혈청 진단 바이오 마커 연구에서 체계적 문헌고찰 및 메타분석의 효용성 연구 : 허혈성 뇌졸중 중심으로 = A study on the efficacy of a systematic review and meta-analysis in serum diagnostic biomarker: focusing on ischemic stroke

국문 초록 (Abstract)

뇌졸중은 전세계적으로 성인의 주요 사망원인 중 하나이며 허혈성 뇌졸중은 뇌졸중에서 가장 발생률이 높고, 진단 시간이 지연됨에 따라 예후의 불량률도 동시에 증가하므로 최대한 빠른 시간 내에 조기 진단이 가능한 혈청 바이오 마커 발굴이 시급하다. 따라서, 이에 대한 연구로 체계적 문헌고찰 및 메타분석의 통계 문헌적 방법으로 접근하였다. 체계적 문헌고찰 방법은 객관적인 연구 기준으로 선행 연구의 결과 데이터를 종합 정리 고찰하는 방법이며 일반적으로 메타분석도 병행한다.
메타분석이란 선행 연구 문헌에서 추출한 다수의 공통된 데이터로부터 통계분석하여 정량적인 좁합적인 유의한 효과 추정치 결과를 도출하는 것을 말한다. 메타분석에 사용되는 효과크기의 유형은 주로 승산비 (odds ratio, OR), 상관계수 (correlation coefficient, r), 곡선 아래 면적 (area under curve, AUC)이 있다. 학술 데이터베이스 검색은 PubMed, EMBASE 그리고 Cochrane library 3가지를 객관적인 기준으로 문헌 검색을 하였고, 모든 추출된 데이터는 허혈성 뇌졸중 환자 대상의 결과만으로 제한하였으며 승산비, 상관계수, 곡선 아래 면적의 결과와 각 95% 신뢰구간의 하한값과 상한값을 각각 추출하였다. 1차적으로 체계적 문헌 고찰 방법으로 허혈성 뇌졸중을 조기 진단하는 혈청 진단 바이오 마커들을 정리한 결과 심장질환과 관련된 BNP, Copeptin, SCUBE1, TnI, 세포 이상과 염증관 관련된 Calprotectin, NSE, 허혈성과 관련된 GPBB, NR2, 뇌혈관질환과 관련된 sLox-1, Tissue kallikrein, suPAR-3, S100B로 도출되었다. 2차적으로 체계적 문헌고찰로 도출된 허혈성 뇌졸중 조기 진단 혈청 진단 바이오 마커들 중 효과크기 곡선 아래 면적으로 추출되고, 3개 이상의 동종 마커로 조사된 Copeptin과 S100B의 메타분석을 진행하기 위해 문헌 질 평가를 진행하였고, Copeptin의 곡선 아래 면적 데이터는 4개, S100B의 데이터는 2개로 메타분석을 진행하였다. Copeptin의 종합적인 효과크기는 0.792 (0.690~0.894), S100B의 전체 효과크기는 0.661 (0.370~0.953)으로 나타났다. 허혈성 뇌졸중을 조기 진단하는 혈청 진단 바이오 마커를 체계적 문헌고찰로 검증은 가능하였으나 실제 추출된 데이터의 정보 부족으로 인해 이론적인 메타분석만 가능하였다. 진단분야에서 혈청 진단 바이오 마커의 효과적인 메타분석이 가능하려면 보다 많은 진단 바이오 마커들의 개별 선행 연구와 각 논문들의 통일성 있는 효과크기 표기 방식이 선행되어야 할 것이다.

다국어 초록 (Multilingual Abstract)

Stroke is one of the leading causes of death in adults worldwide, and ischemic stroke is the most common cause of stroke, and the prognosis defect rate increases as the diagnosis time are delayed. Therefore, as a study of this, we approached it in a statistical method of systematic literature consideration and meta-analyzing. A systematic literature review method is a method for a comprehensive review of the results data of previous studies based on objective research standards. Generally, meta-analyzing is also performed in parallel.
Meta-Analysis is the statistical analysis of several common data extracted from the prior research literature to derive quantitative, narrow, and significant effect estimates. The types of effects used for meta-analyzing are mainly odds ratio (OR), correlation coefficient (r), and area under the curve (AUC). In the academic database search, PubMed, EMBASE, and Cochrane library were searched objectively, and all extracted data were limited to ischemic stroke patients' results. The lower and upper limits of each 95% confidence interval were extracted. A serum diagnostic biomarker for early diagnosis of ischemic stroke is organized as a primary systematic literature study method, and BNP, Copeptin, SCUBE1, TnI, Calprotectin, NSE, ischemic, GPBB, NR2, and sLox-1, Tissue kallikrein, suPAR-3, and S100B are derived. Among ischemic stroke early diagnosis serum diagnostic biomarkers derived from the second systematic literature study, literature quality evaluation was performed to proceed with the meta-analyzing of Copeptin and S100B, which were extracted to the area under the effect size curve.
The overall effect of Copeptin was 0.792 (0.690-0.894), and the overall effect of S100B was 0.661 (0.370-0.953). Although the early diagnostic biomarker of ischemic stroke could be verified by systematic literature review, only theoretical meta-analyzes were possible due to more information on the extracted data. For effective meta-analyzing of serum diagnostic biomarkers in the diagnostic field, more individual prior studies of diagnostic biomarkers and a uniform effect-size notation of each paper will have to precede.

목차 (Table of Contents)

• 국문요지 = i
• 차례 = iii
• 연구배경 = 1
• Part 1. 체계적 문헌 고찰에서 허혈성 뇌졸중의 혈청 진단 바이오 마커 효과 크기에서의 승산비와 상관계수, 곡선 아래 면적값의 효용성 연구 = 19
• Part 1-I. 방법 = 19
• Part 1-II. 결과 = 21
• Part 1-III. 고찰 = 33
• Part 1-IV. 결론 = 39
• Part 2. 허혈성 뇌졸중의 혈청 진단 바이오 마커에 대한 메타분석 연구 = 41
• Part 2-I. 방법 = 41
• Part 2-II. 결과 = 44
• Part 2-III. 고찰 = 56
• Part 2-IV. 결론 = 58
• 참고문헌 = 59
• 부록 = 63
• Abstract = 116

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