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)；常態分布資料之效應量(Effect Size)及統合迴歸(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。然而，受測者之種族與年齡為臨床上認定之重要影響RNFL測量值之因素。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，以統合迴歸之分析方法，探討ROC曲線圖形下面積異質性之可能影響因素，將有助於呈現以OCT診斷青光眼之整體診斷力。

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.

目錄
中文摘要	I
ABSTRACT	II
致謝詞	III
目錄	IV
圖目錄	V
表目錄	V
第一章	緒論	1
第二章	統合迴歸的介紹	2
第一節統合迴歸與一般迴歸的差異性	2
第二節何謂統合迴歸	2
第三節統合迴歸的限制性	5
第四節統合迴歸的模型	5
第三章	統合迴歸的分析方法	7
第一節研究步驟	7
第二節統計方法	7
第三節效果量計算	10
第四節資料分析	12
第四章	研究結果	13
第一節研究基本資料	13
第二節同質性檢驗	14
第三節異質性的探討	16
第五章	結論	27
參考文獻	28

 
圖目錄
圖2.2.1：Log relative risk (13組阿斯匹林VS安慰劑的中風)	4
圖4.1.1：OCT眼球診斷方位相對位置	13
圖4.3.1：最後模型預測的AUC圖形	26

表目錄
表 4.2.1：Cirrus和Stratus兩種儀器在固定效應下不同方位的分析總表	14
表 4.2.2：Cirrus和Stratus兩種儀器在固定效應下不同方位的分析總表	15
表4.3.1：迴歸模型-正常人與青光眼患者的MD差異值	16
表4.3.2：迴歸模型-正常人與青光眼患者的PSD差異值	17
表4.3.3：迴歸模型-正常人與青光眼患者的年齡差異值	18
表4.3.4：迴歸模型- AUC不同的測量部位	19
表4.3.5：迴歸模型-不同的測量儀器	20
表4.3.6：迴歸模型-正常人與青光眼患者的PSD差異值以及年齡差異值	21
表4.3.7：迴歸模型-正常人與青光眼患者的PSD差異值以及AUC不同的測量部位	22
表4.3.8：迴歸模型-正常人與青光眼患者的年齡差異值以及AUC不同的測量部位	23
表4.3.9：迴歸模型-正常人與青光眼患者的年齡差異值以及AUC不同的測量部位	24

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