Display options
Cite
Mendes D, Alves C, Batel-Marques F. Number needed to treat (NNT) in clinical literature: an appraisal. BMC Med. 2017;15(1):112doi: 10.1186/s12916-017-0875-8.
Mendes, D., Alves, C., & Batel-Marques, F. (2017). Number needed to treat (NNT) in clinical literature: an appraisal. BMC medicine, 15(1), 112. https://doi.org/10.1186/s12916-017-0875-8
Mendes, Diogo, et al. "Number needed to treat (NNT) in clinical literature: an appraisal." BMC medicine vol. 15,1 (2017): 112. doi: https://doi.org/10.1186/s12916-017-0875-8
Mendes D, Alves C, Batel-Marques F. Number needed to treat (NNT) in clinical literature: an appraisal. BMC Med. 2017 Jun 01;15(1):112. doi: 10.1186/s12916-017-0875-8. PMID: 28571585; PMCID: PMC5455127.
Copy Download .nbib Format: NLM
Share it on

BMC Med. 2017 Jun 01;15(1):112. doi: 10.1186/s12916-017-0875-8.

Number needed to treat (NNT) in clinical literature: an appraisal.

BMC medicine

Diogo Mendes, Carlos Alves, Francisco Batel-Marques

Affiliations

  1. AIBILI - Association for Innovation and Biomedical Research on Light and Image, CHAD - Centre for Health Technology Assessment and Drug Research, Azinhaga de Santa Comba, Celas, 3000-548, Coimbra, Portugal. [email protected].
  2. University of Coimbra, School of Pharmacy, Laboratory of Social Pharmacy and Public Health, Coimbra, Portugal. [email protected].
  3. AIBILI - Association for Innovation and Biomedical Research on Light and Image, CHAD - Centre for Health Technology Assessment and Drug Research, Azinhaga de Santa Comba, Celas, 3000-548, Coimbra, Portugal.
  4. University of Coimbra, School of Pharmacy, Laboratory of Social Pharmacy and Public Health, Coimbra, Portugal.

PMID: 28571585 PMCID: PMC5455127 DOI: 10.1186/s12916-017-0875-8

Abstract

BACKGROUND: The number needed to treat (NNT) is an absolute effect measure that has been used to assess beneficial and harmful effects of medical interventions. Several methods can be used to calculate NNTs, and they should be applied depending on the different study characteristics, such as the design and type of variable used to measure outcomes. Whether or not the most recommended methods have been applied to calculate NNTs in studies published in the medical literature is yet to be determined. The aim of this study is to assess whether the methods used to calculate NNTs in studies published in medical journals are in line with basic methodological recommendations.

METHODS: The top 25 high-impact factor journals in the "General and/or Internal Medicine" category were screened to identify studies assessing pharmacological interventions and reporting NNTs. Studies were categorized according to their design and the type of variables. NNTs were assessed for completeness (baseline risk, time horizon, and confidence intervals [CIs]). The methods used for calculating NNTs in selected studies were compared to basic methodological recommendations published in the literature. Data were analyzed using descriptive statistics.

RESULTS: The search returned 138 citations, of which 51 were selected. Most were meta-analyses (n = 23, 45.1%), followed by clinical trials (n = 17, 33.3%), cohort (n = 9, 17.6%), and case-control studies (n = 2, 3.9%). Binary variables were more common (n = 41, 80.4%) than time-to-event (n = 10, 19.6%) outcomes. Twenty-six studies (51.0%) reported only NNT to benefit (NNTB), 14 (27.5%) reported both NNTB and NNT to harm (NNTH), and 11 (21.6%) reported only NNTH. Baseline risk (n = 37, 72.5%), time horizon (n = 38, 74.5%), and CI (n = 32, 62.7%) for NNTs were not always reported. Basic methodological recommendations to calculate NNTs were not followed in 15 studies (29.4%). The proportion of studies applying non-recommended methods was particularly high for meta-analyses (n = 13, 56.5%).

CONCLUSIONS: A considerable proportion of studies, particularly meta-analyses, applied methods that are not in line with basic methodological recommendations. Despite their usefulness in assisting clinical decisions, NNTs are uninterpretable if incompletely reported, and they may be misleading if calculating methods are inadequate to study designs and variables under evaluation. Further research is needed to confirm the present findings.

Keywords: Case–control studies; Cohort studies; Data interpretation; Epidemiologic methods; Evidence-based medicine; Meta-analysis; Numbers needed to treat; Randomized controlled trial; Statistical

References

  1. J Clin Epidemiol. 2006 Mar;59(3):217-23 - PubMed
  2. Int J Clin Pract. 2013 May;67(5):407-11 - PubMed
  3. Pharmacoepidemiol Drug Saf. 2014 Jul;23(7):667-78 - PubMed
  4. Rambam Maimonides Med J. 2015 Jul 30;6(3):null - PubMed
  5. Acta Psychiatr Scand. 2010 Feb;121(2):94-102 - PubMed
  6. J Epidemiol Community Health. 2002 Aug;56(8):600-5 - PubMed
  7. J Clin Epidemiol. 2014 Feb;67(2):236-8 - PubMed
  8. J Clin Epidemiol. 2010 Aug;63(8):820-5 - PubMed
  9. BMJ. 2000 Feb 19;320(7233):503-6 - PubMed
  10. BMJ. 1995 Feb 18;310(6977):452-4 - PubMed
  11. Ann Intern Med. 1997 May 1;126(9):712-20 - PubMed
  12. Thorax. 2013 Jun;68(6):540-3 - PubMed
  13. J Clin Epidemiol. 2012 Jan;65(1):42-6 - PubMed
  14. Expert Opin Drug Saf. 2016 Oct;15(10 ):1301-12 - PubMed
  15. Neurology. 2009 Sep 22;73(12):984-90 - PubMed
  16. Int J Epidemiol. 2002 Feb;31(1):72-6 - PubMed
  17. N Engl J Med. 1988 Jun 30;318(26):1728-33 - PubMed
  18. BMC Public Health. 2003 Jan 23;3:7 - PubMed
  19. BMJ. 1999 Dec 4;319(7223):1492-5 - PubMed
  20. Pharmacoepidemiol Drug Saf. 2012 Jan;21(1):21-33 - PubMed
  21. BMC Med Res Methodol. 2002;2:3 - PubMed
  22. BMJ. 2003 Nov 15;327(7424):1162-5 - PubMed
  23. JAMA. 2010 Jul 28;304(4):411-8 - PubMed
  24. BMC Med Res Methodol. 2002;2:1 - PubMed
  25. BMC Med Res Methodol. 2002;2:2 - PubMed
  26. J Clin Epidemiol. 2013 Sep;66(9):1038-44 - PubMed
  27. Stat Med. 2014 Feb 28;33(5):798-810 - PubMed
  28. J Clin Epidemiol. 2014 Feb;67(2):238-9 - PubMed
  29. J Clin Epidemiol. 2010 Jan;63(1):46-55 - PubMed
  30. Int J Epidemiol. 2012 Oct;41(5):1445-59 - PubMed
  31. Drug Saf. 1999 Feb;20(2):109-17 - PubMed
  32. BMC Med Res Methodol. 2009 Mar 20;9:21 - PubMed
  33. Pharmacoepidemiol Drug Saf. 2015 Dec;24(12 ):1259-70 - PubMed
  34. BMJ. 2010 Mar 23;340:c869 - PubMed
  35. JAMA. 2002 Jun 5;287(21):2813-4 - PubMed
  36. ACP J Club. 2003 Mar-Apr;138(2):A11-2 - PubMed
  37. CMAJ. 2008 Sep 9;179(6):549-53 - PubMed
  38. J Clin Epidemiol. 2002 May;55(5):525-30 - PubMed
  39. Ann Intern Med. 2001 Apr 17;134(8):663-94 - PubMed
  40. CNS Drugs. 2016 Oct;30(10):909-29 - PubMed
  41. BMJ. 1999 Jun 5;318(7197):1548-51 - PubMed
  42. Mayo Clin Proc. 2008 Aug;83(8):870-9 - PubMed
  43. Stat Med. 1998 Sep 15;17(17):1923-42 - PubMed
  44. J Epidemiol Community Health. 2002 Aug;56(8):606-10 - PubMed
  45. Stat Med. 2010 Mar 30;29(7-8):851-9 - PubMed
  46. Int J Biostat. 2011;7(1):6 - PubMed
  47. J Clin Epidemiol. 2016 Apr;72:16-26 - PubMed
  48. Stat Med. 2000 Jul 15;19(13):1707-28 - PubMed
  49. N Engl J Med. 2009 Jul 23;361(4):424-5 - PubMed
  50. Lancet. 2000 Nov 18;356(9243):1757-9 - PubMed
  51. Stat Med. 2007 Dec 30;26(30):5586-95 - PubMed
  52. BMJ. 1998 Nov 7;317(7168):1309-12 - PubMed

MeSH terms

Publication Types