El metaanalisis en la investigacion cientifica médica / Meta-analysis in medical scientific research

Las revisiones sistemáticas y los metaanálisis se han consolidado como una herramienta fundamental para la práctica clínica basada en la evidencia. Inicialmente, el metaanálisis fue propuesto como una técnica que podría mejorar la precisión y la potencia estadística de la investigación procedente de estudios individuales con pequeño tamaño muestral. Sin embargo, uno de sus principales inconvenientes es que suelen comparar no más de 2 intervenciones alternativas a la vez. Los «metaanálisis en red» utilizan técnicas novedosas de análisis que permiten incorporar la información procedente de comparaciones directas e indirectas a partir de una red de estudios que examina los efectos de diversos tratamientos de una manera más completa. Pese a sus potenciales limitaciones, su aplicación en epidemiología clínica podría ser potencialmente útil en situaciones en las que existen varios tratamientos que se han comparado frente a un comparador común. Además, estas técnicas pueden ser relevantes ante una pregunta clínica o de investigación cuando existen múltiples tratamientos que deben ser considerados, o cuando se dispone tanto de información directa como indirecta en el cuerpo de la evidencia.

Systematic reviews and meta-analyses have been established as fundamental tools for evidence-based clinical practice. Initially, meta-analysis was proposed as a technique that could improve the precision and statistical power of individual studies research, with small sample sizes. However, one of its main drawbacks was related to usually comparing only 2 alternatives at a time. "Network metaanalyses" uses novel analytical techniques that allow information from direct and indirect comparisons to be incorporated from a network of studies that examine the effects of various treatments in a more comprehensive way. Despite potential limitations, its application in clinical epidemiology would most likely be useful in situations where there are several treatments that need to be compared against a common comparator. In addition, these techniques may be relevant to answer research questions that involve multiple treatments, or when both direct and indirect information are available in the body of evidence.

Exploring the QSAR's predictive truthfulness of the novel N-tuple discrete derivative indices on benchmark datasets.

Graph derivative indices (GDIs) have recently been defined over N-atoms (N = 2, 3 and 4) simultaneously, which are based on the concept of derivatives in discrete mathematics (finite difference), metaphorical to the derivative concept in classical mathematical analysis. These molecular descriptors (MDs) codify topo-chemical and topo-structural information based on the concept of the derivative of a molecular graph with respect to a given event (S) over duplex, triplex and quadruplex relations of atoms (vertices). These GDIs have been successfully applied in the description of physicochemical properties like reactivity, solubility and chemical shift, among others, and in several comparative quantitative structure activity/property relationship (QSAR/QSPR) studies. Although satisfactory results have been obtained in previous modelling studies with the aforementioned indices, it is necessary to develop new, more rigorous analysis to assess the true predictive performance of the novel structure codification. So, in the present paper, an assessment and statistical validation of the performance of these novel approaches in QSAR studies are executed, as well as a comparison with those of other QSAR procedures reported in the literature. To achieve the main aim of this research, QSARs were developed on eight chemical datasets widely used as benchmarks in the evaluation/validation of several QSAR methods and/or many different MDs (fundamentally 3D MDs). Three to seven variable QSAR models were built for each chemical dataset, according to the original dissection into training/test sets. The models were developed by using multiple linear regression (MLR) coupled with a genetic algorithm as the feature wrapper selection technique in the MobyDigs software. Each family of GDIs (for duplex, triplex and quadruplex) behaves similarly in all modelling, although there were some exceptions. However, when all families were used in combination, the results achieved were quantitatively higher than those reported by other authors in similar experiments. Comparisons with respect to external correlation coefficients (q2ext) revealed that the models based on GDIs possess superior predictive ability in seven of the eight datasets analysed, outperforming methodologies based on similar or more complex techniques and confirming the good predictive power of the obtained models. For the q2ext values, the non-parametric comparison revealed significantly different results to those reported so far, which demonstrated that the models based on DIVATI's indices presented the best global performance and yielded significantly better predictions than the 12 0-3D QSAR procedures used in the comparison. Therefore, GDIs are suitable for structure codification of the molecules and constitute a good alternative to build QSARs for the prediction of physicochemical, biological and environmental endpoints.

Sisvar: a computer statistical analysis system / Sisvar: um sistema computacional de análise estatística

Sisvar is a statistical analysis system, first released in 1996 although its development began in 1994. The first version was done in the programming language Pascal and compiled with Borland Turbo Pascal 3. Sisvar was developed to achieve some specific goals. The first objective was to obtain software that could be used directly on the statistical experimental course of the Department of Exact Science at the Federal University of Lavras. The second objective was to initiate the development of a genuinely Brazilian free software program that met the demands and peculiarities of research conducted in the country. The third goal was to present statistical analysis software for the Brazilian scientific community that would allow research results to be analyzed efficiently and reliably. All of the initial goals were achieved. Sisvar gained acceptance by the scientific community because it provides reliable, accurate, precise, simple and robust results, and allows users a greater degree of interactivity.

O Sisvar é um sistema de análise estatística que foi lançado em 1996, embora o seu desenvolvimento tenha sido iniciado em 1994. A primeira versão foi desenvolvida em linguagem de programação Pascal e compilada com o Borland Turbo Pascal 3. O Sisvar foi desenvolvido em virtude de algumas razões específicas. O primeiro objetivo foi o de obter um software que pudesse ser usado diretamente no curso de estatística experimental do Departamento de Ciências Exatas da Universidade Federal de Lavras. O segundo objetivo foi o de iniciar o desenvolvimento de um software genuinamente brasileiro, gratuito que atendesse às demandas e peculiaridades das pesquisas realizadas no país. O terceiro objetivo foi o de apresentar um software de análise estatística para a comunidade científica brasileira que permitisse que os resultados da pesquisa pudessem ser analisados de forma eficiente e confiável. Todos os objetivos iniciais foram atingidos. O motivo da aceitação Sisvar pela comunidade científica é decorrente do fato de que ele é capaz de permitir uma maior interatividade com o usuário e produzir análises confiáveis, pelo fato de elas serem exatas, precisas, simples e robustas.

Aceitação sensorial de filés de peito de frango submetidos a diferentes tratamentos de descongelamento e fritura / Sensory acceptance of chicken breasts fillets submitted to different treatments of thawing and frying

Este trabalho teve como objetivo verificar, através do teste sensorial de comparação múltipla, a existência de diferenças estatisticamente perceptíveis pelos consumidores na ingestão de filés de frango descongelados lentamente (sob refrigeração) ou rapidamente (em microondas) e posteriormente fritos daqueles previamente fritos, congelados e descongelados rapidamente e lentamente. Houve diferença significativa a 1% de probabilidade (p < 0,01) entre os tratamentos utilizados. Sensorialmente, o descongelamento rápido em forno de microondas apresentou melhores resultados devido à maior suculência do filé. Entretanto, não houve diferença significativa deste tratamento com o descongelamento de filés de frango previamente fritos. O forno de microondas é um método rápido de descongelamento que pode ser utilizado para carne de frango em substituição ao método tradicional à medida que proporciona características sensoriais desejáveis ao produto. A comercialização de filés fritos e congelados, prontos para consumo é uma nova alternativa para as indústrias alimentícias.

This study aimed to verify, through the sensory test of multiple comparison, differences statistically perceived by consumers in the intake of chicken fillets thawed slowly (under refrigeration) or rapidly (in microwave) and then fried those previously fried, frozen and thawed rapidly and slowly. Significant difference at 1% (p <0.01) among the treatments used. Sensorially, the rapid thawing in a microwave oven with better results due to increased succulence of steak. However, no significant difference of treatment with the thawing of fillets of fried chicken before. The microwave oven is a rapid method for thawing that can be used for chicken meat to replace the traditional method as it provides desirable sensory characteristics to the product. The marketing of chicken fillets fried and frozen, ready for consumption is a new alternative for the food industries.

Analyzing one-way experiments: a piece of cake of a pain in the neck?

Statistics may be intricate. In practical data analysis many researchers stick to the most common methods, not even trying to find out whether these methods are appropriate for their data and whether other methods might be more useful. In this paper I attempt to show that when analyzing even simple one-way factorial experiments, a lot of issues need to be considered. A classical method to analyze such data is the analysis of variance, quite likely the most often used statistical method in agricultural, biological, ecological and environmental studies. I suspect this is why this method is quite often applied inappropriately: since the method is that common, it does not require too much consideration-this is how some may think. An incorrect analysis may provide false interpretation and conclusions, so one should pay careful attention to which approach to use in the analysis. I do not mean that one should apply difficult or complex statistics; I rather mean that one should apply a correct method that offers what one needs. So, various problems concerned with the analysis of variance and other approaches to analyze such data are discussed in the paper, including checking within-group normality and homocedasticity, analyzing experiments when any of these assumptions is violated, outliers presence, multiple comparison procedures, and other issues.

Realizar análises estatísticas pode ser complicado. Em situações práticas muitos pesquisadores utilizam os procedimentos de análise mais comuns, sem investigar se os mesmos são apropriados para os seus resultados, ou mesmo se há outros métodos que poderiam ser mais adequados. Nesse artigo buscarei mostrar que mesmo na análise de experimentos de classificação simples (com um único fator) vários aspectos precisam ser considerados. A forma clássica de análise desse tipo de dados é a análise de variância, que é provavelmente o método estatístico mais usado na agricultura, biologia, ecologia e estudos de meio ambiente. Suspeito que essa é a razão pela qual tal método é frequentemente usado de forma inapropriada: uma vez que ele é muito usado, não suscita maiores considerações. Imagino que seja esse raciocínio que muitos pesquisadores devam empregar. Análises incorretas podem fornecer falsas interpretações e conclusões, e dessa forma é importante prestar atenção na escolha do procedimento a ser usado na análise. Não estou sugerindo que algum método difícil ou complexo deva ser usado, mas sim que um método correto seja adotado, de forma a fornecer os resultados adequados. Dessa forma, vários problemas relacionados à análise de variância e outras abordagens para analisar esse tipo de dados são discutidas nesse artigo, incluindo verificações de normalidade e homogeneidade de variâncias, análise de experimentos com violação dessas pressuposições, presença de dados discrepantes, testes de comparações múltiplas, além de alguns outros problemas.

Analyzing one-way experiments: a piece of cake of a pain in the neck?

Statistics may be intricate. In practical data analysis many researchers stick to the most common methods, not even trying to find out whether these methods are appropriate for their data and whether other methods might be more useful. In this paper I attempt to show that when analyzing even simple one-way factorial experiments, a lot of issues need to be considered. A classical method to analyze such data is the analysis of variance, quite likely the most often used statistical method in agricultural, biological, ecological and environmental studies. I suspect this is why this method is quite often applied inappropriately: since the method is that common, it does not require too much consideration-this is how some may think. An incorrect analysis may provide false interpretation and conclusions, so one should pay careful attention to which approach to use in the analysis. I do not mean that one should apply difficult or complex statistics; I rather mean that one should apply a correct method that offers what one needs. So, various problems concerned with the analysis of variance and other approaches to analyze such data are discussed in the paper, including checking within-group normality and homocedasticity, analyzing experiments when any of these assumptions is violated, outliers presence, multiple comparison procedures, and other issues.

Realizar análises estatísticas pode ser complicado. Em situações práticas muitos pesquisadores utilizam os procedimentos de análise mais comuns, sem investigar se os mesmos são apropriados para os seus resultados, ou mesmo se há outros métodos que poderiam ser mais adequados. Nesse artigo buscarei mostrar que mesmo na análise de experimentos de classificação simples (com um único fator) vários aspectos precisam ser considerados. A forma clássica de análise desse tipo de dados é a análise de variância, que é provavelmente o método estatístico mais usado na agricultura, biologia, ecologia e estudos de meio ambiente. Suspeito que essa é a razão pela qual tal método é frequentemente usado de forma inapropriada: uma vez que ele é muito usado, não suscita maiores considerações. Imagino que seja esse raciocínio que muitos pesquisadores devam empregar. Análises incorretas podem fornecer falsas interpretações e conclusões, e dessa forma é importante prestar atenção na escolha do procedimento a ser usado na análise. Não estou sugerindo que algum método difícil ou complexo deva ser usado, mas sim que um método correto seja adotado, de forma a fornecer os resultados adequados. Dessa forma, vários problemas relacionados à análise de variância e outras abordagens para analisar esse tipo de dados são discutidas nesse artigo, incluindo verificações de normalidade e homogeneidade de variâncias, análise de experimentos com violação dessas pressuposições, presença de dados discrepantes, testes de comparações múltiplas, além de alguns outros problemas.

Differential effects of neuromuscular blockers on twitches and tetani in the isolated rat muscle: a multiple comparison study using simultaneous confidence intervals

In the present work a comparative quantitative evaluation of the differential effects of neuromuscular blockers on twitches and tetani was performed, encompassing atracurium, cisatracurium, mivacurium, pancuronium, rocuronium and vecuronium. The sciatic nerve-extensor digitorum longus muscle of the rat was used, in vitro. Twitches were evoked at 0.1 Hz and tetani at 50 Hz. The differential effects of the studied compounds on twitches and tetani were statistically compared using simultaneous confidence intervals for the ratios between mean IC(50) for the block of twitches and mean IC(50) for the block of tetani. The results of ratios of mean IC(50) together with their corresponding 95% simultaneous confidence intervals were vecuronium 2.5 (1.8-3.5); mivacurium 3.8 (3.0-4.9); pancuronium 3.9 (2.0-7.6); rocuronium 6.1 (3.8-9.9); atracurium 9.0 (6.4-12.6); cisatracurium 13.1 (6.0-28.4). Using the criteria that neuromuscular blockers displaying disjunct confidence intervals for the ratios of mean IC(50) differ statistically with regard to differential effects on twitches and tetani, significant differences in ratios of IC(50) were detected in the following cases vecuronium vs. rocuronium, vs. atracurium and vs. cisatracurium and mivacurium vs cisatracurium and vs. atracurium. The results show that the magnitude of the differential effects of neuromuscular blockers on twitches and tetani, as evaluated in the present work in the form of ratios of mean IC(50), does not depend on the chemical structure (comparing steroidal and isoquinolinic compounds), but seems to depend on differential pre- and post-synaptic effects of the compounds. It is also suggested that the greater the ability of a compound to block twitches and tetani in a differential manner, the safer is the compound from the clinical anesthesiology viewpoint.