Related Experiment Video
Updated: Sep 1, 2025

Procedure and Key Optimization Strategies for an Automated Capillary Electrophoretic-based Immunoassay Method
Published on: September 10, 2017
A practical approach example to measurement uncertainty: Evaluation of 26 immunoassay parameters
Rabia Tan1, Mustafa Yilmaz2, Yusuf Kurtulmuş3
1Department of Clinical Biochemistry, Aydın Public Health Laboratory, Aydın, Turkey.
Introduction:
Measurement uncertainty is a non-negative parameter that characterizes the distribution of all values appropriate to the measured size and is associated with the measured result. In this study, we aimed to compare the results with various suggestions and produce more qualified results by calculating the measurement uncertainties of the immunoassays like fertility hormones, drug concentration tests, cardiac markers, thyroid function tests and tumour markers.
Materials And Methods:
Uncertainty calculation was made in accordance with the top-down approach according to Nordtest guide. The 12-month study of internal and external quality assessment results were used. The parameters of drug concentration tests were performed on the Abbott Architect c8000, other hormones/markers on the i2000 of the same brand.
Results:
Factors that increased the measurement uncertainty of a test were due to external quality control data. The calculations showed that 13 of 26 parameters satisfied quality requirements. The highest uncertainty value, with 28% belonged to cancer antigen 19-9 test. The lowest value was calculated for prolactin with 8.3%. Dehydroepiandrosterone sulfate and phenytoin performed poorly in terms of measurement uncertainty, although internal and external quality control assessment results were considered favourable for both.
Conclusion:
It is recommended that the concept of measurement uncertainty, which plays an important role in the total quality performance of the laboratory, should be followed up by the clinical laboratory experts at certain time intervals and should be increased the awareness of clinicians about the subject.
Related Concept Videos
Uncertainty in Measurement: Accuracy and Precision
Uncertainty: Overview
Data Validation
Key parameters for method validation include:
Uncertainty in Measurement: Reading Instruments
Contaminants and Errors
Another key consideration is determining the appropriate number of samples required to...
Propagation of Uncertainty from Random Error

