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Clinical Laboratory 47 : 591, 2001.11.
XXI. World Congress of Pathology and Laboratory Medicine G-4

Proposal for Establishment of Genomic Health Management in the Post-genome Era

Tokyo Medical and Dental University, Japan

published edition

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Background: Because information recorded in the human genome is decided on the instant of fertilization and has lifelong consistency, and so it will directly reflect disease etiology and give critical cues for deductive development of disease preventives, genome examination is expected to make great contribution to disease risk prediction / reduction. But knowledge and experience of diagnosis based on current laboratory tests which are focused on cure-oriented medicine cannot be easily applied to genome examination, because it will provide a huge amount of extremely critical information. Then, the feature and its clinical meaning of genome examination are analyzed, and the requirements for which the diagnostic methodology for disease prevention of the next generation is asked are clarified.
Result: [1] The disease risk prediction by genome examination such as SNPs etc. has the following features. (1) Because immense prior investment has already made from the size of a potential market scale in order to accumulate comprehensive databases using the most of IT technology, there is every possibility that very correct indices of diagnostic tests, such as sensitivity / specificity, positive / negative predictive values, pre-test probability and likelihood ratio, will be obtained so that they do not become as compared with the conventional laboratory tests. (2) A term until a disorder actually occurs from the time of its prediction may delay remarkably. (3) There are not few possibilities that a severe risk that cannot be reduced at all will become disclosed. (4) Since the risk is potentially shared with blood relative persons, any disclosed problems of an individual will inevitably influence them. (5) Unlike the case of rare disease with a single origin, genome examination becomes the social problem since no human being is free from any disease risk. (6) Because a huge kind of individual's risks that have a wide range of possibilities will be disclosed at once, it is difficult to understand them as a whole and to adequately cope with them based on conventional theory orusual common sense.
[2] Therefore, unlike the conventional medical treatment, the ultimate purpose of which is restore the health of already affected individuals to its original state, diverse targets as follows should be pursued. (a) better prognosis, (b) minimizing the risk resulting from medical intervention, (c) customer satisfaction, (d) minimizing customer regret, (e) minimizing mental and corporal pain, (f) minimizing restrictions of soul and body activity, (g) doctor's self-evaluation, (h) minimizing doctor's regret and (i) objective evaluation of a doctor.
[3] Among the conventional theory which supports medical judgment, Evidence Based Medicine (EBM) is the idea which is mainly focused on (a) and (b), and may also have an idea with a means to pursue (g), (h), and (i) by some doctor. On the other hand, Medical Decision Making is used as the method of clarifying choice which mainly makes (a) the maximum and makes cost the minimum. Therefore, there is no appropriate model which can treat these (a) - (i) synthetically at present.
Discussion: With evolving the decision tree of Medical Decision Making, if these targets are represented by some proper indices and the relationship among them are represented by some proper functions, a new model which reproduces actual medical judgment to some extent will be established.
Conclusion: In order to bring out the merit of the genome diagnosis of the disease risk prediction, which is expected to expand rapidly in the post-genome era, and to prevent unnecessary confusion, establishment of, so to speak, Genomic Health Management, is pressing need.

Correspondence: Masahiro Mishibori
Tokyo Medical and Dental University, 1-5-45, Yushima,
Bunkyo-ku, 113-8519, Tokyo, Japan;
E-mail: mn.mlab@tmd.ac.jp

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