Remember Me
Or use your Academic/Social account:


Or use your Academic/Social account:


You have just completed your registration at OpenAire.

Before you can login to the site, you will need to activate your account. An e-mail will be sent to you with the proper instructions.


Please note that this site is currently undergoing Beta testing.
Any new content you create is not guaranteed to be present to the final version of the site upon release.

Thank you for your patience,
OpenAire Dev Team.

Close This Message


Verify Password:
Verify E-mail:
*All Fields Are Required.
Please Verify You Are Human:
fbtwitterlinkedinvimeoflicker grey 14rssslideshare1
Bartlett, JW; Frost, C; Mattsson, N; Skillbäck, T; Blennow, K; Zetterberg, H; Schott, JM (2012)
Publisher: Future Medicine
Languages: English
Types: Article
: New proposed criteria for the clinical diagnosis of Alzheimer's disease increasingly incorporate biomarkers, most of which are normally measured on a continuous scale. Operationalizing such criteria thus requires continuous biomarkers to be dichotomized, which in turns requires the selection of a cut-point at which to dichotomize. In this article, we review the statistical principles underlying the choice of cut-points, describe some of the most commonly adopted statistical approaches used to estimate cut-points, highlight potential pitfalls in some of the approaches and characterize in what sense the estimated cut-point from each approach is optimal. We also emphasize that how a cut-point is selected must be made in reference to how the resulting dichotomized biomarker is to be used, and in particular what actions will follow from a positive or negative test result.
  • The results below are discovered through our pilot algorithms. Let us know how we are doing!

    • 1. Andreasen N, Minthon L, Davidsson P et al.: Evaluation of CSF-tau and CSF-Abeta42 as diagnostic markers for Alzheimer disease in clinical practice. Arch Neurol 58(3), 373-379 (2001).
    • 2. Shaw LM, Vanderstichele H, Knapik-Czajka M et al.: Cerebrospinal fluid biomarker signature in Alzheimer's Disease Neuroimaging Initiative Subjects. Ann Neurol 65, 403-413 (2009). * Original paper which estimated cut-points for CSF biomarkers to maximize accuracy, using data from autopsy confirmed AD subjects and normal controls.
    • 3. Mattsson N, Zetterberg H, Hansson O et al.: CSF biomarkers and incipient Alzheimer disease in patients with mild cognitive impairment. JAMA 302, 385-393 (2009). * Original paper which estimated cut-points for CSF biomarkers to give 85% sensitivity for AD, using data from AD subjects and controls.
    • 4. Hansson O, Zetterberg H, Buchhave P et al.: Association between CSF biomarkers and incipient Alzheimer's disease in patients with mild cognitive impairment: a follow-up study. Lancet Neurol 5(3), 228-234 (2006).
    • 5. Schott JM, Bartlett JW, Fox NC, Barnes J: Increased brain atrophy rates in cognitively normal older adults with low cerebrospinal fluid Aβ1-42. Ann Neurol, 68(6):825-34 (2010).
    • 6. Jack CR, Knopman DS, Jagust WJ et al.: Hypothetical model of dynamic biomarkers of the Alzheimer's pathological cascade. Lancet Neurol, 9(1), 119-128 (2010).
    • 7. Dubois B, Feldman HH, Jacova C et al.: Research criteria for the diagnosis of Alzheimer's disease: revising the NINCDS-ADRDA criteria. Lancet Neurol 6(8), 734-746 (2007).
    • 8. Sperling RA, Aisen PS, Beckett LA et al. Toward defining the preclinical stages of Alzheimer's disease: recommendations from the National Institute on Aging-Alzheimer's Association workgroups on diagnostic guidelines for Alzheimer's disease. Alzheimers Dement 7(3), 280-292 (2011).
    • 9. Pepe MS. The Statistical Evaluation of Medical Tests for Classification and Prediction. Oxford University Press, (2003). * Book describing the statistical concepts and methods involved in classification and prediction.
    • 10. Grimes DA, Schulz KF: Uses and abuses of screening tests. Lancet 359, 881-884 (2002). * Original paper highlighting important issues which should be considered when contemplating using a biomarker as a screening test.
    • 11. Sjögren M, Vanderstichele H, Agren H et al. Tau and Aβ42 in cerebrospinal fluid from healthy adults 21-93 years of age: establishment of reference values. Clin Chem 47(10), 1776-1881 (2001).
    • 13. Jack CR, Vemuri P, Wiste HJ et al.: Evidence for ordering of Alzheimer Disease Biomarkers. Arch Neurol 68(12), 1526-1535 (2011).
    • 14. Fluss R, Faraggi D, Reiser B: Estimation of the Youden index and its associated cutpoint point. Biom J. 47(4), 458-472 (2005).
    • 15. Krzanowski WJ, Hand DJ. ROC Curves for Continuous Data. CRC Press, 2009.
    • 16. Youden WJ. An index for rating diagnostic tests. Cancer 3, 32-5 (1950).
    • 17. Schisterman EF, Perkins NJ, Liu A et al.: Optimal cut-point and its corresponding Youden index to discriminate individuals using pooled blood samples. Epidemiology 16, 73-81 (2005).
    • 18. Royston P, Thompson SG. Model-based screening by risk with application to Down's syndrome. Stat Med 11(2), 257-268 (1992).
    • 19. De Meyer G, Shapiro F, Vanderstichele H et al.: Diagnosis-independent Alzheimer disease biomarker signature in cognitively normal elderly people. Arch Neurol .67, 949-956 (2010).
    • 20. Leeflang MMG, Moons KGM, Reitsma JB et al.: Bias in sensitivity and specificity caused by datadriven selection of optimal cutpoint values: mechanisms, magnitude, and solutions. Clin Chem 54, 729-737 (2008).
  • No related research data.
  • No similar publications.

Share - Bookmark

Cite this article