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Absolute Quantification of Aβ1-42 in CSF Using a Mass Spectrometric Reference Measurement Procedure
Published on: March 21, 2017
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Reference Intervals: Comparison of Calculation Methods and Evaluation of Procedures for Merging Reference
George G Klee1, Kiyoshi Ichihara2, Yesim Ozarda3
1Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN.
American Journal of Clinical Pathology
|September 1, 2018
Summary
This study compared six methods for calculating clinical laboratory reference intervals (RIs), finding that parametric methods are best when abnormal values can't be excluded. Merging intrainstitutional data requires caution.
Area of Science:
- Clinical Chemistry
- Laboratory Medicine
- Biostatistics
Background:
- Establishing accurate reference intervals (RIs) is crucial for clinical diagnosis.
- Various statistical procedures exist for RI calculation, leading to potential inconsistencies.
- Harmonizing reference data within institutions presents challenges.
Purpose of the Study:
- To assess the consistency of reference limits and interval widths generated by six different RI calculation procedures.
- To evaluate a protocol for merging intrainstitutional reference data.
Main Methods:
- Compared reference limits and RI widths from Mayo-SAS quantile, EP Evaluator, and four IFCCM (International Federation of Clinical Chemistry and Laboratory Medicine) methods (parametric and nonparametric with/without latent abnormal values exclusion).
- Evaluated regression parameters for harmonizing intrainstitutional reference data.
Main Results:
- Mayo-SAS quantile, EP Evaluator, and nonparametric methods with latent abnormal values exclusion produced similar RIs, often wider than parametric methods.
- Latent abnormal values exclusion yielded narrower RIs for nutritional and inflammatory markers.
- Regression parameter transformation did not guarantee homogeneity of merged intrainstitutional data.
Conclusions:
- Parametric methods are recommended when exclusion of inappropriate values is not feasible.
- Nonparametric procedures may result in wider reference intervals.
- Larger datasets (>200) are advised for reliable estimates; caution is needed when merging intrainstitutional data.
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