Analysis of the interval between submission and publication in genetics journals.

One of the main factors that attracts authors to choose a journal is the time interval between submission and publication, which varies between journals and subject matter. Here, we evaluated the time intervals between submission and publication according to journal impact factor and continent of author's affiliation, considering articles with authors from single or multiple continents. Altogether, 72 journals indexed in the Web of Science database within the subject matter "Genetics and Heredity", divided by impact factor into four quartiles and randomly selected were analyzed for time intervals from article submission to publication. Data from a total of 46,349 articles published from 2016 to 2020 were collected and analyzed considering the following time intervals: submission to acceptance (SA), acceptance to publication (AP) and submission to publication (SP). The median of the quartiles for the SP interval was 166 (IQR [118-225]) days for Q1, 147 (IQR [103-206]) days for Q2, 161 (IQR [116-226]) days for Q3 and 137 (IQR [69-264]) days for Q4, showing a significant difference among quartiles (p < 0.001). In Q4, median interval of time was shorter in interval SA but longer in interval AP, and overall, articles in Q4 had the shortest interval of time in SP. A potential association of the median time interval and authors' continent was analysed and no significant difference was observed between articles with authors from single versus multiple continents or between continents in articles with authors from only one continent. However, in journals from Q4, time from submission to publication was longer for articles with authors from North America and Europe than from other continents, although the difference was not significant. Finally, articles of authors from the African continent had the smallest representation in journals from Q1-Q3 and articles from Oceania were underrepresented in group Q4. The study provides a global analysis of the total time required for submission, acceptance and publication in journals in the field of genetics and heredity. Our results may contribute in the development of strategies to expedite the process of scientific publishing in the field, and to promote equity in knowledge production and dissemination for researchers from all continents.

Sales of "COVID kit" drugs and adverse drug reactions reported by the Brazilian Health Regulatory Agency.

Off-label use of azithromycin, hydroxychloroquine, and ivermectin (the "COVID kit") has been suggested for COVID-19 treatment in Brazil without clinical or scientific evidence of efficacy. These drugs have known adverse drug reactions (ADR). This study aimed to analyze if the sales of drugs in the "COVID kit" are correlated to the reported number of ADR after the COVID-19 pandemic began. Data was obtained from the Brazilian Health Regulatory Agency (Anvisa) website on reported sales and ADRs for azithromycin, hydroxychloroquine, and ivermectin for all Brazilian states. The period from March 2019 to February 2020 (before the pandemic) was compared to that from March 2020 to February 2021 (during the pandemic). Trend adjustment was performed for time series data and cross-correlation analysis to investigate correlation between sales and ADR within the same month (lag 0) and in the following months (lag 1 and lag 2). Spearman's correlation coefficient was used to assess the magnitude of the correlations. After the pandemic onset, sales of all investigated drugs increased significantly (69.75% for azithromycin, 10,856,481.39% for hydroxychloroquine, and 12,291,129.32% for ivermectin). ADR levels of all medications but azithromycin were zero before the pandemic, but increased after its onset. Cross-correlation analysis was significant in lag 1 for all drugs nationwide. Spearman's correlation was moderate for azithromycin and hydroxychloroquine but absent for ivermectin. Data must be interpreted cautiously since no active search for ADR was performed. Our results show that the increased and indiscriminate use of "COVID kit" during the pandemic correlates to an increased occurrence of ADRs.

PSS Health: como calcular tamanho de amostra para testar relações de variáveis com um desfecho binário / PSS Health: how to calculate the sample size to test variables relationships with a binary outcome

Dando continuidade à série de artigos que pretendem orientar o usuário na utilização da ferramenta PSS Health para o planejamento de uma pesquisa, esta edição apresenta um passo a passo de como realizar o cálculo para tamanho de amostra e de quais informações são necessárias para testar relações estatísticas entre variáveis e um desfecho binário: comparação de proporções entre grupos independentes (dois ou mais), comparação de duas proporções dependentes e regressão logística. Todos os exemplos também são ilustrados e disponibilizados em vídeos no canal da Unidade de Bioestatística.

Following the series of articles that aim to guide the user in using the PSS Health tool for planning research, this issue presents a step-by-step guide on how to perform the sample size calculation and what information is needed to test statistical relationships between variables and a binary outcome: comparison of proportions between independent groups (two or more), comparison of two dependent proportions, and logistic regression. All examples are also illustrated and available in videos on the Biostatistics Unit's channel.

Sales of "COVID kit" drugs and adverse drug reactions reported by the Brazilian Health Regulatory Agency / Vendas de "kit-COVID" e reações adversas a esses medicamentos relatadas pela Agência Nacional de Vigilância Sanitária / Ventas de medicamentos del "kit-COVID" y reacciones adversas a los medicamentos notificadas por la Agencia Nacional de Vigilancia Sanitaria

Off-label use of azithromycin, hydroxychloroquine, and ivermectin (the "COVID kit") has been suggested for COVID-19 treatment in Brazil without clinical or scientific evidence of efficacy. These drugs have known adverse drug reactions (ADR). This study aimed to analyze if the sales of drugs in the "COVID kit" are correlated to the reported number of ADR after the COVID-19 pandemic began. Data was obtained from the Brazilian Health Regulatory Agency (Anvisa) website on reported sales and ADRs for azithromycin, hydroxychloroquine, and ivermectin for all Brazilian states. The period from March 2019 to February 2020 (before the pandemic) was compared to that from March 2020 to February 2021 (during the pandemic). Trend adjustment was performed for time series data and cross-correlation analysis to investigate correlation between sales and ADR within the same month (lag 0) and in the following months (lag 1 and lag 2). Spearman's correlation coefficient was used to assess the magnitude of the correlations. After the pandemic onset, sales of all investigated drugs increased significantly (69.75% for azithromycin, 10,856,481.39% for hydroxychloroquine, and 12,291,129.32% for ivermectin). ADR levels of all medications but azithromycin were zero before the pandemic, but increased after its onset. Cross-correlation analysis was significant in lag 1 for all drugs nationwide. Spearman's correlation was moderate for azithromycin and hydroxychloroquine but absent for ivermectin. Data must be interpreted cautiously since no active search for ADR was performed. Our results show that the increased and indiscriminate use of "COVID kit" during the pandemic correlates to an increased occurrence of ADRs.

No Brasil, o uso off label de azitromicina, hidroxicloroquina e ivermectina (o "kit-COVID") foi sugerido para tratar COVID-19 sem que tivéssemos evidências clínicas ou científicas de sua eficácia. Estas drogas têm causado reações adversas (RA) em quem as tomam. Este estudo almejou analisar se a venda dos medicamentos que compõem o "kit-COVID" correlaciona-se com o número relatado de RAs após o início da pandemia da COVID-19. Os dados sobre vendas e RA associados a azitromicina, hidroxicloroquina e ivermectina foram obtidos no site da Agência Nacional de Vigilância Sanitária (Anvisa) para todos os estados brasileiros. Comparamos o período entre março de 2019 e fevereiro de 2020 (antes da pandemia) ao de março de 2020 a fevereiro de 2021 (durante a pandemia). Ajustamos tendências para os dados de séries temporais e as análises de correlação cruzada para investigar a correlação entre vendas e RA em um mesmo mês (lag 0) e nos seguintes (lag 1 e 2). O coeficiente de correlação de Spearman foi utilizado para avaliar a magnitude das correlações. Após o início da pandemia, as vendas de todos os medicamentos investigados aumentaram significativamente (69,75% para azitromicina, 10.856.481,39% para hidroxicloroquina e 12.291.129,32% para ivermectina). Os níveis de RAs de todos os medicamentos (com exceção de azitromicina) eram zero antes da pandemia mas aumentaram após seu início. A análise de correlação cruzada foi significativa no lag 1 para todas as drogas em todo o país. A correlação de Spearman foi moderada para azitromicina e hidroxicloroquina, mas ausente para ivermectina. Os dados devem ser interpretados com cautela, uma vez que não realizamos uma busca ativa por RA. Nossos resultados mostram que o uso aumentado e indiscriminado do "kit-COVID" durante a pandemia se correlaciona com uma ocorrência aumentada de RAs.

Se ha sugerido el uso fuera de lo establecido de azitromicina, hidroxicloroquina e ivermectina (el "kit-COVID") para el tratamiento de la COVID-19 en Brasil sin evidencia clínica o científica de su eficacia. Estos medicamentos tienen reacciones adversas (RAM) conocidas. Este estudio pretendía analizar si las ventas de medicamentos del "kit-COVID" están correlacionadas con el número de reacciones adversas notificadas tras el inicio de la pandemia de COVID-19. Los datos se obtuvieron del sitio web de la Agencia Nacional de Vigilancia Sanitaria (Anvisa) sobre las ventas y las RAM notificadas para la azitromicina, la hidroxicloroquina y la ivermectina para todos los estados brasileños. Se comparó el periodo de marzo de 2019 a febrero de 2020 (antes de la pandemia) con el de marzo de 2020 a febrero de 2021 (durante la pandemia). Se realizó un ajuste de tendencia para los datos de las series de tiempo y un análisis de correlación cruzada para investigar la correlación entre las ventas y la RAM dentro del mismo mes (lag 0) y en los meses siguientes (lag 1 y lag 2). Se utilizó el coeficiente de correlación de Spearman para evaluar la magnitud de las correlaciones. Tras el inicio de la pandemia, las ventas de todos los medicamentos investigados aumentaron significativamente (69,75% para la azitromicina, 10.856.481,39% para la hidroxicloroquina y 12.291.129,32% para la ivermectina). Los niveles de RAM de todos los medicamentos, excepto la azitromicina, eran nulos antes de la pandemia, pero aumentaron tras su inicio. El análisis de correlación cruzada fue significativo en el lag 1 para todos los medicamentos a nivel nacional. La correlación de Spearman fue moderada para la azitromicina y la hidroxicloroquina, pero no para la ivermectina. Los datos deben interpretarse con cautela, ya que no se realizó una búsqueda activa de RAM. Nuestros resultados muestran que el uso creciente e indiscriminado del "kit-COVID" durante la pandemia se correlaciona con una mayor aparición de las RAM.

PSS Health: como calcular tamanho de amostra para testes de comparação de médias de dois grupos / PSS Health: how to calculate sample sizes for mean comparison tests between two groups

Dando continuidade à série de artigos que pretendem orientar o usuário na utilização da ferramenta PSS Health para o planejamento de uma pesquisa, esta edição apresenta um passo a passo de como realizar o cálculo e de quais informações são necessárias para comparar médias: de dois grupos dependentes ou independentes, de dois grupos independentes com duas medidas repetidas (deltas), e com duas ou mais medidas repetidas. Todos os exemplos também são ilustrados e disponibilizados em vídeos no canal da Unidade de Bioestatística.

Following the series of articles aiming to guide users in using the PSS Health tool for research planning, this issue presents a step-by-step guide on how to calculate and what information is needed to compare means between 2 dependent or independent groups, 2 independent groups with 2 repeated measures (deltas), and 2 independent groups with 2 or more repeated measures. All examples are accompanied by figures and available in video on the Biostatistics Unit's channel.

The impact of a bundle to prevent hospital-acquired pneumonia in a cohort of nonventilated patients on enteral nutrition.

We conducted a quasi-experimental study to evaluate a bundle to prevent nonventilator hospital-acquired pneumonia (NV-HAP) in patients on enteral tube feeding. After the intervention, there was an increase in bundle compliance from 55.9% to 70.5% (P < .01) and a significant decrease (34%) in overall NV-HAP rates from 5.71 to 3.77 of 1,000 admissions.

PSS Health: como calcular tamanho de amostra para estimar média, proporção e correlação / PSS Health: how to calculate a sample size to estimate means, proportions, and correlations

A ferramenta PSS Health (Power and Sample Size for Health Researchers) foi desenvolvida com o propósito de facilitar o cálculo do tamanho amostral e do poder de testes de hipóteses para diferentes objetivos de estudo, usando interface amigável e terminologia comum à área da saúde. Este é o primeiro de uma série de artigos que pretendem orientar o usuário na utilização da ferramenta PSS Health para o planejamento de uma pesquisa. Neste artigo, se ensina como utilizar o PSS Health quando o objetivo principal do estudo é estimar uma média, estimar uma proporção (prevalência ou incidência) ou estimar uma correlação. São disponibilizados vídeos demonstrando o uso da ferramenta em cada um dos contextos citados. (AU)

The PSS Health (Power and Sample Size for Health Researchers) tool was developed with the purpose of facilitating the calculation of sample size and power of hypothesis tests for different study objectives, based on a user-friendly interface and common health care terminology. This is the first in a series of articles intending to guide the user in how to use the PSS Health tool for planning a research project. This article teaches how to use PSS Health when the main objective of the study is to estimate means, proportions (prevalence or incidence), or correlations. Videos showing how to use the tool in each of the mentioned contexts are available. (AU)

Equívocos estatísticos: perguntas que você sempre quis fazer, mas nunca teve coragem / Statistical misconceptions: questions you've always wanted to ask, but never dared

Este artigo visa elucidar algumas dúvidas enfrentadas ou equívocos estatísticos cometidos por pesquisadores de diversas áreas. São explanados os temas: "tradução não é validação", "análise fatorial exploratória ou confirmatória", "nem todo estudo com dois grupos tem delineamento caso-controle", "teste ou ajuste de Bonferroni", "tamanho de amostra para teste de hipóteses e/ou para intervalo de confiança", e "testes ou dados paramétricos". A abordagem é realizada em uma linguagem acessível ao público leigo, utilizando exemplos e sugerindo referências para aprofundar o conhecimento.(AU)

This article aims to answer some questions and elucidate statistical misconceptions of researchers from different fields. The following topics are addressed: "translation is not validation", "exploratory or confirmatory factor analysis", "not every study with two groups is a case-control study", "Bonferroni test or adjustment", "sample size for testing hypotheses and/or for confidence intervals", and "parametric data or tests". The topics are explained in lay terms, using examples and suggesting references to advance knowledge.(AU)

Power and sample size for health researchers: uma ferramenta para cálculo de tamanho amostral e poder do teste voltado a pesquisadores da área da saúde / Power and sample size for health researchers: a tool for calculating sample size and statistical power designed for health researchers

Nas próximas edições da seção de Bioestatística da revistaClinical & Biomedical Researchuma nova série de artigos será publicada abordando um assunto de grande importância ao planejar uma pesquisa: o tamanho de amostra mínimo necessário para atingir os objetivos do estudo. Nessa série será apresentado como calcular o tamanho de uma amostra usando a ferramenta PSSHealth(Power and Sample Size for Health Researchers), construído em linguagem R por meio do pacote Shiny, para diferentes tipos e objetivos de estudo, direcionado à pesquisadores da área da saúde, utilizando termos e conceitos comumente utilizados nesta área. Além disso, o pacote fornece uma sugestão de texto com as informações consideradas no cálculo, e como devem ser descritas, com a finalidade de minimizar problemas de interpretação por parte dos pesquisadores. Neste primeiro artigo será apresentada essa ferramenta desenvolvida pela Unidade de Bioestatística do Grupo de Pesquisa e Pós-Graduação do Hospital de Clínicas de Porto Alegre, que permite calcular não apenas o tamanho de amostra, mas também o poder de um teste de hipóteses. (AU)

In the next issues ofClinical and Biomedical Research, the Biostatistics section will introduce a new series of articles addressing a very important subject for research planning: the minimum sample size to achieve the aim of a study. This series will show how to calculate sample size using PSS Health (Power and Sample Size for Health Researchers). This tool was built using R language through the Shiny package. It can be used for different types of study and is designed for health researchers by using terms and concepts commonly used in this area. PSS Health also suggests a text with information considered in the calculation to minimize problems of interpretation by the researchers. In this first article, a general overview of PSS Health will be presented. This tool, which was developed by the Research and Graduate Group Biostatistics Unit of the Hospital de Clínicas de Porto Alegre, is useful not only to calculate sample size but also to determine power of a hypothesis test. (AU)

Incidence of tuberculosis infection in spondyloarthritis patients treated with biological and conventional disease-modifying anti-rheumatic drugs in an endemic area

Introduction: Registries of spondyloarthritis (SpA) patients' follow-up provided evidence that tumor necrosis factor inhibitors (TNFi) increase the incidence of active tuberculosis infection (TB). However, most of these registries are from low burden TB areas. Few studies evaluated the safety of biologic agents in TB endemic areas. This study compares the TB incidence rate (TB IR) in anti-TNF-naïve and anti-TNF-experienced subjects with SpA in a high TB incidence setting.Methods: In this retrospective cohort study, medical records from patients attending a SpA clinic during 13 years (2004 to 2016) in a university hospital were reviewed. The TB IR was calculated and expressed as number of events per 105 patients/year; the incidence rate ratio (IRR) associated with the use of TNFi was calculated.Results: A total of 277 patients, 173 anti-TNF-naïve and 104 anti-TNF-experienced subjects, were evaluated; 35.7% (N = 35) of patients who were prescribed an anti-TNF drug were diagnosed with latent tuberculosis infection (LTBI). Total follow-up time (person-years) was 1667.8 for anti-TNF-naïve and 394.9 for anti-TNF-experienced patients. TB IR (95% CI) was 299.8 (37.4-562.2) for anti-TNF naïve and 1012.9 (25.3-2000.5) for anti-TNF experienced subjects. The IRR associated with the use of TNFi was 10.4 (2.3- 47.9).Conclusions: In this high TB incidence setting, SpA patients exposed to anti-TNF therapy had a higher incidence of TB compared to anti-TNF-naïve subjects, although the TB incidence in the control group was significant.(AU)

Determining the pathogenicity of CFTR missense variants: Multiple comparisons of in silico predictors and variant annotation databases.

Pathogenic variants in the Cystic Fibrosis Transmembrane Conductance Regulator gene (CFTR) are responsible for cystic fibrosis (CF), the commonest monogenic autosomal recessive disease, and CFTR-related disorders in infants and youth. Diagnosis of such diseases relies on clinical, functional, and molecular studies. To date, over 2,000 variants have been described on CFTR (~40% missense). Since few of them have confirmed pathogenicity, in silico analysis could help molecular diagnosis and genetic counseling. Here, the pathogenicity of 779 CFTR missense variants was predicted by consensus predictor PredictSNP and compared to annotations on CFTR2 and ClinVar. Sensitivity and specificity analysis was divided into modeling and validation phases using just variants annotated on CFTR2 and/or ClinVar that were not in the validation datasets of the analyzed predictors. After validation phase, MAPP and PhDSNP achieved maximum specificity but low sensitivity. Otherwise, SNAP had maximum sensitivity but null specificity. PredictSNP, PolyPhen-1, PolyPhen-2, SIFT, nsSNPAnalyzer had either low sensitivity or specificity, or both. Results showed that most predictors were not reliable when analyzing CFTR missense variants, ratifying the importance of clinical information when asserting the pathogenicity of CFTR missense variants. Our results should contribute to clarify decision making when classifying the pathogenicity of CFTR missense variants.

Correlation of enthesitis indices with disease activity and function in axial and peripheral spondyloarthritis: a cross-sectional study comparing MASES, SPARCC and LEI.

BACKGROUND: The presence of enthesitis is associated with higher disease activity, more disability and incapacity to work and a poorer quality of life in spondyloarthritis (SpA). There is currently no consensus on which clinical score should be used to assess enthesitis in SpA. The objective of the present work was to compare the correlation of three enthesitis indices (MASES, SPARCC and LEI) with measures of disease activity and function in a heterogeneous population of patients with axial and peripheral SpA. METHODS: A cross-sectional study was conducted in three Brazilian public university hospitals; patients fulfilling ASAS classification criteria for peripheral or axial SpA were recruited and measures of disease activity and function were collected and correlated to three enthesitis indices: MASES, SPARCC and LEI using Spearman's Correlation index. ROC curves were used to determine if the the enthesitis indices were useful to discriminate patients with active disease from those with inactive disease. RESULTS: Two hundred four patients were included, 71.1% (N = 145) fulfilled ASAS criteria for axial SpA and 28.9% (N = 59) for peripheral SpA. In axial SpA, MASES performed better than LEI (p = 0.018) and equal to SPARCC (p = 0.212) regarding correlation with disease activity (BASDAI) and function (BASFI). In peripheral SpA, only MASES had a weak but statistical significant correlation with DAS28-ESR (rs 0.310 p = 0.05) and MASES had better correlation with functional measures (HAQ) than SPARCC (p = 0.034). CONCLUSION: In this sample composed of SpA patients with high coexistence of axial and peripheral features, MASES showed statistical significant correlation with measures of disease activity and function in both axial and peripheral SpA.

Teste de hipóteses: perguntas que você sempre quis fazer, mas nunca teve coragem / Hypothesis testing: questions you have always wanted to ask, but never had the courage to

Dando continuidade aos artigos da série "Perguntas que você sempre quis fazer, mas nunca teve coragem", que tem como objetivo responder e sugerir referências para o melhor entendimento das principais dúvidas dos pesquisadores do Hospital de Clínicas de Porto Alegre sobre estatística, este segundo artigo se propõe a responder às principais dúvidas levantadas sobre Teste de Hipóteses. São discutidas questões referentes à metodologia de um teste de hipóteses na concepção clássica de Inferência Estatística, bem como tamanho de efeito, tipos de erros, valor de p e poder. Os conceitos são abordados numa linguagem acessível ao público leigo e diversas referências são sugeridas para os curiosos em relação ao tema. (AU)

Continuing the series of articles "Questions you have always wanted to ask, but never had the courage to", which aims to answer the most common questions of researchers at Hospital de Clínicas de Porto Alegre regarding statistics and to suggest references for a better understanding, this second article addresses the topic of hypothesis testing. The hypothesis testing method is discussed from a classical conception of statistical inference, including effect size, type of errors, p-value and power. The concepts are explained in plain language for lay readers and several references are suggested for those curious about the topic. (AU)

Bioestatística e epidemiologia: perguntas que você sempre quis fazer, mas nunca teve coragem / Biostatistics and epidemiology: questions you always wanted to ask but never had the courage to

Dando continuidade aos artigos da série "Perguntas que você sempre quis fazer, mas nunca teve coragem", que tem como objetivo responder e sugerir referências para o melhor entendimento das principais dúvidas estatísticas levantadas por pesquisadores da área da saúde, este terceiro artigo aborda o contexto epidemiológico. Neste contexto, foram diferenciadas as principais medidas como prevalência, incidência, Odds Ratio (OR), Risco Relativo (RR), Razão de Prevalência (RP) e Hazard Ratio (HR), foi esclarecido o uso de análises por intenção de tratar e análise por protocolo, e também discutidos alguns dos termos comumente utilizados e pouco compreendidos como tipo de amostra, nível de evidência, relevância clínica e estatística, entre outros. (AU)

Continuing the series of articles "Questions you always wanted to ask but never had the courage to," which aims to answer key statistical questions raised by health researchers and suggest references for a better understanding, this third article addresses the epidemiological context. In this context, important measures such as prevalence, incidence, odds ratio (OR), relative risk (RR), prevalence ratio (PR) and hazard ratio (HR) were differentiated; the use of intention-to-treat analysis and per-protocol analysis was clarified; and some terms commonly used and poorly understood were discussed, such as type of sample, level of evidence, clinical and statistical relevance, among others. (AU)

Modelagem estatística: perguntas que você sempre quis fazer, mas nunca teve coragem / Statistical modeling: questions you have always wanted to ask but never had the courage to

Dando continuidade aos artigos da série "Perguntas que você sempre quis fazer, mas nunca teve coragem", que tem como objetivo responder e sugerir referências para o melhor entendimento das principais dúvidas dos pesquisadores do Hospital de Clínicas de Porto Alegre sobre estatística, este quarto artigo se propõe a responder às principais dúvidas levantadas sobre modelagem estatística. São discutidas questões referentes à classificação de variáveis em independentes e dependentes, diferenças entre correlação, associação e regressão, os principais tipos de regressão e quais etapas são necessárias na construção de modelos. Os conceitos são abordados numa linguagem acessível ao público leigo e diversas referências são sugeridas para os curiosos em relação ao tema. (AU)

Continuing the series of articles "Questions you have always wanted to ask but never had the courage to," which aims to answer the most common questions of researchers at Hospital de Clínicas de Porto Alegre regarding statistics and to suggest references for a better understanding, this forth article addresses the topic of statistical modeling. Questions about classification of variables as dependent or independent, differences between correlation, association and regression, types of regression and steps for statistical modeling are discussed. The concepts are explained in plain language for lay readers and several references are suggested for those curious about the topic. (AU)

Correlation of enthesitis indices with disease activity and function in axial and peripheral spondyloarthritis: a crosssectional study comparing MASES, SPARCC and LEI

Abstract Background: The presence of enthesitis is associated with higher disease activity, more disability and incapacity to work and a poorer quality of life in spondyloarthritis (SpA). There is currently no consensus on which clinical score should be used to assess enthesitis in SpA. The objective of the present work was to compare the correlation of three enthesitis indices (MASES, SPARCC and LEI) with measures of disease activity and function in a heterogeneous population of patients with axial and peripheral SpA. Methods: A cross-sectional study was conducted in three Brazilian public university hospitals; patients fulfilling ASAS classification criteria for peripheral or axial SpA were recruited and measures of disease activity and function were collected and correlated to three enthesitis indices: MASES, SPARCC and LEI using Spearman's Correlation index. ROC curves were used to determine if the the enthesitis indices were useful to discriminate patients with active disease from those with inactive disease. Results: Two hundred four patients were included, 71.1% (N = 145) fulfilled ASAS criteria for axial SpA and 28.9% (N = 59) for peripheral SpA. In axial SpA, MASES performed better than LEI (p = 0.018) and equal to SPARCC (p = 0.212) regarding correlation with disease activity (BASDAI) and function (BASFI). In peripheral SpA, only MASES had a weak but statistical significant correlation with DAS28-ESR (rs 0.310 p = 0.05) and MASES had better correlation with functional measures (HAQ) than SPARCC (p = 0.034). Conclusion: In this sample composed of SpA patients with high coexistence of axial and peripheral features, MASES showed statistical significant correlation with measures of disease activity and function in both axial and peripheral SpA.(AU)

Estatística descritiva: perguntas que você sempre quis fazer, mas nunca teve coragem / Descriptive statistics: questions you have always wanted to ask, but never had the courage to

A revista do HCPA (Clinical & Biomedical Research) está reabrindo a seção de Bioestatística com o intuito de apresentar artigos explicativos, conceituais ou tutoriais, de modo a elucidar os leitores sobre os mais diversos temas estatísticos. Neste contexto, este artigo será o primeiro de uma série que tem como objetivo responder algumas das questões mais levantadas por pesquisadores da área da saúde. Começando pela Estatística Descritiva, alguns conceitos são esclarecidos e diversas referências são indicadas para o estudo do tema e para análises em SPSS ou R-project. (AU)

The HCPA journal (Clinical & Biomedical Research) is reopening its Biostatistics section with the aim of presenting readers with explanatory, conceptual or tutorial articles on a wide range of statistical topics. In this context, this is the first in a series of articles seeking to answer some of the questions raised by health researchers. Starting with descriptive statistics, some concepts are introduced and several references are indicated for those interested in studying the topic and performing analyses in SPSS or R-project. (AU)

Os principais delineamentos na Epidemiologia: ensaios clínicos (parte II) / The major designs in Epidemiology: clinical trial (part II)

O tema "estudos experimentais" é um conteúdo amplo, de difícil síntese. Com o objetivo de sintetizar as principais informações referentes a um estudo experimental, este trabalho visa dar continuidade ao estudo do tema iniciado em Mancuso et al. (2013). Além do contexto teórico abordado até então, a metodologia de desenvolvimento também é de fundamental importância. Os resultados podem sofrer interferências graves e os objetivos não alcançados, se a metodologia aplicada não for adequada. Além destes, as análises estatísticas e o número de sujeitos são fundamentais para a validade dos resultados. Na primeira parte, foram apresentadas as principais informações para iniciar um ensaio clínico. Nesta segunda parte serão abordados tópicos metodológicos como tipos, fases e delineamentos de um ensaio e tópicos estatísticos como análises e tamanho amostral (AU)

The theme "experimental studies" is a broad content, difficult synthesis. With the aim to synthesize key information related to an experimental study, this paper aims to continue the study of the topic began in Mancuso et al.(2013). Besides the theoretical context discussed so far, the development methodology is also of fundamental importance. The results may suffer severe interference and goals not achieved, the methodology is not adequate. In addition, statistical analyzes and number of subjects are fundamental to the validity of the results. In the first part, the main information to start a clinical trial were presented. In this second part will be addressed methodological topics as types, phases and outlines a testing and statistical topics such as analysis and sample size (AU)

Os principais delineamentos na Epidemiologia: ensaios clínicos (parte I) / The major designs in Epidemiology: clinical trial (part I)

Um estudo experimental tem como objetivo principal conduzir um ou mais tratamentos ou intervenções de modo a modificar, de alguma forma, um processo de doença. Para as comparações, pelo menos dois grupos devem ser formados, diferenciando-se pelos tratamentos. Geralmente um grupo intervenção e outro controle. Além disso, os sujeitos devem ser alocados de forma aleatória aos grupos, de preferencia adotando-se o "cegamento", pois previne certos vieses. Sob todas as circunstâncias, a ética na pesquisa deve prevalecer. Contudo, estes são apenas tópicos de um assunto muito amplo. Para contemplar os principais assuntos do tema, dois artigos foram estruturados, buscando-se sintetizar as principais informações sem comprometer o rigor científico. Neste primeiro artigo serão apresentadas as principais informações para iniciar um ensaio clínico (AU)

A clinical trial study aims to conduct one or more treatments or interventions in order to change, somehow, a disease process. For comparisons, at least two groups should be formed, differing by treatments. Usually an intervention group and a control group. In addition, the subject must be allocated randomly to groups, preferably adopting the "blinding" because it prevents certain biases. Under all circumstances, the research ethics should prevail. However, these topics are just a very a broad topic. To address the main issues of the topic, two articles were structured, trying to summarize the principal information without compromising the scientific rigor. In this first article the main information to start a clinical trial will be presented (AU)

Os principais delineamentos na epidemiologia / Primary study designs in epidemiology

O presente artigo se propõe a descrever brevemente delineamentos epidemiológicos que são largamente utilizados na pesquisa da área da saúde. Os tipos de estudo abordados nesse artigo são a coorte, o caso controle, os estudos de prevalência, os estudos de teste diagnóstico, os estudos ecológicos, os ensaios clínicos, os estudos de validade, fidedignidade e concordância e os estudos-piloto. Para cada um dos delineamentos são indicadas referências bibliográficas para os leitores poderem obter maior detalhamento dos delineamentos descritos.

This article aims to briefly describe the primary study designs used in epidemiologic research. We discuss the following types of study designs: cohort, case-control, prevalence studies, diagnostic test studies, ecologic studies, clinical trials, pilot studies, and validity, reliability and agreement tests. This article ends with a number of bibliographic references on each type of study so that readers can seek further information.