细胞游离DNA在胆道癌诊断中的价值：一项meta分析

doi:10.3969/j.issn.1674-8115.2023.09.012

上海交通大学学报（医学版） ›› 2023, Vol. 43 ›› Issue (9): 1175-1185.doi: 10.3969/j.issn.1674-8115.2023.09.012

细胞游离DNA在胆道癌诊断中的价值：一项meta分析

杨越¹^,²(), 何开举³, 宗家豪⁴, 杨自逸¹^,², 吴向嵩¹^,², 龚伟¹^,²()

^1.上海交通大学医学院附属新华医院普外科，上海 200092
^2.上海市胆道疾病研究重点实验室，上海交通大学医学院胆道疾病研究所，上海市胆道疾病研究中心，上海 200092
^3.上海交通大学医学院，上海 200025
^4.山东大学齐鲁医院消化内科，济南 250012

收稿日期:2023-05-30 接受日期:2023-08-22 出版日期:2023-09-28 发布日期:2023-09-28
通讯作者: 龚　伟，电子信箱：gongwei@xinhuamed.com.cn。
作者简介:杨　越（1999—），女，硕士生；电子信箱：yueyueyoung@126.com。
基金资助:
国家自然科学基金(81974371);上海交通大学医学院“双百人”项目(20151001)

Diagnostic value of cell-free DNA to biliary tract cancers: a meta-analysis

YANG Yue¹^,²(), HE Kaiju³, ZONG Jiahao⁴, YANG Ziyi¹^,², WU Xiangsong¹^,², GONG Wei¹^,²()

^1.Department of General Surgery, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200092, China
^2.Shanghai Key Laboratory of Biliary Tract Disease Research, Research Institute of Biliary Tract Disease, Shanghai Jiao Tong University School of Medicine, Shanghai Research Center of Tract Disease, Shanghai 200092, China
^3.Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
^4.Department of Gastroenterology, Qilu Hospital of Shandong University, Jinan 250012, China

Received:2023-05-30 Accepted:2023-08-22 Online:2023-09-28 Published:2023-09-28
Contact: GONG Wei, E-mail: gongwei@xinhuamed.com.cn.
Supported by:
National Natural Science Foundation of China(81974371);“Two-hundred Talents” Program of Shanghai Jiao Tong University School of Medicine(20151001)

摘要/Abstract

摘要：

目的·采用meta分析方法全面评价细胞游离DNA（cell-free DNA，cfDNA）对胆道癌（biliary tract cancer，BTC）的诊断准确性，探究样本来源、检测方法以及截断值选择等对诊断效果的影响，为更好开展临床应用提供依据。方法·检索8个中英文数据库中关于cfDNA对BTC诊断价值的前瞻性或回顾性研究，截止时间为2023年4月。根据纳入和排除标准进行筛选和数据提取，用Spearman秩相关分析评估阈值效应，运用Cochran Q检验、I²检验分析纳入研究间的异质性。拟合双变量混合效应模型，计算总体敏感度、特异度和曲线下面积（area under the curve，AUC）等统计量，判断诊断性能。同时，基于研究类型、样本量大小、检测方式、样本来源和诊断参照标准进行亚组分析。结果·共纳入28项诊断性试验，用诊断性试验准确性质量评价工具2（Diagnostic Accuracy Studies Tool Version 2，QUADAS-2）评价均属于中-高等质量研究，Spearman秩相关分析提示存在阈值效应，合并统计量后求得敏感度（Sen_合并）为0.80（95%CI 0.67~0.88），特异度（Spe_合并）为0.96（95%CI 0.92~0.98），阳性似然比（PLR_合并）为22.7（95%CI 9.4~55.2），阴性似然比（NLR_合并）为0.21（95%CI 0.12~0.36），诊断比数比（DOR_合并）为108（95%CI 31~374）。综合受试者工作特征（summary receiver operating characteristic，SROC）曲线的AUC为0.96（95%CI 0.94~0.98），提示cfDNA对BTC的诊断效能较高。亚组分析结果提示，选择不同的检测方式和样本来源的准确度和敏感度有所不同。结论·cfDNA检测对诊断BTC敏感度和特异度较高，适用于经影像学和常规肿瘤标志物初筛怀疑有恶性风险的患者，但检测方法和样本来源的选择仍需进一步开展面向更广泛人群的临床研究来进一步规范。

关键词: meta分析, 胆道癌, 细胞游离DNA, 诊断

Abstract:

Objective ·To comprehensively evaluate the diagnostic accuracy of cell-free DNA (cfDNA) to biliary tract cancer (BTC), and provide a basis for better clinical application. Methods ·Clinical studies on the diagnostic value of cfDNA to BTC were collected by searching eight databases from inception to April 2023. The studies were selected according to the inclusion and exclusion criteria, and then data was extracted. The threshold effects were assessed with Spearman′s rank correlation analysis, and heterogeneity among the included studies was analyzed by using Cochran′s Q test and I² test. A bivariate mixed-effects model was fitted, and statistics such as overall sensitivity, specificity, and area under the curve (AUC) were calculated to determine the diagnostic performance. The subgroup analyses were carried out based on the study type, sample size, detection method, sample source, and diagnostic reference standard. Results ·A total of 28 diagnosis tests were included, all of which were evaluated as medium-high quality by using Diagnostic Accuracy Studies Tool Version 2 (QUADAS-2). The presence of threshold effects was found by using the Spearman rank correlation analysis. The pooled sensitivity was 0.80 (95%CI 0.67?0.88), and specificity was 0.96 (95%CI 0.92?0.98), positive likelihood ratio (PLR) was 22.7 (95%CI 9.4?55.2), negative likelihood ratio (NLR) was 0.21 (95%CI 0.12?0.36), and diagnostic odds ratio (DOR) was 108 (95%CI 31?374), respectively. The AUC of the summary receiver operating characteristic (SROC) curve was 0.96 (95%CI 0.94?0.98), demonstrating the high accuracy of cfDNA in the diagnosis of BTC. The results of subgroup analyses suggested that the accuracy and sensitivity of choosing different testing methods and sample sources varied. Conclusion ·The detection of cfDNA has high sensitivity and specificity in diagnosing BTC, and is suitable for the patients suspected to be malignant after screening with imaging tests and conventional tumor markers. However, the standardization and uniformity of detection methods and sample sources still need to be further standardized by conducting clinical studies on a wider population.

Key words: meta-analysis, biliary tract cancer (BTC), cell-free DNA (cfDNA), diagnosis

中图分类号:

R735.8

杨越, 何开举, 宗家豪, 杨自逸, 吴向嵩, 龚伟. 细胞游离DNA在胆道癌诊断中的价值：一项meta分析[J]. 上海交通大学学报（医学版）, 2023, 43(9): 1175-1185.

YANG Yue, HE Kaiju, ZONG Jiahao, YANG Ziyi, WU Xiangsong, GONG Wei. Diagnostic value of cell-free DNA to biliary tract cancers: a meta-analysis[J]. Journal of Shanghai Jiao Tong University (Medical Science), 2023, 43(9): 1175-1185.

图/表 13

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Study	Study type	Country	Reference standard
HAN 2021^[25]	Prospective study	South Korea	BTC: pathological examination
HE 2023^[26]	Retrospective and prospective study	China	BTC: pathological examination; BBD: pathological examination and clinical follow-up; healthy population: pathological examination/clinical follow-up
HUA 2021^[27]	Prospective study	China	BTC: pathological examination
KINUGASA 2018^[28]	Prospective study	Japan	Pathological examination
KUMARI 2019^[29]	Retrospective study	India	Imaging/pathological examination
KUMARI 2022^[30]	Retrospective study	India	Imaging/pathological examination
KUMARI 2017^[31]	Retrospective study	India	Imaging/pathological examination
WANG 2021^[32]	Prospective study	China	Pathological examination
WASENANG 2019^[33]	Prospective study	Thailand	BTC: pathological examination
WINTACHAI 2021^[34]	Retrospective study	Thailand	Pathological examination
MO 2020^[35]	Retrospective study	China	BTC/BBD: imaging examination/pathological examination

Study	Study type	Country	Reference standard
HAN 2021^[25]	Prospective study	South Korea	BTC: pathological examination
HE 2023^[26]	Retrospective and prospective study	China	BTC: pathological examination; BBD: pathological examination and clinical follow-up; healthy population: pathological examination/clinical follow-up
HUA 2021^[27]	Prospective study	China	BTC: pathological examination
KINUGASA 2018^[28]	Prospective study	Japan	Pathological examination
KUMARI 2019^[29]	Retrospective study	India	Imaging/pathological examination
KUMARI 2022^[30]	Retrospective study	India	Imaging/pathological examination
KUMARI 2017^[31]	Retrospective study	India	Imaging/pathological examination
WANG 2021^[32]	Prospective study	China	Pathological examination
WASENANG 2019^[33]	Prospective study	Thailand	BTC: pathological examination
WINTACHAI 2021^[34]	Retrospective study	Thailand	Pathological examination
MO 2020^[35]	Retrospective study	China	BTC/BBD: imaging examination/pathological examination

Subgroup	Study/n	Sensitivity (95%CI)	Specificity (95%CI)	PLR	NLR	DOR	AUC (95%CI)
Overall	28	0.80 (0.67‒0.88)	0.96 (0.92‒0.98)	22.7	0.21	108	0.96 (0.94‒0.98)
Study type
Prospective study	16	0.74 (0.51‒0.89)	0.97 (0.93‒0.99)	26.1	0.26	99	0.97 (0.95‒0.98)
Retrospective study	10	0.86 (0.72‒0.93)	0.93 (0.73‒0.99)	12.4	0.15	81	0.95 (0.92‒0.96)
Sample size
>90	12	0.89 (0.78‒0.95)	0.96 (0.83‒0.99)	20.9	0.12	179	0.96 (0.94‒0.98)
≤90	16	0.67 (0.47‒0.83)	0.97 (0.92‒0.99)	23.9	0.34	71	0.96 (0.94‒0.97)
Method
Gene or mutation analysis	6	0.67 (0.44‒0.84)	1.00 (0.85‒1.00)	457.0	0.33	1 394	0.95 (0.93‒0.97)
qPCR	13	0.94 (0.84‒0.98)	0.98 (0.88‒1.00)	38.8	0.06	644	0.99 (0.98‒1.00)
Methylation analysis	9	0.51 (0.37‒0.65)	0.94 (0.82‒0.98)	9.2	0.52	18	0.77 (0.73‒0.81)
Sample type
Bile	4	0.70 (0.53‒0.83)	1.00 (0.67‒1.00)	511.0	0.30	1 690	0.95 (0.92‒0.96)
Serum	19	0.85 (0.66‒0.94)	0.97 (0.90‒0.99)	24.7	0.16	156	0.97 (0.96‒0.99)
Plasma	5	0.72 (0.45‒0.89)	0.92 (0.70‒0.98)	9.4	0.30	31	0.91 (0.88‒0.93)
Control type
Benign biliary disease	18	0.68 (0.54‒0.79)	0.96 (0.92‒0.99)	19.0	0.34	57	0.93 (0.91‒0.95)
Healthy population	6	1.00 (0.70‒1.00)	1.00 (0.90‒1.00)	503.6	0.00	205 953	1.00 (0.99‒1.00)
Reference standard
Pathological examination	4	0.82 (0.69‒0.90)	0.93 (0.60‒0.99)	12.3	0.19	63	0.90 (0.87‒0.93)
Pathological examination in BTC group	16	0.75 (0.52‒0.89)	0.98 (0.94‒0.99)	33.7	0.26	130	0.98 (0.96‒0.99)
Clinical assessment	8	0.87 (0.66‒0.96)	0.95 (0.68‒0.99)	18.2	0.14	129	0.96 (0.94‒0.97)

Subgroup	Study/n	Sensitivity (95%CI)	Specificity (95%CI)	PLR	NLR	DOR	AUC (95%CI)
Overall	28	0.80 (0.67‒0.88)	0.96 (0.92‒0.98)	22.7	0.21	108	0.96 (0.94‒0.98)
Study type
Prospective study	16	0.74 (0.51‒0.89)	0.97 (0.93‒0.99)	26.1	0.26	99	0.97 (0.95‒0.98)
Retrospective study	10	0.86 (0.72‒0.93)	0.93 (0.73‒0.99)	12.4	0.15	81	0.95 (0.92‒0.96)
Sample size
>90	12	0.89 (0.78‒0.95)	0.96 (0.83‒0.99)	20.9	0.12	179	0.96 (0.94‒0.98)
≤90	16	0.67 (0.47‒0.83)	0.97 (0.92‒0.99)	23.9	0.34	71	0.96 (0.94‒0.97)
Method
Gene or mutation analysis	6	0.67 (0.44‒0.84)	1.00 (0.85‒1.00)	457.0	0.33	1 394	0.95 (0.93‒0.97)
qPCR	13	0.94 (0.84‒0.98)	0.98 (0.88‒1.00)	38.8	0.06	644	0.99 (0.98‒1.00)
Methylation analysis	9	0.51 (0.37‒0.65)	0.94 (0.82‒0.98)	9.2	0.52	18	0.77 (0.73‒0.81)
Sample type
Bile	4	0.70 (0.53‒0.83)	1.00 (0.67‒1.00)	511.0	0.30	1 690	0.95 (0.92‒0.96)
Serum	19	0.85 (0.66‒0.94)	0.97 (0.90‒0.99)	24.7	0.16	156	0.97 (0.96‒0.99)
Plasma	5	0.72 (0.45‒0.89)	0.92 (0.70‒0.98)	9.4	0.30	31	0.91 (0.88‒0.93)
Control type
Benign biliary disease	18	0.68 (0.54‒0.79)	0.96 (0.92‒0.99)	19.0	0.34	57	0.93 (0.91‒0.95)
Healthy population	6	1.00 (0.70‒1.00)	1.00 (0.90‒1.00)	503.6	0.00	205 953	1.00 (0.99‒1.00)
Reference standard
Pathological examination	4	0.82 (0.69‒0.90)	0.93 (0.60‒0.99)	12.3	0.19	63	0.90 (0.87‒0.93)
Pathological examination in BTC group	16	0.75 (0.52‒0.89)	0.98 (0.94‒0.99)	33.7	0.26	130	0.98 (0.96‒0.99)
Clinical assessment	8	0.87 (0.66‒0.96)	0.95 (0.68‒0.99)	18.2	0.14	129	0.96 (0.94‒0.97)

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细胞游离DNA在胆道癌诊断中的价值：一项meta分析

Diagnostic value of cell-free DNA to biliary tract cancers: a meta-analysis

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Metrics

Study	Sample	Method	Sample size/n	Cut off	TP/n	FP/n	FN/n	TN/n
HAN 2021^[25]	Bile	ddPCR	46	1 500 copies·mL^-1	20	0	22	4
HAN 2021^[25]	Plasma	ddPCR	20	60 copies·mL^-1	3	0	13	4
HE 2023^[26]	Bile	qPCR	188	NA	74	0	21	93
HE 2023^[26]	Bile	NGS	188	NA	80	2	15	91
HUA 2021^[27]	Serum	qPCR	158	403.65 ng·mL^-1	78	2	5	73
	Serum	qPCR	153	113.82 ng·mL^-1	83	0	0	70
	Serum	qPCR	158	364 ng·mL^-1	76	7	7	68
	Serum	qPCR	153	96 ng·mL^-1	83	0	0	70
KINUGASA 2018^[28]	Bile	NGS	43	NA	14	0	10	19
KUMARI 2019^[29]	Serum	qPCR	96	406.582 5 ng·mL^-1	48	5	12	31
	Serum	qPCR	96	1 128.429 ng·mL^-1	43	12	17	24
	Serum	qPCR	96	cfDNA integrity index: 0.356	47	7	13	29
	Serum	Methylated DNA Quantification Kit	96	Global DNA methylation: 0.713 5	33	18	27	18
KUMARI 2022^[30]	Serum	qPCR	75	251.2 ng·mL^-1	50	0	0	25
KUMARI 2017^[31]	Serum	qPCR	56	372.92 ng·mL^-1	30	0	4	22
KUMARI 2017^[31]	Serum	qPCR	51	218.55 ng·mL^-1	34	0	0	17
WANG 2021^[32]	Plasma	Low-coverage WGS	47	\|Z\|-score in UCAD test 2.32	26	2	3	16
WASENANG 2019^[33]	Serum	MSP	80	OPCML 3.24%‒50% methylation	32	4	8	36
	Serum	MSP	80	HOXD9 1.56%‒50% methylation	27	4	13	36
	Serum	MSP	80	HOXA9 1.56%‒50% methylation	19	15	21	25
	Serum	MSP	80	OPCML, HOXD9 both methylated	25	0	15	40
	Serum	MSP	80	OPCML, HOXA9 both methylated	12	1	28	39
	Serum	MSP	80	HOXA9, HOXD9 both methylated	10	1	30	39
	Serum	MSP	80	OPCML, HOXA9, HOXD9 ≥2 markers methylated	29	2	11	38
	Serum	MSP	80	OPCML, HOXA9, HOXD9 all methylated	9	0	31	40
WINTACHAI 2021^[34]	Plasma	qPCR	92	0.217 5 ng·µL^-1	55	1	7	29
WINTACHAI 2021^[34]	Plasma	qPCR	95	0.338 8 ng·µL^-1	51	14	11	19
MO 2020^[35]	Plasma	qPCR	85	18.06 ng·µL^-1	26	2	19	38