有效進行系統文獻回顧與統合分析研究

Effectively Performing Systematic Review and Meta-Analysis

王慧瑜(Hue-Yu Wang) ； 劉人瑋(Jen-Wei Liu) ； 葉明功(Ming-Kung Yeh)

《臺灣臨床藥學雜誌》 26卷1期 (2018/01) Pp. 1-10

https://doi.org/10.6168/FJCP.201801_26(1).0001

摘要

隨著研究綜述方法學的進展，系統性文獻回顧(systematic review, SR)與統合分析(meta-analysis, MA)已大量被運用於臨床研究，然而這二個名詞卻常被混用。雖SR 常應用MA彙整研究文獻，作成客觀性的結論，但不是每一種SR都適合進行MA。簡言之，MA是處理「量性研究的融合」，SR則可包含質性或量性的研究報告。近年來在臺灣實證醫學會的倡導下培育了許多這方面專家，也為藥學界開啟一扇研究大門。為鼓勵及倡導臺灣藥學在SR-MA研究能更積極的投入，在2016 年第十三屆臺灣臨床藥學雜誌的編輯委員會上，通過雜誌投稿領域增設「系統性文獻回顧」的建議，同時廣邀學者專家投稿此領域的綜合性評述或原著文章。初學者在撰寫MA時常無所適從，不知如何進行；本文引用撰寫MA的標準流程—Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA)聲明書並列舉實例，藉此提供有效及可行的方法，讓有心投入者瞭解進行SR-MA 的研究步驟，並順利完成MA 的研究發表。

關鍵字

系統性文獻回顧 ； 統合分析 ； PRISMA聲明書 ； 森林圖 ； 偏誤風險

並列摘要

As research methodology has progressed, systematic review (SR) and meta-analysis (MA) have been used in clinical researches. However, these two items often confuse researchers. Although SR is often used to accumulate research and develop an objective conclusion, not every SR is suitable for MA. In other words, MA is for quantitative research synthesis, whereas SR contains qualitative or quantitative research reports. Recently, the Taiwan Evidence-Based Medicine Association (TEBMA) trained numerous experts in this field and created a research area for pharmacy. To encourage and advocate pharmacist investment in SR-MA research, it was included as a submission field at the twentieth session of the editorial committee of Formosa Journal of Clinical Pharmacy in 2016; experts were invited to submit their articles in this research field. Beginners may not know how to write SR-MA articles at first. Therefore, we adopted the golden standard operation process-the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) statement-and presented some examples for those who were interested in this research field. We hope that this will help researchers publish efficiently.

並列關鍵字

Systematic Review ； Meta-Analysis ； Preferred Reporting Items for Systematic Reviews and Meta-Analysis Statement ； Forest Plot ； Risk of Bias