor la semana posterior al inicio de la cuarentena, pero aumentó moderadamente desde la quincena de abril. Se discute las implicancias de las medidas tempranas tomadas para mitigar la transmisión. La vigilancia genómica será una herramienta necesaria para conocer la transmisión y evolución del virus, y complementará la información epidemiológica.

The understanding of COVID-19, caused by the SARS-CoV-2, is essential to improve evidence-based public health policies. The effective reproductive number (Rt) in Peru was estimated using information from 113 complete genomes sequenced by the Instituto Nacional de Salud del Perú (INS), available in the GISAID public database. The Rt trend during March and April of 2020 was found to be similar to results from other epidemiological reports. The Rt decreased during the first two weeks of March. Its lowest value was reported during the week after the quarantine began. The Rt increased moderately after the second week of April. The implication of early decisions taken to mitigate the transmission are discussed. Genomic surveillance will be necessary to understand the transmission and evolution of SARS-CoV-2 in Peru, and will complement the epidemiological information.

Toxicity of ß-(1→3, 1→6)-á´ -glucans produced by Diaporthe sp. endophytes on Metarhizium anisopliae (Metschnikoff) Sorokin assessed by conidia germination speed parameter / Toxicidade de ß- (1 → 3, 1 → 6) -á´ -glucanas produzidas por endófitos Diaporthe sp. sobre Metarhizium anisopliae (Metschnikoff) Sorokin avaliada pelo parâmetro de velocidade de germinação dos conídios

We have previously reported that ß-(1→3,1→6)-ᴅ-glucans produced by endophytes Diaporthe sp. G27-60 and G65-65 (GenBank accession codes JF766998 and JF767007, respectively) are promising anti-proliferation agents against human breast carcinoma (MCF-7) and hepatocellular carcinoma (HepG2-C3A) cells. However, the literature fails to describe the effects of Diaporthe exopolysaccharides (EPS) on eukaryotic healthy cells. The fungus Metarhiziumanisopliae has been employed as model-system to evaluate the toxicity of pharmaceutical and agricultural-interest substances, taking into account, among other parameters, the speed of conidia germination. Current study verified the effect of different concentrations of Diaporthe ß-glucans on the germination speed of M. anisopliae. Conidia were incubated with ß-glucans treatments (50, 200 and 400 µg/mL) at 28ºC, sampled during 24 h and analyzed by light microscopy. At the end of a 24-h incubation, the amount of germinated conidia reached ≈99% for controls and ranged between 97.7 and 98.6% for treatments. Bayesian analysis indicated that Diaporthe glucans had no toxicity on M. anisopliaeand the curve of germination occurred as expected for this fungal strain. Considering the validity of filamentous fungi as model-systems, results are important data on the toxicity of endophytic EPS on healthy cells and may be associated with our previous results obtained for these polymers against tumor cells.

Anteriormente, um estudo mostrou que ß-(1→3,1→6)-ᴅ-glucanas produzidas pelos endófitos Diaporthe sp. G27-60 e G65-65 (códigos de acesso no GenBank JF766998 e JF767007, respectivamente) são agentes promissores com ação antiproliferativa contra células HepG2-C3A (hepatoma humano) e MCF-7 (adenocarcinoma mamário humano). No entanto, os efeitos de exopolissacarídeos (EPS) produzidos por fungos do gênero Diaporthe em células eucarióticas sadias não estão descritos na literatura atual. O fungo Metarhiziumanisopliae tem sido utilizado como sistema-modelo para avaliar a toxicidade de substâncias de interesse farmacêutico e agronômico, considerando, entre outros parâmetros, a velocidade de germinação de conídios. O presente estudo teve como objetivo verificar os efeitos de diferentes concentrações de ß-glucanas produzidas por Diaporthe sp. sobre a velocidade de germinação de M. anisopliae. Os conídios foram incubados com os tratamentos de ß-glucanas (50, 200 e 400 µg/mL) a 28 ºC, com amostras coletadas ao longo de 24 h, e analisados por microscopia de luz. Ao final das 24 h de incubação, o total de conídios germinados nos controles foi de ≈99%, e variou entre 97,7 e 98,6% para os tratamentos. A análise bayesiana indicou que as glucanas de Diaporthe sp. não apresentaram toxicidade sobre M. anisopliae, e a curva de germinação atendeu ao esperado para essa linhagem fúngica. Considerando a validade dos fungos filamentosos como sistemas-modelo, esses resultados representam dados importantes sobre a toxicidade dos EPS de endófitos sobre células sadias e podem ser associados aos resultados anteriormente obtidos para esses polímeros em testes contra células tumorais.

Evaluation of the performance of three serological tests for diagnosis of Leishmania infantum infection in dogs using latent class analysis / Avaliação da realização de três testes sorológicos para diagnóstico de infecção por Leishmania infantum em cães utilizando análise de classe latente

Abstract Canine leishmaniasis (CanL) is a disease caused by Leishmania infantum. Serological methods are the most common diagnostic techniques used for the diagnosis of the CanL. The objective of our study was to estimate the sensitivity and specificity of one in-house ELISA kit (ELISA UNIZAR) and three commercially available serological tests (MEGACOR Diagnostik GmbH) including an immunochromatographic rapid test (FASTest LEISH®), an immunofluorescent antibody test (MegaFLUO LEISH®) and an enzyme-linked immunosorbent assay (MegaELISA LEISH®), using latent class models in a Bayesian analysis. Two hundred fifteen serum samples were included. The highest sensitivity was achieved for FASTest LEISH® (99.38%), ELISA UNIZAR (99.37%), MegaFLUO LEISH® (99.36%) followed by MegaELISA LEISH® (98.49%). The best specificity was obtained by FASTest LEISH® (98.43%), followed by ELISA UNIZAR (97.50%), whilst MegaFLUO LEISH® and MegaELISA LEISH® obtained the lower specificity (91.94% and 91.93%, respectively). The results of present study indicate that the immunochromatographic rapid test evaluated FASTest LEISH® show similar levels of sensitivity and specificity to the quantitative commercial tests. Among quantitative serological tests, sensitivity and specificity were similar considering ELISA or IFAT techniques.

Resumo A leishmaniose canina (Lcan) é uma causada pela Leishmania infantum. Os métodos sorológicos são as técnicas diagnósticas mais utilizadas para o diagnóstico da leishmaniose canina. O objetivo do nosso estudo foi estimar a sensibilidade e a especificidade de um kit ELISA interno (ELISA UNIZAR) e de três testes sorológicos disponíveis comercialmente, feitos pelo mesmo fabricante (MEGACOR Diagnostik GmbH), incluindo um teste rápido imunocromatográfico (FASTest LEISH®), um teste de anticorpos imunofluorescentes (Megafluo LEISH®) e um ensaio de imunoabsorção enzimática (Megaelisa LEISH®), utilizando-se modelos de classe latentes numa análise bayesiana. Foram incluídas duzentas e quinze amostras de soro. A maior sensibilidade foi alcançada para Fastest LEISH® (99,38%), ELISA UNIZAR (99,37%), Megafluo LEISH® (99,36%) seguida por Megaelisa LEISH® (98,49%). A melhor especificidade foi obtida por FASTest LEISH® (98,43%), seguida por ELISA UNIZAR (97,50%), enquanto Megafluo LEISH® e Megaelisa LEISH® obtiveram a menor especificidade (91,94% e 91,93%, respectivamente). Os resultados do presente estudo indicam que o teste rápido imunocromatográfico, avaliado por FASTest LEISH® mostra níveis similares de sensibilidade e especificidade aos testes comerciais quantitativos incluídos. Entre os testes sorológicos quantitativos, a sensibilidade e a especificidade foram semelhantes, considerando-se as técnicas de ELISA ou IFI.

Recent advances in Bayesian inference of isolation-with-migration models

Isolation-with-migration (IM) models have become popular for explaining population divergence in the presence of migrations. Bayesian methods are commonly used to estimate IM models, but they are limited to small data analysis or simple model inference. Recently three methods, IMa3, MIST, and AIM, resolved these limitations. Here, we describe the major problems addressed by these three software and compare differences among their inference methods, despite their use of the same standard likelihood function.

Bayesian model and spatial analysis of oral and oropharynx cancer mortality in Minas Gerais, Brazil / Modelo Bayesiano e análise espacial da mortalidade por câncer de boca e orofaringe em Minas Gerais, Brasil

Abstract The objective of this study was to determine of oral and oropharynx cancer mortality rate and the results were analyzed by applying the Spatial Analysis of Empirical Bayesian Model. To this end, we used the information contained in the International Classification of Diseases (ICD-10), Chapter II, Category C00 to C14 and Brazilian Mortality Information System (SIM) of Minas Gerais State. Descriptive statistics were observed and the gross rate of mortality was calculated for each municipality. Then Empirical Bayesian estimators were applied. The results showed that, in 2012, in the state of Minas Gerais, were registered 769 deaths of patients with cancer of oral and oropharynx, with 607 (78.96%) men and 162 (21.04%) women. There was a wide variation in spatial distribution of crude mortality rate and were identified agglomeration in the South, Central and North more accurately by Bayesian Estimator Global and Local Model. Through Bayesian models was possible to map the spatial clustering of deaths from oral cancer more accurately, and with the application of the method of spatial epidemiology, it was possible to obtain more accurate results and provide subsidies to reduce the number of deaths from this type of cancer.

Resumo O objetivo deste estudo foi determinar a taxa de mortalidade por câncer de boca e aplicar o Modelo Bayesiano Empírico e a Análise Espacial para suavizar a taxa bruta de mortalidade por câncer de boca e orofaringe. Foi usado o Capítulo II da Classificação Internacional de Doenças (CID-10) para Categorias C00 a C14. Os dados foram extraídos do Sistema de Informações sobre Mortalidade do Brasil (SIM) do Estado de Minas Gerais. As estatísticas descritivas e as taxas brutas de mortalidade foram calculadas para cada município. Posteriormente, foram aplicados os estimadores Bayesianos Empíricos. Em 2012, em Minas Gerais, foram registradas 769 mortes para o câncer de boca e orofaringe, dos quais 607 (78,96%) eram homens e 162 (21,04%) mulheres. Houve uma grande variação na distribuição espacial da taxa de mortalidade bruta. Foi possível identificar aglomeração nas regiões Sul, Central e Norte com maior precisão pelo Estimador Bayesiano Modelo Global e Local. Através dos Modelos Bayesian foi possível mapear aglomeração espacial de mortes por câncer de boca e orofaringe com maior precisão. Assim, pela epidemiologia espacial foi possível obter resultados mais precisos e fornecer subsídios para ações para reduzir a mortalidade por este tipo de câncer.

Bayesian Network Model to Evaluate the Effectiveness of Continuous Positive Airway Pressure Treatment of Sleep Apnea / 대한의료정보학회지

OBJECTIVES: The association between obstructive sleep apnea (OSA) and mortality or serious cardiovascular events over a long period of time is not clearly understood. The aim of this observational study was to estimate the clinical effectiveness of continuous positive airway pressure (CPAP) treatment on an outcome variable combining mortality, acute myocardial infarction (AMI), and cerebrovascular insult (CVI) during a follow-up period of 15.5 years (186 ± 58 months). METHODS: The data set consisted of 978 patients with an apnea-hypopnea index (AHI) ≥5.0. One-third had used CPAP treatment. For the first time, a data-driven causal Bayesian network (DDBN) and a hypothesis-driven causal Bayesian network (HDBN) were used to investigate the effectiveness of CPAP. RESULTS: In the DDBN, coronary heart disease (CHD), congestive heart failure (CHF), and diuretic use were directly associated with the outcome variable. Sleep apnea parameters and CPAP treatment had no direct association with the outcome variable. In the HDBN, CPAP treatment showed an average improvement of 5.3 percentage points in the outcome. The greatest improvement was seen in patients aged ≤55 years. The effect of CPAP treatment was weaker in older patients (>55 years) and in patients with CHD. In CHF patients, CPAP treatment was associated with an increased risk of mortality, AMI, or CVI. CONCLUSIONS: The effectiveness of CPAP is modest in younger patients. Long-term effectiveness is limited in older patients and in patients with heart disease (CHD or CHF).

Comparing definitions of spatial relations for the analysis of geographic disparities in mortality within a Bayesian mixed-effects framework / Comparação de definições de relações espaciais para a análise das desigualdades geográficas na mortalidade no quadro de efeitos mistos bayesiana

ABSTRACT: Objective: To analyze the conceptual and technical differences between three definitions of spatial relations within a Bayesian mixed-effects framework: classical multilevel definition, spatial multiple membership definition and conditional autoregressive definition with an illustration of the estimate of geographic disparities in early neonatal mortality in Colombia, 2011-2014. Methods: A registry based cross-sectional study was conducted. Births and early neonatal deaths were obtained from the Colombian vital statistics registry for 2011-2014. Crude and adjusted Bayesian mixed effects regressions were performed for each definition of spatial relation. Model fit statistics, spatial autocorrelation of residuals and estimated mortality rates, geographic disparity measures, relative ratios and relative differences were compared. Results: The definition of spatial relations between municipalities based on the conditional autoregressive prior showed the best performance according to both fit statistics and residual spatial pattern analyses. Spatial multiple membership definition had a poor performance. Conclusion: Bayesian mixed effects regression with conditional autoregressive prior as an analytical framework may be an important contribution to epidemiological design as an improved alternative to ecological methods in the analyses of geographic disparities of mortality, considering potential ecological bias and spatial model misspecification.

RESUMO: Objetivo: Analisar as diferenças conceptuais e técnicas entre três definições de relações espaciais dentro do quadro de efeitos mistos bayesiano: definição multinível clássica, definição de filiação múltipla espacial e definição condicional auto regressivo com uma ilustração da estimativa das disparidades geográficas na mortalidade neonatal precoce na Colômbia, 2011-2014. Métodos: Foi realizado um estudo transversal de base do registro. Nascimentos e mortes neonatais precoces foram obtidos a partir do registro de estatísticas vitais Colombiano para o período 2011-2014. Regressões mistas bayesianas brutos e ajustados foram realizadas para cada definição de relação espacial. As estatísticas de ajuste do modelo, autocorrelação espacial dos resíduos, as estimativas das taxas de mortalidade, as medidas de disparidade geográfica, as relações relativas e as diferenças relativas foram comparadas. Resultados: A definição das relações espaciais entre os municípios com base no priori condicional auto regressivo apresentou o melhor desempenho de acordo com as estatísticas de ajuste e a análises de padrão espacial dos resíduos. A definição de filiação múltipla espacial mostrou o mau desempenho. Conclusão: A regressão de efeitos mistos bayesiana com priori condicional auto regressivo como quadro analítico pode ser uma contribuição importante para desenho epidemiológico como uma alternativa melhorada aos métodos ecológicos nas análises das desigualdades geográficas, considerando e potencial viés ecológico e má especificação do modelo espacial.

Evaluation of Related Risk Factors in Number of Musculoskeletal Disorders Among Carpet Weavers in Iran

BACKGROUND: Musculoskeletal disorders (MSDs) are a common problem among carpet weavers. This study was undertaken to introduce affecting personal and occupational factors in developing the number of MSDs among carpet weavers. METHODS: A cross-sectional study was performed among 862 weavers in seven towns with regard to workhouse location in urban or rural regions. Data were collected by using questionnaires that contain personal, workplace, and information tools and the modified Nordic MSDs questionnaire. Statistical analysis was performed by applying Poisson and negative binomial mixed models using a full Bayesian hierarchical approach. The deviance information criterion was used for comparison between models and model selection. RESULTS: The majority of weavers (72%) were female and carpet weaving was the main job of 85.2% of workers. The negative binomial mixed model with lowest deviance information criterion was selected as the best model. The criteria showed the convergence of chains. Based on 95% Bayesian credible interval, the main job and weaving type variables statistically affected the number of MSDs, but variables age, sex, weaving comb, work experience, and carpet weaving looms were not significant. CONCLUSION: According to the results of this study, it can be concluded that occupational factors are associated with the number of MSDs developing among carpet weavers. Thus, using standard tools and decreasing hours of work per day can reduce frequency of MSDs among carpet weavers.

Overview of Network Meta-analysis for a Rheumatologist

The need to combine direct and indirect evidence is increasing in clinical fields, and this is especially true when direct evidence is inconclusive. Thus, in recent years, network meta-analysis has been utilized increasingly in medicine. Network meta-analysis is a statistical method that enables comparison of multiple treatments simultaneously-by combining direct and indirect evidence of the relative treatment effects-to assess the comparative effectiveness of multiple interventions even if there are no head-to-head comparisons. Network meta-analysis has some advantages in addressing all treatments for a specific condition, comparing interventions and ranking the efficacy and safety of multiple treatments, and increasing the certainty of evidence by pooling direct and indirect evidence to generate overall estimates. The major assumption in network meta-analysis is exchange-ability of the studies, and other key assumptions include similarity, consistency, and transitivity. The Bayesian approach is used most commonly in network meta-analysis because it provides greater flexibility that allows for the use of more complex models and can produce estimates of rank probabilities. Bayesian network meta-analysis produces treatment rankings according to the probability of being the best treatment, the second best, third best, and so forth. Network meta-analysis is an interesting method that provides useful information for use in by rheumatologists in decision-making.

Big Data Analysis Using Modern Statistical and Machine Learning Methods in Medicine / 대한배뇨장애요실금학회지

In this article we introduce modern statistical machine learning and bioinformatics approaches that have been used in learning statistical relationships from big data in medicine and behavioral science that typically include clinical, genomic (and proteomic) and environmental variables. Every year, data collected from biomedical and behavioral science is getting larger and more complicated. Thus, in medicine, we also need to be aware of this trend and understand the statistical tools that are available to analyze these datasets. Many statistical analyses that are aimed to analyze such big datasets have been introduced recently. However, given many different types of clinical, genomic, and environmental data, it is rather uncommon to see statistical methods that combine knowledge resulting from those different data types. To this extent, we will introduce big data in terms of clinical data, single nucleotide polymorphism and gene expression studies and their interactions with environment. In this article, we will introduce the concept of well-known regression analyses such as linear and logistic regressions that has been widely used in clinical data analyses and modern statistical models such as Bayesian networks that has been introduced to analyze more complicated data. Also we will discuss how to represent the interaction among clinical, genomic, and environmental data in using modern statistical models. We conclude this article with a promising modern statistical method called Bayesian networks that is suitable in analyzing big data sets that consists with different type of large data from clinical, genomic, and environmental data. Such statistical model form big data will provide us with more comprehensive understanding of human physiology and disease.

Molecular characterisation of hepatitis B virus in the resident Chinese population in Panama City

Despite the effectiveness of current hepatitis B virus (HBV) vaccines, it is estimated that 350 million individuals suffer from chronic HBV infection and more than 50% of these affected individuals live on the Asian continent. Panama is a country with a great diversity of foreign groups; the Chinese community is a large example of this phenomenon. There is an urgent need to perform studies that evaluate the prevalence and the genetic diversity of HBV in this community. This study aimed to evaluate the prevalence of HBV and its genotypes and mutant variants in the Chinese population residing in Panama. In total, 320 subjects were enrolled in the study. Forty-two subjects (13.1%) were positive for HBsAg and HBV-DNA from 18 subjects revealed the presence of genotypes B2 and C1. Secondary mutations associated with drug resistance at positions rtV207L and rtN239T of the reverse transcriptase gene were identified. Additionally, the mutation pair A1762T/G1764A was found in three samples and the mutation G1896A was detected in an HBeAg-negative subject. In conclusion, to our knowledge, this is the first study to report high HBV prevalence rates in resident ethnic Chinese in Central America and the presence of genotypes B2 and C1 in this region.

Spatial distribution of suicide incidence rates in municipalities in the state of Espírito Santo (Brazil), 2003-2007: spatial analysis to identify risk areas / Distribuição especial das taxas de incidência de suicídio nos municípios do Estado do Espírito Santo (Brasil), no período de 2003 a 2007

OBJECTIVE: To analyze the spatial distribution of suicide incidence rate in a residential municipality of the state of Espírito Santo (ES), Brazil, from 2003 to 2007. METHODS: Ecologic study of the exploratory kind, based on secondary data. Deaths per suicide, which took place in each municipality of ES, were included in the data according to information provided by the Mortality Information System. For the spatial data analysis, a Bayesian approach was used (Global empirical and Local Bayesian ones) to correct epidemiological rates. Moran's I index was calculated to a worldwide spatial level dependence, and Local Moran (LISA) to a local spatial correlation. The following software applications were used: Excel; R 2.6.2; SPSS 11.5 and TerraView 3.3.1. RESULTS: The geographical localization of the municipalities that showed an incidence rate characterized as the average for suicide after adjustment (EBest Global) forms a corridor in the countryside. Some common characteristics among these municipalities are: a) immigration (Italians, Pomeranians/ Germans); b) rural population (average of 53%); c) supporting economy (agriculture, husbandry and livestock). A global and local spatial correlation was found among the municipalities (p < 0.05). CONCLUSION: The study identified the spatial context where the greatest death incidence rate per suicide occurred in the state of ES, during the mentioned period.

OBJETIVO: Analisar a distribuição espacial das taxas de incidência de suicídio segundo o município de residência no estado do Espírito Santo (2003 a 2007). MÉTODOS: Estudo ecológico do tipo exploratório, baseado em dados secundários. Foram incluídos os óbitos por suicídio ocorridos no período, em cada um dos municípios do Estado, conforme o Sistema de Informação sobre Mortalidade. Para análise espacial dos dados, utilizou-se a abordagem bayesiana (Bayesianos Empírico Global e Local) para correção de taxas epidemiológicas. Calculou-se o índice I de Moran, para dependência espacial em nível global, e o Moran Local (LISA), para correlação espacial local. Foram utilizados os seguintes programas: Excel; R 2.6.2; SPSS 11.5 e TerraView 3.3.1. RESULTADOS: A localização geográfica dos municípios que apresentaram taxa de incidência classificada como média para o suicídio após ajuste (EBest Global) forma um corredor localizado no interior do estado. Algumas características comuns a esses municípios são: a) imigração (italianos e pomerânios/alemães); b) população rural (média 53%); c) base econômica (agricultura, pecuária ou agropecuária). Encontrou-se correlação espacial global e local entre os municípios (p < 0,05). CONCLUSÃO: Identificou-se o contexto espacial onde ocorreram as maiores taxas de incidência dos óbitos por suicídio no estado do Espírito Santo, durante o período.

Prediction of kidney cancer incidence in urban China by age-period-cohort Bayesian model / 中华泌尿外科杂志

Objective To predict the disease burden of kidney cancer and to provide basic information for etiology and control planning.Methods We retrieved incidence data of kidney cancer from 18 urban cancer registries from National Central Cancer Registry during ten years period from 1998 to 2007.Ageperiod-cohort Bayesian model was applied for modeling to predict kidney cancer incidence in urban China in 2008-2015.Results Between 1998 and 2007,the incidence of kidney cancer in urban registration areas kept increasing dramatically.Incidence for male raised from 3.12/100 000 in 1998 to 5.36/100 000 in 2007 and from 1.66/100 000 to 2.67/100 000 for female.Different models showed that the increase was mainly caused by a cohort effect (P ＜ 0.001).The predicted incidence rate of kidney cancer for the year 2015 is 9.93 per 100 000 in male and 4.54 per 100 000 in female.The number of new cases will rise to 52 259 in 2015,including 36 616 men and 15 643 women.Conclusions The burden of kidney cancer in urban areas would increase due to the effect of age and cohort.Kidney cancer will become one of the main cancers threatening people's health in urban areas in China.Etiology research and planning of prevention and control for kidney cancer should be enhanced.

The complete mitochondrial genome of the small yellow croaker and partitioned Bayesian analysis of Sciaenidae fish phylogeny

To understand the phylogenetic position of Larimichthys polyactis within the family Sciaenidae and the phylogeny of this family, the organization of the mitochondrial genome of small yellow croaker was determined herein. The complete, 16,470 bp long, mitochondrial genome contains 37 mitochondrial genes (13 protein-coding, 2 ribosomal RNA and 22 transfer RNA genes), as well as a control region (CR), as in other bony fishes. Comparative analysis of initiation/termination codon usage in mitochondrial protein-coding genes of Percoidei species, indicated that COI in Sciaenidae entails an ATG/AGA codon usage different from other Percoidei fishes, where absence of a typical conserved domain or motif in the control regions is common. Partitioned Bayesian analysis of 618 bp of COI sequences data were used to infer the phylogenetic relationships within the family Sciaenidae. An improvement in harmonic mean -lnL was observed when specific models and parameter estimates were assumed for partitions of the total data. The phylogenetic analyses did not support the monophyly of Otolithes, Argyrosomus, and Argyrosominae. L. polyactis was found to be most closely related to Collichthys niveatus, whereby, according to molecular systematics studies, the relationships within the subfamily Pseudosciaenidae should be reconsidered.

A Bayesian approach to estimate the accuracy of "in-house" ELISA assay to measure rabies antibodies from compulsory vaccinated dogs and cattle

Rabies is a vaccine-preventable disease that causes acute encephalitis in mammals, and it is still a significant public health problem in numerous countries. lnfected dogs represent the main vectors involved in human rabies. Additionally, cattle rearing close to geographic areas where vampire bats are found presents an important connection with rural epidemiology. We applied two "in-house" enzyme-linked immunosorbent assay (ELISA) methodologies, considered alternatives to measure antibodies from vaccinated dogs and cattle, without employing the gold standard approach. The ELISA assays were performed on individual serum samples taken from domestic adult dogs and cows compulsory vaccinated against rabies (147 urban dogs and 64 cows; n equal 211). The sandwich and liquid-phase competitive ELISA (scELlSA and ipcELlSA). considered "in-house" assays. were performed according to previous works. The only statistical methodology that allows this study is the Bayesian approach, developed to replace the conventional Hui-Walter paradigm. For conditional independent Bayesian model (one population, two tests and no gold standard) the prior information for sensitivity and specificity of each test, mode, prevalence and transformed (alpha, beta) were submitted to Bayesian inference. The "in-house" IpcELISA revealed 16 - out of 261 serum samples - negative results, whereas in scELISA all results were positive. The Bayesian approach showed that prior information was specified for all parameters; posterior medians were SescELISA 89%, SpscELISA 88%, SPipcELISA 95% SeipcELISA 98%, and prevalence (pi) of 99%, without the use of gold standard analysis to measure specific anti-rabies antibodies

A Study to Validate the Pretest Probability of Malignancy in Solitary Pulmonary Nodule / 결핵및호흡기질환

BACKGROUND: Solitary pulmonary nodules (SPN) are encountered incidentally in 0.2% of patients who undergo chest X-ray or chest CT. Although SPN has malignant potential, it cannot be treated surgically by biopsy in all patients. The first stage is to determine if patients with SPN require periodic observation and biopsy or resection. An important early step in the management of patients with SPN is to estimate the clinical pretest probability of a malignancy. In every patient with SPN, it is recommended that clinicians estimate the pretest probability of a malignancy either qualitatively using clinical judgment or quantitatively using a validated model. This study examined whether Bayesian analysis or multiple logistic regression analysis is more predictive of the probability of a malignancy in SPN. METHODS: From January 2005 to December 2008, this study enrolled 63 participants with SPN at the Kangnam Sacred Hospital. The accuracy of Bayesian analysis and Bayesian analysis with a FDG-PET scan, and Multiple logistic regression analysis was compared retrospectively. The accurate probability of a malignancy in a patient was compared by taking the chest CT and pathology of SPN patients with <30 mm at CXR incidentally. RESULTS: From those participated in study, 27 people (42.9%) were classified as having a malignancy, and 36 people were benign. The result of the malignant estimation by Bayesian analysis was 0.779 (95% confidence interval [CI], 0.657 to 0.874). Using Multiple logistic regression analysis, the result was 0.684 (95% CI, 0.555 to 0.796). This suggests that Bayesian analysis provides a more accurate examination than multiple logistic regression analysis. CONCLUSION: Bayesian analysis is better than multiple logistic regression analysis in predicting the probability of a malignancy in solitary pulmonary nodules but the difference was not statistically significant.