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      Explicación del tamaño muestral empleado: una exigencia irracional de las revistas biomédicas Translated title: Explanation of samples sizes in current biomedical journals: an irrational requirement

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          Abstract

          Objetivos: Discutir conceptualmente la pertinencia de las demandas prevalecientes acerca de lo que debe comunicarse sobre la determinación del tamaño de muestra en estudios publicados, y aquilatar el grado en que tales demandas son satisfechas por autores y exigidas por árbitros y editores. Métodos: Se llevó adelante una búsqueda bibliográfica con el fin de conocer y debatir críticamente los razonamientos que pudieran haberse expuesto para respaldar la norma según la cual los autores deben justificar el tamaño muestral. A continuación se valoró el cumplimiento de dicha norma en los artículos originales publicados a lo largo de 2009 en las seis revistas de más alto factor de impacto en el campo de la salud. Resultados: Las razones esgrimidas para respaldar la exigencia de explicar el tamaño muestral empleado resultan escasas y endebles, a la vez que hay no pocas razones para no suscribirlas. Se constató que dicha pauta es mayoritariamente ignorada en la literatura actual de mayor impacto. En el 56% (intervalo de confianza del 95% [IC95%]: 52-59) de los artículos no se fundamenta el tamaño empleado y sólo el 27% (IC95%: 23-30) cumple con todas las exigencias de las guías a las que se adhieren las propias revistas estudiadas. Conclusiones: El estudio permite concluir que no hay argumentos convincentes para exigir que en un artículo publicado se explique cómo se llegó a cierto tamaño muestral. Tal exigencia carece de utilidad y no promueve, sino que más bien menoscaba, la transparencia del reporte de las investigaciones.

          Translated abstract

          Objectives: To discuss the theoretical relevance of current requirements for explanations of the sample sizes employed in published studies, and to assess the extent to which these requirements are currently met by authors and demanded by referees and editors. Methods: A literature review was conducted to gain insight into and critically discuss the possible rationale underlying the requirement of justifying sample sizes. A descriptive bibliometric study was then carried out based on the original studies published in the six journals with the highest impact factor in the field of health in 2009. Results: All the arguments used to support the requirement of an explanation of sample sizes are feeble, and there are several reasons why they should not be endorsed. These instructions are neglected in most of the studies published in the current literature with the highest impact factor. In 56% (95%CI: 52-59) of the articles, the sample size used was not substantiated, and only 27% (95%CI: 23-30) met all the requirements contained in the guidelines adhered to by the journals studied. Conclusions: Based on this study, we conclude that there are no convincing arguments justifying the requirement for an explanation of how the sample size was reached in published articles. There is no sound basis for this requirement, which not only does not promote the transparency of research reports but rather contributes to undermining it.

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          The quality of reports of randomised trials in 2000 and 2006: comparative study of articles indexed in PubMed

          Objectives To examine the reporting characteristics and methodological details of randomised trials indexed in PubMed in 2000 and 2006 and assess whether the quality of reporting has improved after publication of the Consolidated Standards of Reporting Trials (CONSORT) Statement in 2001. Design Comparison of two cross sectional investigations. Study sample All primary reports of randomised trials indexed in PubMed in December 2000 (n=519) and December 2006 (n=616), including parallel group, crossover, cluster, factorial, and split body study designs. Main outcome measures The proportion of general and methodological items reported, stratified by year and study design. Risk ratios with 95% confidence intervals were calculated to represent changes in reporting between 2000 and 2006. Results The majority of trials were two arm (379/519 (73%) in 2000 v 468/616 (76%) in 2006) parallel group studies (383/519 (74%) v 477/616 (78%)) published in specialty journals (482/519 (93%) v 555/616 (90%)). In both 2000 and 2006, a median of 80 participants were recruited per trial for parallel group trials. The proportion of articles that reported drug trials decreased between 2000 and 2006 (from 393/519 (76%) to 356/616 (58%)), whereas the proportion of surgery trials increased (51/519 (10%) v 128/616 (21%)). There was an increase between 2000 and 2006 in the proportion of trial reports that included details of the primary outcome (risk ratio (RR) 1.18, 95% CI 1.04 to 1.33), sample size calculation (RR 1.66, 95% CI 1.40 to 1.95), and the methods of random sequence generation (RR 1.62, 95% CI 1.32 to 1.97) and allocation concealment (RR 1.40, 95% CI 1.11 to 1.76). There was no difference in the proportion of trials that provided specific details on who was blinded (RR 0.91, 95% CI 0.75 to 1.10). Conclusions Reporting of several important aspects of trial methods improved between 2000 and 2006; however, the quality of reporting remains well below an acceptable level. Without complete and transparent reporting of how a trial was designed and conducted, it is difficult for readers to assess its conduct and validity.
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            The use of predicted confidence intervals when planning experiments and the misuse of power when interpreting results.

            Although there is a growing understanding of the importance of statistical power considerations when designing studies and of the value of confidence intervals when interpreting data, confusion exists about the reverse arrangement: the role of confidence intervals in study design and of power in interpretation. Confidence intervals should play an important role when setting sample size, and power should play no role once the data have been collected, but exactly the opposite procedure is widely practiced. In this commentary, we present the reasons why the calculation of power after a study is over is inappropriate and how confidence intervals can be used during both study design and study interpretation.
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              Design, analysis, and presentation of crossover trials

              Objective Although crossover trials enjoy wide use, standards for analysis and reporting have not been established. We reviewed methodological aspects and quality of reporting in a representative sample of published crossover trials. Methods We searched MEDLINE for December 2000 and identified all randomized crossover trials. We abstracted data independently, in duplicate, on 14 design criteria, 13 analysis criteria, and 14 criteria assessing the data presentation. Results We identified 526 randomized controlled trials, of which 116 were crossover trials. Trials were drug efficacy (48%), pharmacokinetic (28%), and nonpharmacologic (30%). The median sample size was 15 (interquartile range 8–38). Most (72%) trials used 2 treatments and had 2 periods (64%). Few trials reported allocation concealment (17%) or sequence generation (7%). Only 20% of trials reported a sample size calculation and only 31% of these considered pairing of data in the calculation. Carry-over issues were addressed in 29% of trial's methods. Most trials reported and defended a washout period (70%). Almost all trials (93%) tested for treatment effects using paired data and also presented details on by-group results (95%). Only 29% presented CIs or SE so that data could be entered into a meta-analysis. Conclusion Reports of crossover trials frequently omit important methodological issues in design, analysis, and presentation. Guidelines for the conduct and reporting of crossover trials might improve the conduct and reporting of studies using this important trial design.
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                Author and article information

                Contributors
                Role: ND
                Role: ND
                Journal
                gs
                Gaceta Sanitaria
                Gac Sanit
                Ediciones Doyma, S.L. (Barcelona, Barcelona, Spain )
                0213-9111
                February 2013
                : 27
                : 1
                : 53-57
                Affiliations
                [02] La Habana orgnameCentro Nacional de Información de Ciencias Médicas orgdiv1Vicedirección de Servicios Informativos Especiales Cuba
                [01] La Habana orgnameCentro Nacional de Información de Ciencias Médicas orgdiv1Vicedirección de Docencia e Investigación Cuba
                Article
                S0213-91112013000100009
                10.1016/j.gaceta.2012.01.017
                77c702d0-3b7b-4607-b89d-c23405defe9c

                This work is licensed under a Creative Commons Attribution-NonCommercial 3.0 International License.

                History
                : 25 January 2012
                : 08 November 2011
                Page count
                Figures: 0, Tables: 0, Equations: 0, References: 35, Pages: 5
                Product

                SciELO Spain


                Tamaño de muestra,Guía,Ensayo clínico controlado,Estadísticas,Artículo de revista,Sample size,Guidelines,Controlled clinical trial,Statistics,Journal article

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