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Vol. 74. Issue 7.
Pages 642-643 (July 2021)
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Vol. 74. Issue 7.
Pages 642-643 (July 2021)
Letter to the Editor
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The use of Bayes factor in clinical cardiology research. Response
El uso del factor Bayes en la investigación clínica de cardiología. Respuesta
Juan Manuel Monteagudo Ruiz, Jorge Solano-López, José Luis Zamorano, Ángel Sánchez-Recalde
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Corresponding author:
Servicio de Cardiología, Hospital Universitario Ramón y Cajal, Madrid, Spain
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Rev Esp Cardiol. 2021;74:641-210.1016/j.rec.2021.01.020
Cristian Antony Ramos-Vera
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To the Editor,

We greatly appreciate Cristian Antony Ramos-Vera's interest in our article; in his letter he highlights the virtues of using Bayes factor (BF) as an alternative to the traditional dichotomous interpretation of hypothesis testing, and his analysis provides more robust support for our findings.1

Frequentist statistics almost entirely dominate medical research. The average reader has interiorized the concepts of hypothesis testing, P value, and statistical significance. The limitations of frequentist statistics and the problems with their interpretation have been widely discussed2 and, in addition, repeated appeals have been made to include Bayesian statistics in biomedical research.3 While it is true that Bayesian statistics allow a more natural and intuitive interpretation, the reality is that their use is not widespread and most readers do not understand them.

Hoekstra et al.4 performed a reanalysis of 36 articles with negative results and calculated the BF. The smallest BF was 2.42 (observed data are 2.42 times more probable under the null hypothesis) and the largest, 560.9. A key point is that there was a poor correlation between the P value and the BF. A high P value may have been present in studies with little evidence in favor of the null hypothesis (low BF) or in studies with strong evidence (high BF). This allows us to assert that the BF intuitively communicates the probative strength of the hypothesis; therefore, we, like Dr Ramos-Vera, recommend that this should routinely be included in scientific articles.


No funding was received for this article.


J.M. Monteagudo conceived and wrote the article. J. Solano-López critically reviewed the manuscript. J.L. Zamorano critically reviewed the manuscript. Á. Sanchez-Recalde conceived the idea for this article and critically reviewed the manuscript. All authors have approved the final version of the manuscript.


Á. Sánchez-Recalde is associate editor of Revista Española de Cardiología; the journal's established editorial procedure was followed to ensure the impartial handling of this manuscript.

J. Solano-López, J.L. Zamorano, A. Pardo Sanz, et al.
Factores de riesgo de muerte hospitalaria en pacientes con infarto agudo de miocardio durante la pandemia de la COVID-19.
Rev Esp Cardiol., 73 (2020), pp. 985-993
J.P.A. Ioannidis.
Why most published research findings are false.
L.C. Gurrin, J.J. Kurinczuk, P.R. Burton.
Bayesian statistics in medical research: an intuitive alternative to conventional data analysis.
J Eval Clin Pract., 6 (2000), pp. 193-204
R. Hoekstra, R. Monden, D. Ravenzwaaij, van, E.J. Wagenmakers.
Bayesian reanalysis of null results reported in medicine: Strong yet variable evidence for the absence of treatment effects.
PLoS One., 13 (2018), pp. e0195474
Copyright © 2021. Sociedad Española de Cardiología
Revista Española de Cardiología (English Edition)

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