2002 Fiscal Year Final Research Report Summary
Analysis of age-related variations in laboratory tests by use of latent information recovered from routine laboratory data
| Project/Area Number |
13672437
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Laboratory medicine
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| Research Institution | Yamaguchi University (2002)
Kawasaki Medical School (2001) |
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Principal Investigator |
ICHIHARA Kiyoshi Yamaguchi University School of Medicine, Professor, 医学部, 教授 (10144495)
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| Project Period (FY) |
2001 – 2002
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| Keywords | reference interval / disease-specific reference interval / age-related changes / latent reference value extraction method / data-mining / latent abnormal value exclusion method / standardization / 小児基準値 |
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| Research Abstract |
I have developed a data-mining method to derive a reference interval (RI) for laboratory tests from a routine laboratory data, called "latent reference value extraction method", in 1996. It features simultaneous setting of RIs for multiple test items mutually related and a rigid exclusion of those individuals with abnormal values in other test items. Thus it requires an iterative processing to optimize RIs. In this research I developed a realistic algorithm to obtain appropriate initial estimates of RIs, to exclude apparently abnormal individuals, and to adjust for a distorted age distribution commonly seen in patients' population. A software based on the revised methodology not only has a flexible ability to optimize derivation of RIs but also has an ability to derive age-specific reference interval using a stepwise age-adjusted exclusion of abnormal values. The software was applied to various clinical laboratory data. In Okayama, age-related RIs were derived for common test items. Consistent age-related changes in RIs were observed in all the analytes. It was also applied to reveal year-by-year changes in RIs (0 to 23 year old) for major laboratory analytes. All of them showed peculiar profiles while a use of conventional methodology led to apparently distorted profiles. It was also found to be applicable to obtain so-called disease-specific RIs using a large data from hemodialysis patients.
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