[How many subjects do I need to power my study?]. / ¿Cuántos sujetos necesito para mi estudio?

The article presents a tool that helps answer the question “How many subjects do I need to power my study? We show how to determine sample size in observational epidemiological studies and provide examples of application using the statistical package Epidat, which is a shareware program developed under the auspices of the Pan American Health Organization, the Galician Board of Health and the University CES of Colombia. Examples of calculation of sample size for prevalence studies (cross-sectional), case-control studies and cohort studies are given.

El artículo presenta una herramienta metodológica que ayuda a responder la pregunta ¿Cuántos sujetos necesito para mi estudio? Se presenta cómo determinar tamaño de muestra en estudios epidemiológicos observacionales dando ejemplos de aplicación usando el paquete estadístico Epidat de distribución libre elaborado bajo el auspicio de la Organización Panamericana de la Salud, la Junta de Salud de Galicia y la Universidad CES de Colombia. Se dan ejemplos de cálculo de tamaño de muestra para estudios de prevalencia (corte transversal), para estudios de casos y controles y para estudios de cohortes.

El uso de metodología estadística actualizada en la investigación biomédica: el ejemplo de metodología para análisis interino en ensayos clínicos / The use of state of the art statistical methodology in biomedical research: the example of methodology for interim analyses in clinical trials

Background: Clinical research stresses the need for evidence as a basis for setting research agendas. The extent to which current clinical research involves recent advances in biostatistics is not well known. Aim: This manuscript focuses on the use of interim analyses accumulating data in clinical trials. Material and Methods: A PubMed search was conducted for the period 1990-2000. Keywords used included interim analysis, alpha-spending function, and early termination, after subsetting to randomised controlled trials (RCT) that were multicenter since these particular studies are more likely to have external monitoring boards conducting interim analyses. Studies were grouped by clinical discipline and also by journals of high or low impact index. Results: Thirteen thousand two hundred eighty two articles with both RCT and multicenter were found. Of these, the interim analysis keyword yielded 879 articles, of which only 163 (19 percent) studies reported their methodology. The percentages varied by clinical discipline and by journal type. A 25 percent random sample of the articles were further reviewed to investigate the appropriateness of the interim analysis methods used. Discussion: Recent articles in the medical literature attempt to make the interim analysis methods more accessible to clinicians. However, further training of statisticians involved in clinical trials is needed as well