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Progress in Clinical Neurosciences: Measuring the Benefit of Therapies for Neurological Disorders

Published online by Cambridge University Press:  02 December 2014

Miguel Bussière  and
Samuel Wiebe
Miguel Bussière*
Affiliation:
Department of Clinical Neurological Sciences, University of Western Ontario, London, Ontario, Canada
Samuel Wiebe
Affiliation:
Department of Clinical Neurosciences, University of Calgary, Calgary, Alberta, Canada
*
Division of Neurology, Department of Clinical Neurological Sciences, University of Western Ontario, 339 Windermere Road, Rm 7-GE6, London, Ontario, N6A 5A5, Canada
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Abstract:

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Background:

Clinicians in the neurosciences need to interpret and apply a growing body of evidence about therapy.

Methods:

Using a clinical scenario about painful diabetic neuropathy and evidence about one treatment option, we review the advantages, limitations, and the clinical interpretation of commonly reported measures of effectiveness, emphasizing their application to the care of individual patients.

Results:

Absolute differences between treatment and control groups (e.g., absolute risk difference) are clinically intuitive and preferable to relative measures (e.g., relative risk). The number needed to treat is particularly useful and clinically applicable. Continuous measures are best interpreted using thresholds of clinically important change, which provide information about the number of patients experiencing meaningful improvement or worsening.

Conclusions:

Using simple principles of evidence based care, clinicians can correctly interpret the common measures of treatment effectiveness and apply them to the care of individual patients.

Résumé:

RÉSUMÉ:Introduction:

Les cliniciens en neurosciences doivent interpréter et appliquer de plus en plus de données sur le traitement des maladies neurologiques.

Méthodes:

Au moyen d’un scénario clinique décrivant une neuropathie diabétique douloureuse et des données sur une option thérapeutique, nous avons revu les avantages, les limites et l’interprétation clinique de mesures d’efficacité fréquemment rapportées, en mettant l’accent sur leur application au traitement de patients individuels.

Résultats:

Les différences absolues entre le groupe sous traitement et le groupe témoin (e.g. la différence absolue du risque) sont intuitives en clinique et préférables à des mesures relatives (e.g. le risque relatif). Le nombre de sujets à traiter (NNT) est particulièrement utile et il est applicable en clinique. La meilleure interprétation de mesures continues est l’utilisation de seuils de changements importants en clinique qui donnent de l’information sur le nombre de patients dont l’état s’améliore ou empire de façon significative.

Conclusions:

En utilisant des principes simples de thérapie factuelle, les cliniciens peuvent interpréter correctement les mesures courantes d’efficacité thérapeutique et les appliquer aux soins de patients particuliers.

Type
Review Article
Information
Canadian Journal of Neurological Sciences , Volume 32 , Issue 4 , November 2005 , pp. 419 - 424
Copyright
Copyright © The Canadian Journal of Neurological 2005

References

1. Wiebe, S, Demaerschalk, B. Evidence based care in the neurosciences. Can J Neurol Sci 2002; 29: 115–119.CrossRefGoogle ScholarPubMed
2. Schulz, KF, Moher, D, Altman, DG. Interpreting the number needed to treat. JAMA 2002; 288: 831–832.Google Scholar
3. Moher, D, Altman, DG, Schulz, KF. Reporting the clinical importance of randomized controlled trials. CMAJ 2002; 166: 711–712.Google Scholar
4. Laupacis, A, Sackett, DL, Roberts, RS. An assessment of clinically useful measures of the consequences of treatment. N Engl J Med 1988; 318: 1728-1733.Google Scholar
5. Cook, RJ, Sackett, DL. The number needed to treat: a clinically useful measure of treatment effect. BMJ 1995; 310: 452–454.Google Scholar
6. McQuay, HJ, Moore, RA. Using numerical results from systematic reviews in clinical practice. Ann Intern Med 1997; 126: 712–720.Google Scholar
7. Backonja, M, Beydoun, A, Edwards, KR, et al. Gabapentin for the symptomatic treatment of painful neuropathy in patients with diabetes mellitus: a randomized controlled trial. JAMA 1998; 280: 1831–1836.Google Scholar
8. Backonja, MM. Use of anticonvulsants for treatment of neuropathic pain. Neurology 2002; 59(5 Suppl 2): S14-S17.Google Scholar
9. Davies, HT, Crombie, IK, Tavakoli, M. When can odds ratios mislead? BMJ 1998; 316: 989–991.Google Scholar
10. Naylor, CD, Chen, E, Strauss, B. Measured enthusiasm: does the method of reporting trial results alter perceptions of therapeutic effectiveness? Ann Intern Med 1992; 117: 916–921.Google Scholar
11. Bucher, HC, Weinbacher, M, Gyr, K. Influence of method of reporting study results on decision of physicians to prescribe drugs to lower cholesterol concentration. BMJ 1994; 309: 761–764.Google Scholar
12. Chatelier, G, Zapletal, E, Lemaitre, D, Menard, J, Degoulet, P. The number needed to treat: a clinically useful nomogram in its proper context. BMJ 1996; 312: 426–429.Google Scholar
13. Sackett, DL, Straus, SE, Richardson, WS, Rosenberg, W, Haynes, RB. Chapter 5. Therapy. In: Sackett, DL, Straus, SE, Richardson, WS, Rosenberg, W, Haynes, RB (Eds). Evidence-Based Medicine. How to Practice and Teach EBM. (2nd ed.) New York: Churchill Livingstone 2000: 136–137.Google Scholar
14. Sackett, DL, Straus, SE, Richardson, WS, Rosenberg, W, Haynes, RB. Chapter 5. Therapy. In: Sackett, DL, Straus, SE, Richardson, WS, Rosenberg, W, Haynes, RB (Eds). Evidence-Based Medicine. How to Practice and Teach EBM. (2nd ed.) New York: Churchill Livingstone 2000: 116–117.Google Scholar
15. Medical Research Council Antiepileptic Drug Withdrawal Study Group. Prognostic index for recurrence of seizures after remission of epilepsy. BMJ 1993; 306: 1374–1378.Google Scholar
16. Smith, LA, Oldman, AD, McQuay, HJ, Moore, RA. Eletriptan for acute migraine (Cochrane Review). In: The Cochrane Library Issue 3. 2004. Oxford: Update Software.Google Scholar
17. McAlister, FA, Straus, SE, Guyatt, GH, Haynes, RB. Users’ guides to the medical literature: XX. Integrating research evidence with the care of the individual patient. Evidence-Based Medicine Working Group. JAMA 2000; 283: 2829–2836.Google Scholar
18. Cina, CS, Clase, CM, Haynes, RB. Carotid endarterectomy for symptomatic carotid stenosis (Cochrane Review). In: The Cochrane Library Issue 3. 2004. Oxford: Update Software.Google Scholar
19. Smeeth, L, Haines, A, Ebrahim, S. Numbers needed to treat derived from meta-analyses - sometimes informative, usually misleading. BMJ 1999; 318: 1548–1551.Google Scholar
20. Sinclair, JC, Cook, RJ, Guyatt, GH, Pauker, SG, Cook, DJ. When should an effective treatment be used? Derivation of the threshold number needed to treat and the minimum event rate for treatment. J Clin Epidemiol 2001; 54: 253–262.Google Scholar
21. Cohen, J. The t test for means. In: Cohen, J, (Ed). Statistical Power Analysis For The Behavioral Sciences. Hillsdale: Lawrence Erlbaum Associates, 1988: 19–74.Google Scholar
22. Guyatt, GH, Juniper, EF, Walter, SD, Griffith, LE, Goldstein, RS. Interpreting treatment effects in randomised trials. BMJ 1998;316: 690–693.Google Scholar
23. Wiebe, S, Guyatt, G, Weaver, B, Matijevic, S, Sidwell, C. Comparative responsiveness of generic and specific quality-of-life instruments. J Clin Epidemiol 2003; 56: 52–60.Google Scholar
24. Norman, GR, Sloan, JA, Wyrwich, KW. Interpretation of changes in health-related quality of life. The remarkable universality of half a standard deviation. Medical Care 2003; 41: 582–592.Google Scholar