Data Modeling for Immunological and Clinical Data of Leukemia and Myasthenia Patients

F. Gerneth; R. Haux; C. A. Müller’

doi:10.1055/s-0038-1634862

Methods of Information in Medicine, Table of Contents

Methods Inf Med 1992; 31(02): 136-146
DOI: 10.1055/s-0038-1634862

Original Article

Schattauer GmbH

Data Modeling for Immunological and Clinical Data of Leukemia and Myasthenia Patients

Authors

F. Gerneth

¹University of Tübingen, Special Research Program in Leukemia Research and Immunogenetics, Tübingen

²University of Tübingen, Institute for Medical Information Processing, Tübingen
R. Haux

³University of Heidelberg, Institute for Medical Biometry and Informatics, Department of Medical Informatics, Heidelberg
C. A. Müller’

¹University of Tübingen, Special Research Program in Leukemia Research and Immunogenetics, Tübingen

⁴University of Tübingen, Section on Transplantation Immunology and Immune Hematology, Tübingen, Germany

Abstract

Abstract:

In this study it was investigated whether and to what extent semantic data models and their methods for data modeling are useful for adequate representation and integration of immunological and clinical data. To that end the special research program in leukemia research and immunogenetics (SFB 120) of the University of Tübingen was taken as an example. Based on the semantic data model RIWT we propose the design of a database system, report on its realization, and discuss this approach. Using a semantic data model, the quality of data increased considerably. This means, for instance, that the integration of the molecular-biological knowledge allows a better control of the person-related results. Hence, the decisions based of these data may have greater validity and the treatment on leukemia patients can be improved. Furthermore, the elucidation of immune mechanisms concerning auto-immune diseases could be improved.

Key-Words

Database Design - Semantic Data Model - Hospital Information System - Immunology - Molecular Biology

Full Text

References

REFERENCES
1 Gratwohl A, Hermans J, Zwaan FE. Bone marrow transplantation for leukaemia in Europe. Folia Haematol Leipzig 1989; 116: 353-60.
2 Brotin MM, Horowitz MM, Gale RP. Current status of bone marrow transplant registry. Nat Immun Cell Growth Regul 1988; 07: 334-50.
3 Albert ED, Baur MP, Mayr WR. eds. Histocompatibility Testing 1984. Berlin: Springer; 1984
4 Codd EF. Extending the database relational model to capture more meaning. ACM Transactions on Database Systems 1979; 04: 397-434.
5 Peckham J, Maryanski F. Semantic data models. ACM Computing Surveys 1988; 20: 153-89.
6 Härder T, Reuter A. Architektur von Datenbank-systemen für Non-Standard-Anwendungen. In: Blaser A, Pistor P. eds. Datenbank-Systeme für Büro, Technik und Wissenschaft. Berlin: Springer; 1985: 253-86.
7 Chen PP. The Entity-Relationship Model - toward a unified view of Data. ACM Transactions on Database Systems 1976; 01: 9-36.
8 Jagannathan D, Gluck RL, Fritchman BL. SIM: A database system based on the semantic data model. ACM SIGMOD RECORD 1988; 17: 46-55.
9 Alagic S. Relational Database Technology. New York: Springer; 1986
10 Lyngbaek P, Vianu V. Mapping a semantic database model to the relational model. ACM SIGMOD RECORD 1987; 16: 132-42.
11 Osborn SL, Heaven TE. The design of a relational database systems with abstract data types for domains. ACM Transactions on Database Systems 1988; 11: 357-73.
12 Haux R, Gerneth F. Non-Standard data models for statistical data analysis. Bull Int Stat Inst 1989; 53 (03) 171-90.
13 Haux R, Winter A. Universal relation assumptions in a modified RM/T data model. (submitted).
14 Codd EF. A relational model of data for large shared data banks. Comm ACM 1970; 13: 377-87.
15 Winter A. Die Verwaltung verteilter Datenbestande in einem Klinikuminformationssystem auf der Basis eines unirelationalen Informationssystemmodells (Dr. sc. hum. Dissertation). Department of Medical Informatics. Heidelberg: University of Heidelberg; 1991
16 Mann G, Haux R. Database scheme design for clinical studies based on a semantic data model. (To appear in Computational Statistics & Data Analysis).
17 Winter A. Eine objektorientierte Methode zum Datenbankschemaentwurf auf der Basis des modifizierten RM/T-Modells. In: Giani G, Repges R. eds. Biometrie und Informatik - neue Wege zur Erkenntnisgewinnung in der Medizin. Berlin: Springer; 1989: 199-203.
18 Schlageter G, Stucky W. Datenbanksysteme: Konzepte und Modelle. 2nd ed. Stuttgart: Teubner; 1983
19 Pawelec G, Schlag H, Schwuléra U, Lenz E, Schneider E, Schaudt K, Bühring HJ, Ehninger G. Immunological monitoring of cancer patients during a phase I/II clinical trail of natural interleukin 2. In: Freund M, Welte K. eds. Cytokines in Hematopoiesis, Oncology and AIDS. Heidelberg: Springer; 1991. (in press).
20 Melms A, Klinkert W, Schalke B, Tzartos S, Wekerle H. Lymphocyte interaction in human myasthenia gravis: modulation of T cell proliferation by monoclonal antibodies to the acetylcholine receptor. (submitted).
21 Einsele H, Vallbracht A, Müller CA. Comparison of different techniques for detection of cytomegalovirus infection following bone marrow transplantation. Eur J Clin Microbiol Infect Dis 1990; 09: 595-600.
22 Roitt IM, Brostoff J, Male DK. Immunology. London: Gower Medical Publishing; 1985
23 Khan MA. A brief review of the HLA system. Journal of the Pakistan Medical Association 1989; 39: 187-91.
24 Bodmer WF, Albert E, Bodmer JG. et al. Nomenclature for factors of the HLA system, 1987. In: Dupont B. ed. Immunology of HLA. vol I, Histocompatibility Testing, 1987. New York: Springer; 1989: 72-9.
25 Bodmer JG, Marsh SGE, Parham P. et al. Nomenclature for Factors of the HLA system, 1989. Human Immunol 1990; 28: 326-42.
26 Kerzin-Storrar L, Metcalfe RA, Dyer PA. et al. Genetic factors in myasthenia gravis: A family study. Neurology 1988; 38: 38-42.
27 Gersting JM. Rapid prototyping of database systems in human genetics data collection. J Med Syst 1987; 11: 177-89.
28 Neugebauer M, Willems J, Baur MP. Analysis of multilocus pedigree data by computer. In: Albert ED, Baur MP, Mayr WR. eds. Histocompatibility Testing 1984. Berlin: Springer; 1984: 52-8.
29 Yount EA. The use of relational database commands in retrieval pedigree information. J Med Syst 1987; 11: 169-75.
30 Brand R. The EBMT User Manual. Leiden: Inst Med Stat and Med Inform; 1989
31 Advisory Committee of the International Bone Marrow Transplant Registry. Report of the IBMTR. Bone Marrow Transplantation 1989; 04: 221-8.
32 Baur MP, Albert ED, Mayr WR. The central data analysis of the ninth workshop. In: Albert ED, Baur MP, Mayr WR. eds. Histocompatibility Testing 1984. Berlin: Springer; 1989: 37-51.
33 Sierp G, Bouret E, Albert E. et al. Comparison of different mathematical approaches for computer interpretation of serological HLA data. Intern Mathem Genetics Meeting; Groningen: 1989
34 Sierp G, Albert E. Unbaised serum analysis. In: Albert ED, Baur MP, Mayr WR. eds. Histocompatibility Testing 1984. Berlin: Springer; 1989: 64-8.
35 Project Molecular Biophysics. Program manual for the program package HUSAR. Heidelberg: German Cancer Research Centre; 1991
36 Gerneth F, Haux R, Muller CA. Data modeling for immunological and clinical data of leukemia and myasthenia patients [Report 2/1991]. Institute for Medical Information Processing. Tübingen: University of Tübingen; 1991
37 Barsalou T, Wiederhold G. Applying a semantic model to an immunology database. Proc Ann Symp Comput Appl Med Care 1987; 11: 871-8.