alexa Dynamic Registration Method with Balancing for Prognostic Factors in Observational Studies
ISSN: 2155-6180

Journal of Biometrics & Biostatistics
Open Access

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Research Article

Dynamic Registration Method with Balancing for Prognostic Factors in Observational Studies

Masahiro Sugihara1*, Satoshi Morita2, Naoki Yamanouchi1, Shinya Sakai3, Noriaki Ohba3, Wataru Ichikawa4 and Yasuo Ohashi5

1Clinical Data and Biostatistics Department, R&D Division, Daiichi Sankyo Co., Ltd., Tokyo, Japan

2Department of Biostatistics and Epidemiology, Yokohama City University Graduate School of Medicine and Medical Center, Yokohama, Japan

3Statistics Analysis Division 1, Biometrics Department, EPS Co., Ltd., Tokyo, Japan

4Department of Clinical Oncology, National Defense Medical College Hospital, Saitama, Japan

5Department of Biostatistics/Epidemiology and Preventive Health Sciences, University of Tokyo, Tokyo, Japan

*Corresponding Author:
Masahiro Sugihara
Clinical Data and Biostatistics Department
R&D Division, Daiichi Sankyo Co., Ltd.
1-2-58, Hiromachi, Shinagawa-ku
Tokyo 140-8710, Japan
Tel: +813-5740-3422
Fax: +813-5740-3607
E-mail: [email protected]

Received date: March 13, 2012; Accepted date: May 18, 2012; Published date: May 19, 2012

Citation: Sugihara M, Morita S, Yamanouchi N, Sakai S, Ohba N, et al.(2012) Dynamic Registration Method with Balancing for Prognostic Factors in Observational Studies. J Biomet Biostat S7:012.doi:10.4172/2155-6180.S7-012

Copyright: © 2012 Sugihara M, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

 

Abstract

 Randomized controlled trials are the most scientifically informative studies for evaluating treatment effects. However, we need to conduct observational studies to evaluate unallocatable factors such as genotype, preference, or lifestyle. In observational studies, subject characteristics among the comparison groups might be imbalanced due to non-random allocation. We proposed a dynamic registration method to improve comparability among comparison groups with no allocation. The dynamic registration method is a registration method based on the minimization method, which decides whether or not to register a subject based on the background information of subjects already recruited and the new subject. Simulation studies were conducted to examine the performance of this method in improving comparability among comparison groups. Simulation studies showed that the dynamic registration method improves the comparability among comparison groups. The dynamic registration method can be used to enhance the quality of observational studies for unallocatable factors.

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