Communications for Statistical Applications and Methods

The Korean Statistical Society (한국통계학회)
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Multivariate Meta-Analysis Methods of Comparing the Sensitivity and Specificity of Two Diagnostic Tests

두 진단검사의 비교에 대한 민감도와 특이도의 다변량 메타분석법

  • Nam, Seon-Young (Biostatistics Division, Department of Medical Lifescience, The Catholic University of Korea) ;
  • Song, Hae-Hiang (Biostatistics Division, Department of Medical Lifescience, The Catholic University of Korea)
  • 남선영 (가톨릭대학교 의생명과학교실 의학통계학과) ;
  • 송혜향 (가톨릭대학교 의생명과학교실 의학통계학과)
  • Received : 20100900
  • Accepted : 20101100
  • Published : 2011.01.30
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Abstract

Researchers are continuously trying to find innovative diagnostic tests and published articles are accumulating at an enormous rate in many medical fields. Meta-analysis enables previously published study results to be reviewed and summarized; therefore, an objective assessment of diagnostic tests can be done with a meta-analysis of sensitivities and specificities. Data obtained by applying two diagnostic tests to a well-defined group of diseased patients produce a pair of sensitivity and by applying the same medical tests to a group of non-diseased subjects produce a pair of specificity. The statistical tests in the meta-analysis need to consider the correlatedness of the results from two diagnostic tests applied to the same diseased and non-diseased subjects. The associations between two diagnostic test results are often found to be unequal for the diseased and non-diseased subjects. In this paper, multivariate meta-analytic methods are studied by taking into account the different associations between correlated variables. On the basis of Monte Carlo simulations, we evaluate the performance of the multivariate meta-analysis methods proposed in this paper.

질병에 대한 새로운 진단검사 방법이 의학 연구자들에 의해 끊임없이 개발되고 있으며, 기존 진단검사 방법과 새로운 진단검사 방법을 비교하는 연구논문이 계속 출간되어 누적되고 있다. 메타분석법으로 다수 연구논문의 결과를 종합하여 정확성이 높은 진단검사에 대해 객관적인 결론을 내리게 된다. 이와같이 출간된 두 진단검사를 비교하는 각 연구논문은 각각 질병을 가진 개체와 질병을 가지지 않은 개체에 두 검사를 모두 실시하여 한 쌍의 민감도와 특이도를 구하여 비교한다. 이러한 연구논문의 결과를 종합하는 메타분석은 동일 개체에 실시한 두 검사로 인해 한 쌍의 민감도간의 연관성과 한 쌍의 특이도 간의 연관성을 고려한 메타분석법을 본 논문에서 제시한다. 논문예제 자료와 모의시험으로 메타분석 검정통계량의 효율성을 평가한다.

Keywords

References

  1. Cho, H. and Cole, S. R. (2006). Bivariate meta-ananlysis of sensitivity and specificity with sparse data: A generalized linear mixed model approach, Journal of Clinical Epidemiology, 59, 1331-1333. https://doi.org/10.1016/j.jclinepi.2006.06.011
  2. Harbord, R. M., Deeks, J. J., Egger, M., Whiting, P. and Sterne, J. A. C. (2007). A unification of models for meta-analysis of diagnostic accuracy studies, Biostatistics, 8, 239-251. https://doi.org/10.1093/biostatistics/kxl004
  3. Menke, J. (2010). Bivariate random-effects meta-analysis of sensitivity and specificity with SAS PROC GLIMMIX, Methods Inf Med, 49, 54-64.
  4. Picano, E., Bedetti, G., Varga, A. and Cseh, E. (2000). The comparable diagnostic accuracies of dobutamine-stress and dipyridamole-stress echocardiographies: A meta-analysis, Coronary Artery Disease, 11, 151-159. https://doi.org/10.1097/00019501-200003000-00010
  5. Reitsma, J. B., Glas, A. S., Rutjes, A. W. S., Rob, J. S., Bossuyt, P. M. and Zwinderman, A. H. (2005). Bivariate analysis of sensitivity and specificity produces informative summary measures in diagnostic reviews, Journal of Clinical Epidemiology, 58, 982-990. https://doi.org/10.1016/j.jclinepi.2005.02.022
  6. Riley, R. D., Abrams, K. R., Sutton, A. J., Lambert, P. C. and Thompson, J. R. (2007a). Bivariate random-effects meta-analysis and the estimation of between-study correlation, BMC Medical Research Methodology, 7, 3. https://doi.org/10.1186/1471-2288-7-3
  7. Riley, R. D., Abrams, K. R., Lambert, P. C., Sutton, A. J. and Thompson, J. R. (2007b). An evaluation of bivariate random-effects meta-analysis for the joint synthesis of two correlated outcomes, Statistics in Medicine, 26, 78-97. https://doi.org/10.1002/sim.2524
  8. Snedecor, G. W. and Cochran, W. G. (1989). Statistical Methods, Eighth Edition, Iowa State University Press.
  9. van Houwelingen, H. C., Arends, L. R. and Theo, S. (2002). Advanced methods in meta-analysis: multivariate approach and meta-regression, Statistics in Medicine, 21, 589-624. https://doi.org/10.1002/sim.1040