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Quantification de la valeur ajoutée d’un biomarqueur par l’indice de Net Reclassification Improvement

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Les biomarqueurs en médecine d’urgence

Part of the book series: Références en médecine d’urgence. Collection de la SFMU ((REFERMED))

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Résumé

Pour orienter sa démarche diagnostique ou thérapeutique, le clinicien doit estimer, le plus souvent de manière implicite, la probabilité du diagnostic suspecté ou le pronostic de la pathologie en cause. Des modèles de prédiction clinique ont été dérivés et validés de manière rigoureuse pour l’assister face à des situations cliniques variées rencontrées en médecine d’urgence [1–3]. Ces modèles de prédiction clinique assignent à chaque patient une probabilitéen fonction de la valeur de différents prédicteurs recueillis par l’interrogatoire, l’examen clinique ou des tests simples [4].

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Références

  1. Aujesky D, Obrosky DS, Stone RA, et al. (2005) Derivation and validation of a prognostic model for pulmonary embolism. Am J Respir Crit Care Med 172: 1041–1046

    Article  PubMed  Google Scholar 

  2. Fine MJ, Auble TE, Yealy DM, et al. (1997) A prediction rule to identify low-risk patients with community-acquired pneumonia. N Engl J Med 336: 243–250

    Article  PubMed  CAS  Google Scholar 

  3. Wells PS, Anderson DR, Bormanis J, et al. (1997) Value of assessment of pretest probability of deep-vein thrombosis in clinical management. Lancet 350: 1795–1798

    Article  PubMed  CAS  Google Scholar 

  4. Steyerberg EW (2010) Clinical prediction models. New York: Springer

    Google Scholar 

  5. Pencina MJ, D’Agostino RB, Vasan RS (2010) Statistical methods for assessment of added usefulness of new biomarkers. Clin Chem Lab Med 48: 1703–1711

    Article  PubMed  CAS  Google Scholar 

  6. Pencina MJ, D’Agostino RB, Sr., D’Agostino RB, Jr., Vasan RS (2008) Evaluating the added predictive ability of a new marker: from area under the ROC curve to reclassification and beyond. Stat Med 27: 157–172

    Article  PubMed  Google Scholar 

  7. Ware JH (2006) The limitations of risk factors as prognostic tools. N Engl J Med 355: 2615–2617

    Article  PubMed  CAS  Google Scholar 

  8. Pepe MS, Janes H, Longton G, et al. (2004) Limitations of the odds ratio in gauging the performance of a diagnostic, prognostic, or screening marker. Am J Epidemiol 159: 882–890

    Article  PubMed  Google Scholar 

  9. Harreil FE (2001) Regression modeling strategies. With applications to linear models, logistic regression, and survival analysis. New York: Springer

    Google Scholar 

  10. Cook NR, Paynter NP (2011) Performance of reclassification statistics in comparing risk prediction models. Biom J 53: 237–258

    Article  PubMed  Google Scholar 

  11. Pepe MS, Feng Z, Gu JW (2008) Comments on ‘Evaluating the added predictive ability of a new marker: From area under the ROC curve to reclassification and beyond’ by M. J. Pencina et al., Statistics in Medicine (DOI: 10.1002/sim.2929). Stat Med 27: 173–181

    Article  PubMed  CAS  Google Scholar 

  12. Janes H, Pepe MS, Gu W (2008) Assessing the value of risk predictions by using risk stratification tables. Ann Intern Med 149: 751–760

    PubMed  Google Scholar 

  13. Scherz N, Labarère J, Mean M, et al. (2010) Prognostic importance of hyponatremia in patients with acute pulmonary embolism. Am J Respir Crit Care Med 182: 1178–1183

    Article  PubMed  Google Scholar 

  14. Pencina MJ, D’Agostino RB, Sr., Steyerberg EW (2011) Extensions of net reclassification improvement calculations to measure usefulness of new biomarkers. Stat Med 30: 11–21

    Article  PubMed  Google Scholar 

  15. Tzoulaki I, Liberopoulos G, Ioannidis JP (2011) Use of reclassification for assessment of improved prediction: an empirical evaluation. Int J Epidemiol 40: 1094–1105.

    Article  PubMed  Google Scholar 

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Labarère, J., Raskovalova, T. (2012). Quantification de la valeur ajoutée d’un biomarqueur par l’indice de Net Reclassification Improvement . In: Claessens, YÉ., Ray, P. (eds) Les biomarqueurs en médecine d’urgence. Références en médecine d’urgence. Collection de la SFMU. Springer, Paris. https://doi.org/10.1007/978-2-8178-0297-8_5

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  • DOI: https://doi.org/10.1007/978-2-8178-0297-8_5

  • Publisher Name: Springer, Paris

  • Print ISBN: 978-2-8178-0296-1

  • Online ISBN: 978-2-8178-0297-8

  • eBook Packages: MedicineMedicine (R0)

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