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    Title: ROC曲線下面積之統合分析法 : 青光眼診斷之應用
    Other Titles: Meta analysis method for area under ROC curve : application to glaucoma diagnosis
    Authors: 蕭力誠;Hsiao, Li-Cheng
    Contributors: 淡江大學數學學系碩士班
    張玉坤;Chang, Yue-Cune
    Keywords: 統合分析;ROC曲線;ROC曲線圖形下面積;光電同調斷層掃描儀;青光眼診斷;視神經纖維層;Meta-Analysis;ROC Curve;Area under ROC Cure(AUC);Optical Coherence Tomography(OCT);Glaucoma Diagnosis;Retinal Nerve Fiber Layer
    Date: 2011
    Issue Date: 2011-12-28 18:12:53 (UTC+8)
    Abstract: 統合分析是將一些議題相關但彼此獨立的臨床實驗之研究結果(大都取材於已發表之期刊論文),以量性加權平均的方法結合統整,用來代表此議題現階段之研究結果,據此評估療效或草擬新的臨床實驗之依據。常用之統合分析方法依資料特性有: 二元資料之相對危險度(Relative Risk)、勝算比(Odds Ratio)及率差(Rates Difference);常態分佈資料之效應量(Effect Size)及統合回歸(Meta Regression)等。至於臨床醫學診斷常用之ROC曲線圖形下面積的統合分析方法,至今尚未被提出。
    青光眼是不可逆的視神經病變,其疾病的特色就是漸進性的視神經纖維層(Retinal Nerve Fiber Layer,RNFL)厚度的變薄,其嚴重度可以客觀的由影像檢查儀進行評估,目前眼科是以光電同調斷層掃描儀(Optical Coherence Tomography,OCT)為主。現今發表之文獻以OCT診斷青光眼之診斷力呈現顯著之異質性,所用診斷力指標常以靈敏度(Sensitivity)、特異性(Specificity)及ROC曲線圖形下面積呈現。據此,以隨機效應之統合分析方法,綜合ROC曲線圖形下面積,將有助於呈現以OCT診斷青光眼之整體診斷力。本研究計畫將提出ROC曲線圖形下面積之固定及隨機效應的統合分析方法,並將之應用在以OCT診斷青光眼的研究議題。
    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.
    Glaucoma is 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. 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, a random effects’ meta-analysis for AUC will be helpful to synthesize the overall diagnostic capacities of OCT for glaucoma. In this study, we are going to propose a fixed/random effects meta-analysis method for area under ROC curve and apply it to glaucoma diagnostic by OCT.
    Appears in Collections:[數學學系暨研究所] 學位論文

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