Analysis of age-related variations in laboratory tests by use of latent information recovered from routine laboratory data

点击翻译按钮获取中文摘要

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.