Clinical Chemistry Link to Randox Laboratories Web Site
HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
 QUICK SEARCH:   [advanced]


     


Clinical Chemistry 49: 1822-1829, 2003; 10.1373/clinchem.2003.021469
This Article
Right arrow Full Text
Right arrow Full Text (PDF)
Right arrow Submit an electronic Letter to
the Editor about this paper
Right arrow View responses
Right arrow Alert me when this article is cited
Right arrow Alert me when eLetters are posted
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 ISI 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 ISI Web of Science (7)
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Kristiansen, J.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Kristiansen, J.
Related Collections
Right arrow Laboratory Management
(Clinical Chemistry. 2003;49:1822-1829.)
© 2003 American Association for Clinical Chemistry, Inc.


Point/Counterpoint

The Guide to Expression of Uncertainty in Measurement Approach for Estimating Uncertainty

An Appraisal

Jesper Kristiansen1

1 The National Institute of Occupational Health, Lersø Parkallé 105, DK-2100 Copenhagen, Denmark. Fax 45-39-165201; e-mail jkr{at}ami.dk.

Background: The aim of the Guide to Expression of Uncertainty in Measurement (GUM) is to harmonize the different practices for estimating and reporting uncertainty of measurement. Although there are clear advantages in having a common approach for evaluating uncertainty, application of the GUM approach to chemistry measurements is not straightforward. In the above commentary, Krouwer suggests that the GUM approach should not be applied to diagnostic assays, because (a) the quality of diagnostic assays is to low, and (b) the GUM uncertainty intervals are too narrow to predict the outliers that occasionally trouble these methods.

Methods: Some of the examples presented by Krouwer are reviewed. Sodium measurements are modeled mathematically to illustrate the GUM approach to uncertainty. A standardized uncertainty evaluation process is presented.

Results: Modeling of sodium measurements demonstrates how the GUM uncertainty interval reflects the treatment of a bias: The width of the uncertainty interval varied depending on whether a correction for a calibrator lot bias was applied, but in both cases it was consistent with the distribution of measurement results. Expanding the uncertainty interval to include outliers runs counter to the definition of uncertainty. Used appropriately, the GUM uncertainty can be helpful in detecting outliers. In standardizing the uncertainty evaluation, the importance of the analytical imprecision and traceability was emphasized. It is problematic that manufacturers of commercial assays rarely inform about the uncertainty of the values assigned to the calibrators. As demonstrated by an example, external quality-assurance data may be used to estimate this uncertainty.

Conclusions: The GUM uncertainty should be applied to measurements in laboratory medicine because it may actually support the forces that drive the work on improving the quality of measurement procedures. However, it is important that the GUM approach is made more manageable by standardizing the uncertainty evaluation procedure as much as possible. It is essential to focus on the traceability and uncertainty of calibrators and reagents supplied by manufacturers of assays. Information about uncertainty is necessary in the evaluation of the uncertainty associated with manufacturers’ measurement procedures, and in general it may force manufacturers to increase their efforts in improving the metrologic and analytical quality of their products.




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


Home page
Ann. N. Y. Acad. Sci.Home page
B. BERCIK INAL, M. KOLDAS, H. INAL, C. COSKUN, A. GUMUS, and Y. DOVENTAS
Evaluation of Measurement Uncertainty of Glucose in Clinical Chemistry
Ann. N.Y. Acad. Sci., April 1, 2007; 1100(1): 223 - 226.
[Abstract] [Full Text] [PDF]


Home page
Clin. Chem.Home page
J. Middleton and J. E. Vaks
Evaluation of Assigned-Value Uncertainty for Complex Calibrator Value Assignment Processes: A Prealbumin Example
Clin. Chem., April 1, 2007; 53(4): 735 - 741.
[Abstract] [Full Text] [PDF]


Home page
Clin. Chem.Home page
R. M. Lequin
Guide to the Expression of Uncertainty of Measurement: Point/Counterpoint
Clin. Chem., May 1, 2004; 50(5): 977 - 978.
[Full Text] [PDF]

eLetters:

Read all eLetters

Response to Kristiansen's Counterpoint
Jan S. Krouwer
Clinical Chemistry Online, 22 Dec 2003 [Full text]



HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
Copyright © 2003 by the American Association for Clinical Chemistry.