Comparison of Bayesian method and multiple linear regression method in predicting warfarin dose model / 中国临床药理学与治疗学

AIM: To evaluate the predictive performance of Warfarin Dose Calculator (WDC) based on Bayesian method, Warfarin Dosing and International Warfarin Pharmacogenetics Consortium (IWPC) Warfarin Dose Calculator based on Multiple Linear Regression (MLR) in the absence of warfarin related genotypes, in order to provide help for patients using warfarin in areas where there is unconditional warfarin related genotypes detection. METHODS: The predicted performance of each tool was evaluated by calculating the mean prediction error (MPE), root mean square error (RMSE) and the percentage of patients whose prediction error was within ±20% of the actual maintenance dose. All statistical analyses were performed by SPSS statistics 26.0 software. RESULTS: The Posteriori of the WDC had the lowest MPE, RMSE and highest percentage of patients whose prediction errors within ±20% of the actual maintenance dose. In addition, the predictive accuracy of the Priori and Posteriori of WDC is significantly higher than that of Warfarin Dosing and IWPC warfarin dose calculator. CONCLUSION: Among the three assistant tools for warfarin dose prediction, Warfarin Dose Calculator based on Bayesian method may be more suitable for warfarin dose prediction of patients in unconditional warfarin related genotypes detection area.

Pharmaceutical Care of a Neonate with Septicemia Based on Population Pharmacokinetics / 医药导报

Objective To introduce a pharmaceutical care method based on population pharmacokinetics(PPK)and Bayesian method. Methods A predictive model for individualized vancomycin dosing was established based on the JPKD-Bayesian software and a PPK model according to the intervenous drop infusion of vancomycin in Chinese children.Individualized dosage regimen of vancomycin was devised for a neonate with septicemia caused by methicillin-resistant staphylococcus epidermidis (MRSE)using the predictive model. Results The model prediction error of the trough concentration of vancomycin was 0.8 mg·L-1 ,and the weighted residual(WRES)was 8.7%,and thus the predictive accuracy of the model was satisfactory.The MRSE infection in this patient was effectively controlled following individualized vancomycin dosage regimen according to the model predicted results,and there were no vancomycin-caused adverse reactions. Conclusion Application of advanced pharmaceutical knowledge such as PPK contributes to clinical medication,and it can promote the quality of pharmaceutical care provided by clinical pharmacists.

Investigating the Effects of Imputation Methods for Modelling Gene Networks Using a Dynamic Bayesian Network from Gene Expression Data

Background: Gene expression data often contain missing expression values. Therefore, several imputation methods have been applied to solve the missing values, which include k-nearest neighbour (kNN), local least squares (LLS), and Bayesian principal component analysis (BPCA). However, the effects of these imputation methods on the modelling of gene regulatory networks from gene expression data have rarely been investigated and analysed using a dynamic Bayesian network (DBN). Methods: In the present study, we separately imputed datasets of the Escherichia coli S.O.S. DNA repair pathway and the Saccharomyces cerevisiae cell cycle pathway with kNN, LLS, and BPCA, and subsequently used these to generate gene regulatory networks (GRNs) using a discrete DBN. We made comparisons on the basis of previous studies in order to select the gene network with the least error. Results: We found that BPCA and LLS performed better on larger networks (based on the S. cerevisiae dataset), whereas kNN performed better on smaller networks (based on the E. coli dataset). Conclusion: The results suggest that the performance of each imputation method is dependent on the size of the dataset, and this subsequently affects the modelling of the resultant GRNs using a DBN. In addition, on the basis of these results, a DBN has the capacity to discover potential edges, as well as display interactions, between genes.

Spatio-temporal patterns of tuberculosis incidence in Ribeirão Preto, State of São Paulo, southeast Brazil, and their relationship with social vulnerability: a Bayesian analysis / Padrões espaço-temporais da incidência de tuberculose em Ribeirão Preto, Estado de São Paulo, sudeste do Brasil, e suas relações com a vulnerabilidade social: uma análise bayesiana

INTRODUCTION: The purpose of this ecological study was to evaluate the urban spatial and temporal distribution of tuberculosis (TB) in Ribeirão Preto, State of São Paulo, southeast Brazil, between 2006 and 2009 and to evaluate its relationship with factors of social vulnerability such as income and education level. METHODS: We evaluated data from TBWeb, an electronic notification system for TB cases. Measures of social vulnerability were obtained from the SEADE Foundation, and information about the number of inhabitants, education and income of the households were obtained from Brazilian Institute of Geography and Statistics. Statistical analyses were conducted by a Bayesian regression model assuming a Poisson distribution for the observed new cases of TB in each area. A conditional autoregressive structure was used for the spatial covariance structure. RESULTS: The Bayesian model confirmed the spatial heterogeneity of TB distribution in Ribeirão Preto, identifying areas with elevated risk and the effects of social vulnerability on the disease. We demonstrated that the rate of TB was correlated with the measures of income, education and social vulnerability. However, we observed areas with low vulnerability and high education and income, but with high estimated TB rates. CONCLUSIONS: The study identified areas with different risks for TB, given that the public health system deals with the characteristics of each region individually and prioritizes those that present a higher propensity to risk of TB. Complex relationships may exist between TB incidence and a wide range of environmental and intrinsic factors, which need to be studied in future research.

INTRODUÇÃO: O objetivo deste estudo ecológico é avaliar a distribuição espacial e temporal da tuberculose (TB) na área urbana de Ribeirão Preto, São Paulo, entre os anos de 2006 e 2009, e estudar as suas relações com fatores de vulnerabilidade social como renda e educação. MÉTODOS: Foram utilizados dados do TBWeb, um sistema de notificação de dados de TB. As medidas de vulnerabilidade social foram obtidas da Fundação SEADE (Sistema Estadual de Análise de Dados) e informações sobre o número de habitantes, educação e renda dos chefes dos domicílios foram obtidas do Instituto Brasileiro de Geografia e Estatística. A análise estatística utilizou um modelo bayesiano de regressão assumindo que os novos casos de TB observados em cada área assumem uma distribuição de Poisson. RESULTADOS: O modelo bayesiano confirmou a heterogeneidade especial da distribuição da TB em Ribeirão Preto, identificando áreas com elevado risco de TB e os efeitos da vulnerabilidade social sobre a doença. Foi evidenciado que a taxa de TB associa-se com as medidas de renda, educação e vulnerabilidade social. Entretanto, são observadas áreas com baixa vulnerabilidade social e alto nível educacional, mas altas taxas de TB. CONCLUSÕES: O estudo identificou áreas com diferentes riscos de TB, permitindo que o sistema público de saúde lide com as diferentes características de cada região e priorize aquelas que apresentem maior propensão de risco de TB. São evidentes relações complexas entre a incidência de TB e um amplo número de fatores ambientais e intrínsecos, o que mostra a necessidade destes serem estudados em trabalhos futuros.

Mortalidade por Neoplasias no Brasil de 2003 a 2007 / The Mortalit y by Neoplasms in Brazil from 2003 to 2007 / La mortandad por Neoplasias en Brasil entre 2003 Y 2007

A incidência de neoplasias no Brasil e no mundo tem aumentado nos últimos anos, vitimando grande número de pessoas anualmente. O trabalho teve como objetivo a análise epidemiológica descritiva da mortalidade por neoplasias no Brasil, de 2003 a 2007. Os dados foram levantados nos registros do Sistema de Informações de Mortalidade do Ministério da Saúde e a aplicação do método estatístico de Bayes rendeu os mapas das razões de mortalidade padronizadas para 425 microrregiões do país. Os resultados indicam que, entre 2003 e 2007, no Brasil: eram do sexo masculino entre 53 e 54por cento das vítimas de neoplasias registradas; em 2007, a maioria das mulheres falecidas com idades entre 30 e 49 anos foram vitimadas por neoplasias; as proporções de óbitos por neoplasias aumentaram no país e em todos os estados, apresentando as maiores taxas no Rio Grande do Sul, Santa Catarina, Paraná, São Paulo e Distrito Federal; muitas microrregiões com baixas taxas de mortalidadepor câncer apresentaram elevadas proporções de óbitos por causas mal definidas. Concluise que as taxas aferidas no Brasil, para as os óbitos por neoplasias, foram menores que as de outros países.

The occurrence of neoplaasm cases has increased in the last few years in Brazil and worldwide, resulting in many deaths every year. This work aims to make a descriptive epidemiologic analysis of the mortality by cancer in Brazil, from 2003 to 2007. Data was taken from records of the Ministry of Health Information System and the application of Bayes? Statistical approach which portrayed maps concerning the reasons of mortality by neoplasms in 425 micro-regions of the country. The results indicate that, between 2003 and 2007, in Brazil: between 53percent and 54percent of the victims of cancer deaths were male; in 2007, most of the women who died from cancer were between the ages of 30 and 49; the proportion of cancerrelated deaths increased throughout the country, with higher rates found in the states of Rio Grande do Sul, Santa Catarina, Paraná, São Paulo and Distrito Federal; many micro-regions having lower rates for cancer- related deaths presented high values of deaths by uncertain causes. This study concludes that the rates determined in Brazil, for cancer-related deaths were lower than in another countries.

En los últimos años, la incidencia de neoplasias ha presentado aumentos em Brasil y en todo el mundo resultando, a cada año, en muchas muertes. El trabajo objetivo el análisis epidemiológico descriptivo de la mortandad por Neoplasias en Brasil, entre 2003 y 2007. Los datos fueron recolectados en el Sistema de Informaciones de Mortandad del Ministerio de la Salud y, para mapear las razones de la mortandad estandarizada de 425 microregiones del país, se ha aplicado el método estadístico de bayes. Los resultados indican que entre los años de 2003 y 2007, en Brasil: 53por ciento a 54por ciento del total de víctimas registradaspor Neoplasia fueron hombres,; en 2007, la mayor proporción fue de mujeres en edades comprendidas entre 30 y 49 años; las muertes por Neoplasias crecieron en todos los estados del país, presentando los mayores índices las regiones de Rio Grande do Sul, Santa Catarina, Paraná, São Paulo y Distrito Federal; varias microregiones con bajos índices de mortandad por cáncer presentaron altas proporciones de muertes por males no determinados. Se concluye que los índices de mortandad por cáncer en Brasil, comparados con otros países, fueron menores.

Measurement of Glomerular Filtration Rate by Rapid Intravenous Injection of a Newly Developed Inulin Fraction / Journal of Rural Medicine

Objective: Since the conventional drip-infusion method for measuring inulin clearance (Cin) has problems related to its accuracy and performance, we explored a more accurate and concise method by rapid intravenous injection of a newly developed inulin fraction (Inulead®), in which spot urine sampling was omitted and the administration period of inulin was shortened from 120 to 5 minutes. Patients and Methods: Twenty seven patients (M/F: 15/12, 67.8 ± 12.9 years old) admitted to the Nephrology ward were enrolled in this study. Inulead®, 1500 mg dissolved in 150 mL of saline, was intravenously administered in 5 minutes. Then, sequential blood samplings and urine collection were performed for 24 hours. Cins were calculated by the following three formulae: (1) a pharmacokinetic analysis using a two compartments model based on the plasma inulin concentration to determine Cin, which was the administered dose divided by the area under the curve (AUC) from 0 to ∞, (2) urinary inulin excretion divided by the AUC for 24 hours and (3) the Bayesian method using a three-point set of plasma inulin concentrations to predict the change of inulin concentration to determine Cin as in 1. These Cins were compared with levels of estimated GFR (eGFR), creatinine clearance (Ccr), serum β2 microglobulin (β2MG) and serum cystatin C (Cys C). Results: Cins obtained by the above three methods were well correlated with each other (r. = 0.9088 – 0.9998) and with eGFR (r. = 0.8286 – 0.8650), Ccr (r. = 0.821 – 0.864), 1/β2MG (r. = 0.631 –0.752) and 1/CysC (r. = 0.830 – 0.857). The averaged differences of each Cin from eGFR were distributed between –4.4 and –4.5 mL/min. Conclusion: Since the Cins by rapid inulin injection showed satisfactory correlation and differences with other GFR parameters, this method will be a good alternative to the drip infusion method, and may reduce the burden of patients and medical staff.