Meta Regression Analysis Method for Area under ROC Curve: Application to Glaucoma Diagnosis

• Main Authors: Chung-Yuan Ho, 何仲遠
• Other Authors: 張玉坤
• Format: Others
• Language: zh-TW
• Published: 2011
• Online Access: http://ndltd.ncl.edu.tw/handle/92443545856026228649

碩士 === 淡江大學 === 數學學系碩士班 === 99 === Meta-analysis is a quantitative weighted average method to combine the results of related but independent studies (usually drawn from the published literatures) and synthesize summaries and conclusions which may be used to evaluate the therapeutic effects and/or plain new study accordingly. The commonly used meta-analyses, dependent on the characteristic of data, are: the relative risk, odds ratio, and rates difference for binary data and effect size and meta-regression for normally distributed data. Meta-analysis for area under ROC curve (AUC), a commonly used medical diagnosis method, has not been proposed yet. Glaucomais an irreversible optic neuropathy, which characterized by progressive retinal nerve fiber layer(RNFL)thinning.Its severity could be evaluated objectively by imaging techniques which mainly by optical coherence tomography (OCT) in current ophthalmology. However, subject’s ethnicity and age are considered as clinically important factors for RNFL measurements. The diagnostic capacities of OCT for glaucoma were heterogeneous in the current published literatures. Most of them were presented in terms of sensitivity, specificity, and area under ROC curve (AUC). Accordingly, meta regression analysiscan be used to explore the potential prognostic factors for the heterogeneityof AUC that will be helpful to synthesize the overall diagnostic capacities of OCT for glaucoma.