Lectures additionnelles

Vous trouverez ci-dessous des lectures complémentaires à propos de l’analyse bayésienne ainsi que des exemples de son applications dans la recherche médicale. Vous pouvez à chaque fois télécharger le fichier .pdf en cliquant sur l’image 📰.

Introductions à la statistique bayésienne pour des scientifiques appliqués (biologistes ou médecins)

📰 Jorge López Puga, Martin Krzywinski, and Naomi Altman, “Bayes’ Theorem,” Nature Methods 12, no. 4 (2015): 277–278, doi:10.1038/nmeth.3335.

📰 Jorge López Puga, Martin Krzywinski, and Naomi Altman, “Bayesian Statistics,” Nature Methods 12, no. 5 (2015): 377–378, doi:10.1038/nmeth.3368.

📰 Anna E. McGlothlin and Kert Viele, “Bayesian Hierarchical Models,” JAMA 320, no. 22 (2018): 2365, doi:10.1001/jama.2018.17977.

📰 Jasleen K. Grewal, Martin Krzywinski, and Naomi Altman, “Markov Models – Markov Chains,” Nature Methods 16, no. 8 (2019): 663–664, doi:10.1038/s41592-019-0476-x.

📰 Sean R Eddy, “What Is Bayesian Statistics?” Nature Biotechnology 22, no. 9 (2004): 1177–1178, doi:10.1038/nbt0904-1177.

L’approche bayésienne dans la littérature médicale — quelques exemples

Ré-analyse bayésienne d’un essai clinique

Étude originale

📰 Alain Combes et al., “Extracorporeal Membrane Oxygenation for Severe Acute Respiratory Distress Syndrome,” New England Journal of Medicine 378, no. 21 (2018): 1965–1975, doi:10.1056/NEJMoa1800385.

Ré-analyse bayésienne

📰 Ewan C. Goligher et al., “Extracorporeal Membrane Oxygenation for Severe Acute Respiratory Distress Syndrome and Posterior Probability of Mortality Benefit in a Post Hoc Bayesian Analysis of a Randomized Clinical Trial,” JAMA 320, no. 21 (2018): 2251, doi:10.1001/jama.2018.14276.

Commentaires & réponse

📰 Roger J. Lewis and Derek C. Angus, “Time for Clinicians to Embrace Their Inner Bayesian?: Reanalysis of Results of a Clinical Trial of Extracorporeal Membrane Oxygenation,” JAMA 320, no. 21 (2018): 2208–2210, doi:10.1001/jama.2018.16916.

📰 Scott K. Aberegg, “Post Hoc Bayesian Analyses,” JAMA 321, no. 16 (2019): 1631–1632, doi:10.1001/jama.2019.1198. David Ferreira and Nicolas Meyer, “Post Hoc Bayesian Analyses,” JAMA 321, no. 16 (2019): 1632–1632, doi:10.1001/jama.2019.1194. Ewan C. Goligher, George Tomlinson, and Arthur S. Slutsky, “Post Hoc Bayesian Analyses—Reply,” JAMA 321, no. 16 (2019): 1632–1633, doi:10.1001/jama.2019.1202.

Méta-analyse bayésienne

📰 Christian Röver, “Bayesian Random-Effects Meta-Analysis Using the Bayesmeta R Package,” arXiv Preprint 1711.08683 (2017), http://www.arxiv.org/abs/1711.08683.

📰 Nicola D Crins et al., “Interleukin-2 Receptor Antagonists for Pediatric Liver Transplant Recipients: A Systematic Review and Meta-Analysis of Controlled Studies,” Pediatric Transplantation 18, no. 8 (2014): 839–850, doi:10.1111/petr.12362.

📰 Shipra Arya, Todd A. Schwartz, and Amir A. Ghaferi, “Practical Guide to Meta-Analysis,” JAMA Surgery 155, no. 5 (2020): 430, doi:10.1001/jamasurg.2019.4523.

📰 Stylianos Serghiou and Steven N. Goodman, “Random-Effects Meta-Analysis: Summarizing Evidence with Caveats,” JAMA 321, no. 3 (2019): 301–302, doi:10.1001/jama.2018.19684.

Continuous Reassessment Methods (CRM) pour la recherche de dose

📰 Florentia Kaguelidou et al., “Dose-Finding Study of Omeprazole on Gastric pH in Neonates with Gastro-Esophageal Acid Reflux Using a Bayesian Sequential Approach,” ed. Imti Choonara, PLOS ONE 11, no. 12 (2016): e0166207, doi:10.1371/journal.pone.0166207.