An Intelligent Data Mining Model Approach for Adverse Effects of Hormone Replacement Therapy

Y. Lee; K. Dharmala; C.H. Lee

doi:10.1055/s-0038-1627826

Methods of Information in Medicine, Table of Contents

Methods Inf Med 2007; 46(01): 05-18
DOI: 10.1055/s-0038-1627826

Original Articles

Schattauer GmbH

An Intelligent Data Mining Model Approach for Adverse Effects of Hormone Replacement Therapy

Authors

Y. Lee

¹School of Computing and Engineering, University of Missouri – Kansas City, Kansas City, MO, USA
K. Dharmala

²Division of Pharmaceutical Sciences, School of Pharmacy, University of Missouri – Kansas City, Kansas City, MO, USA
C.H. Lee

²Division of Pharmaceutical Sciences, School of Pharmacy, University of Missouri – Kansas City, Kansas City, MO, USA

Abstract

Summary

Objectives: A number of controversial studies have been reported on the potential risk of breast cancer caused by hormone replacement therapy (HRT). Some studies showed a positive relationship between HRT and breast cancer onset, but other studies have not confirmed these results. To clarify the contradictory outcomes in the relationships between HRT and the onset of breast cancer, we have designed an intelligent data mining model (IDM), which is able to find proper prognostic factors for cancer onset and provides alternate measures in interpretation of outcome of clinical data through hierarchies of attributes.

Methods: Based on the selection criteria, we selected 22 sets of random and case-control studies of the last 15 years, which identified any involvements of HRT with breast cancer. We analyzed the relationship between HRT and breast cancer using an IDM model consisting of data mining algorithms and public domain data mining tools. Prognostic factors which underline the major etiological dispositions of breast cancer were identified.

Results: The variables which are closely associated with cancer onset to some degree are age 60-69, age at menopause 40-49, parity 0, age 40-49, and types of menopause oophorectomy. An implementation of IDM model on overall pooled data indicated that there is no significant relationship between breast cancer onset and HRT. It is suggested that HRT patients with specific physiological and pathological conditions related with the higher ranks of prognostic factors may have a greater chance to get breast cancer.

Conclusion: The results of this study may guide biomedical research directed at establishing the causal relationships between various medications and their complications, allowing an accurate assessment of efficacy and side effects of new therapeutic treatment in clinical trials without reliance on a large control population.

Keywords

Estrogen - breast cancer - hormone therapy - side effects - risk factor - cohort study - observation study and casecontrol study

Full Text

References

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