European Journal of Epidemiology

, Volume 25, Issue 9, pp 603–605 | Cite as

Critical evaluation of the Newcastle-Ottawa scale for the assessment of the quality of nonrandomized studies in meta-analyses



Uveal Melanoma Cohort Member Nurse Health Study Quality Item Response Proportion 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



I am very grateful for many helpful comments by an anonymous reviewer on an earlier version of this manuscript.


  1. 1.
    Stroup DF, Berlin JA, Morton SC, Olkin I, Williamson GD, Rennie D, et al. Meta-analysis of observational studies in epidemiology: a proposal for reporting. Meta-analysis of observational studies in epidemiology (MOOSE) group. JAMA. 2000;283(15):2008–12.CrossRefPubMedGoogle Scholar
  2. 2.
    Sanderson S, Tatt ID, Higgins JP. Tools for assessing quality and susceptibility to bias in observational studies in epidemiology: a systematic review and annotated bibliography. Int J Epidemiol. 2007;36(3):666–76.CrossRefPubMedGoogle Scholar
  3. 3.
    Deeks JJ, Dinnes J, D’Amico R, Sowden AJ, Sakarovitch C, Song F, et al. Evaluating non-randomised intervention studies. Health Technol Assess 2003;7(27):iii–173.Google Scholar
  4. 4.
    Juni P, Witschi A, Bloch R, Egger M. The hazards of scoring the quality of clinical trials for meta-analysis. JAMA. 1999;282(11):1054–60.CrossRefPubMedGoogle Scholar
  5. 5.
    Wells GA, Shea B, O’Connell D, Peterson J, Welch V, Losos M, et al. The Newcastle-Ottawa Scale (NOS) for assessing the quality if nonrandomized studies in meta-analyses. Available from: URL: [cited 2009 Oct 19].
  6. 6.
    Li W, Ma D, Liu M, Liu H, Feng S, Hao Z, et al. Association between metabolic syndrome and risk of stroke: a meta-analysis of cohort studies. Cerebrovasc Dis. 2008;25(6):539–47.CrossRefPubMedGoogle Scholar
  7. 7.
    Myung SK, Ju W, McDonnell DD, Lee YJ, Kazinets G, Cheng CT, et al. Mobile phone use and risk of tumors: a meta-analysis. J Clin Oncol. 2009;27:5565–72.CrossRefPubMedGoogle Scholar
  8. 8.
    Miettinen OS. Theoretical epidemiology. Principles of occurrence research in medicine. Albany, New York: Delmar Publishers Inc; 1985.Google Scholar
  9. 9.
    Gefeller O, Pfahlberg A, Brenner H, Windeler J. An empirical investigation on matching in published case-control studies. Eur J Epidemiol. 1998;14(4):321–5.CrossRefPubMedGoogle Scholar
  10. 10.
    Schüz J, Böhler E, Berg G, Schlehofer B, Hettinger I, Schlaefer K, et al. Cellular phones, cordless phones, and the risks of glioma and meningioma (Interphone Study Group, Germany). Am J Epidemiol. 2006;163(6):512–20.CrossRefPubMedGoogle Scholar
  11. 11.
    Austin MA, Criqui MH, Barrett-Connor E, Holdbrook MJ. The effect of response bias on the odds ratio. Am J Epidemiol. 1981;114(1):137–43.PubMedGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2010

Authors and Affiliations

  1. 1.Institut für Klinische Epidemiologie, Medizinische FakultätMartin-Luther-Universität Halle-WittenbergHalle (Saale)Germany

Personalised recommendations