Clinical Chemistry
HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
QUICK SEARCH:   [advanced]


     

Clinical Chemistry 47: 2137-2145, 2001;
This Article
Right arrow Full Text
Right arrow Full Text (PDF)
Right arrow Supplemental Tables
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Right arrow Citation Map
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in Web of Science
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Right arrow reprints & permissions
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via Web of Science (30)
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Horn, P. S.
Right arrow Articles by Pesce, A. J.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Horn, P. S.
Right arrow Articles by Pesce, A. J.
Related Collections
Right arrow Laboratory Management
Right arrow General Clinical Chemistry
(Clinical Chemistry. 2001;47:2137-2145.)
© 2001 American Association for Clinical Chemistry, Inc.

Articles

Effect of Outliers and Nonhealthy Individuals on Reference Interval Estimation

Paul S. Horn1a, Lan Feng2, Yanmei Li3 and Amadeo J. Pesce4

1 Department of Mathematical Sciences, University of Cincinnati, Cincinnati, OH 45221-0025.

2 Mount Carmel Health System, Columbus, OH 43222.

3 HGO Technology, Wheeling, WV 26003.

4 Department of Pathology and Laboratory Medicine, University of Cincinnati, Cincinnati, OH 45267-0714.

aAuthor for correspondence. Fax 513-556-3417; e-mail paul.horn{at}uc.edu.

Background: Improvement in reference interval estimation using a new outlier detection technique, even with a physician-determined healthy sample, is examined. The effect of including physician-determined nonhealthy individuals in the sample is evaluated.

Methods: Traditional data transformation coupled with robust and exploratory outlier detection methodology were used in conjunction with various reference interval determination techniques. A simulation study was used to examine the effects of outliers on known reference intervals. Physician-defined healthy groups with and without nonhealthy individuals were compared on real data.

Results: With 5% outliers in simulated samples, the described outlier detection techniques had narrower reference intervals. Application of the technique to real data provided reference intervals that were, on average, 10% narrower than those obtained when outlier detection was not used. Only 1.6% of the samples were identified as outliers and removed from reference interval determination in both the healthy and combined samples.

Conclusions: Even in healthy samples, outliers may exist. Combining traditional and robust statistical techniques provide a good method of identifying outliers in a reference interval setting. Laboratories in general do not have a well-defined healthy group from which to compute reference intervals. The effect of nonhealthy individuals in the computation increases reference interval width by ~10%. However, there is a large deviation among analytes.




The following articles in journals at HighWire Press have cited this article:


Home page
 J Am Coll CardiolHome page
P. Venge, N. Johnston, B. Lindahl, and S. James
Normal plasma levels of cardiac troponin I measured by the high-sensitivity cardiac troponin I access prototype assay and the impact on the diagnosis of myocardial ischemia.
J. Am. Coll. Cardiol., September 22, 2009; 54(13): 1165 - 1172.
[Abstract] [Full Text] [PDF]

Home page
 Ann Clin BiochemHome page
F. Ceriotti, R. Hinzmann, and M. Panteghini
Reference intervals: the way forward
Ann Clin Biochem, January 1, 2009; 46(1): 8 - 17.
[Abstract] [Full Text] [PDF]

Home page
 Ann Clin BiochemHome page
B. Shine
Use of routine clinical laboratory data to define reference intervals
Ann Clin Biochem, September 1, 2008; 45(5): 467 - 475.
[Abstract] [Full Text] [PDF]

Home page
 Clin. Chem.Home page
H. E. Solberg and A. Lahti
Detection of Outliers in Reference Distributions: Performance of Horn's Algorithm
Clin. Chem., December 1, 2005; 51(12): 2326 - 2332.
[Abstract] [Full Text] [PDF]

Home page
 Clin. Chem.Home page
E. Grossi, R. Colombo, S. Cavuto, and C. Franzini
The REALAB Project: A New Method for the Formulation of Reference Intervals Based on Current Data
Clin. Chem., July 1, 2005; 51(7): 1232 - 1240.
[Abstract] [Full Text] [PDF]

Home page
 Clin. Chem.Home page
P. S. Horn and A. J. Pesce
Effect of Ethnicity on Reference Intervals
Clin. Chem., October 1, 2002; 48(10): 1802 - 1804.
[Full Text] [PDF]


HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
Copyright © 2001 by the American Association for Clinical Chemistry.