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
• 论著 · 循证医学 • 上一篇
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()
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
E-mail:yueyueyoung@126.com;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:
YANG Yue1,2(), HE Kaiju3, ZONG Jiahao4, YANG Ziyi1,2, WU Xiangsong1,2, GONG Wei1,2()
Received:
2023-05-30
Accepted:
2023-08-22
Online:
2023-09-28
Published:
2023-09-28
Contact:
GONG Wei
E-mail:yueyueyoung@126.com;gongwei@xinhuamed.com.cn
Supported by:
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。
中图分类号:
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.
Study | Study type | Country | Reference standard |
---|---|---|---|
HAN 2021[ | Prospective study | South Korea | BTC: pathological examination |
HE 2023[ | Retrospective and prospective study | China | BTC: pathological examination; BBD: pathological examination and clinical follow-up; healthy population: pathological examination/clinical follow-up |
HUA 2021[ | Prospective study | China | BTC: pathological examination |
KINUGASA 2018[ | Prospective study | Japan | Pathological examination |
KUMARI 2019[ | Retrospective study | India | Imaging/pathological examination |
KUMARI 2022[ | Retrospective study | India | Imaging/pathological examination |
KUMARI 2017[ | Retrospective study | India | Imaging/pathological examination |
WANG 2021[ | Prospective study | China | Pathological examination |
WASENANG 2019[ | Prospective study | Thailand | BTC: pathological examination |
WINTACHAI 2021[ | Retrospective study | Thailand | Pathological examination |
MO 2020[ | Retrospective study | China | BTC/BBD: imaging examination/pathological examination |
表1 纳入研究基本信息表
Tab 1 Basic characteristics of the included studies
Study | Study type | Country | Reference standard |
---|---|---|---|
HAN 2021[ | Prospective study | South Korea | BTC: pathological examination |
HE 2023[ | Retrospective and prospective study | China | BTC: pathological examination; BBD: pathological examination and clinical follow-up; healthy population: pathological examination/clinical follow-up |
HUA 2021[ | Prospective study | China | BTC: pathological examination |
KINUGASA 2018[ | Prospective study | Japan | Pathological examination |
KUMARI 2019[ | Retrospective study | India | Imaging/pathological examination |
KUMARI 2022[ | Retrospective study | India | Imaging/pathological examination |
KUMARI 2017[ | Retrospective study | India | Imaging/pathological examination |
WANG 2021[ | Prospective study | China | Pathological examination |
WASENANG 2019[ | Prospective study | Thailand | BTC: pathological examination |
WINTACHAI 2021[ | Retrospective study | Thailand | Pathological examination |
MO 2020[ | Retrospective study | China | BTC/BBD: imaging examination/pathological examination |
Study | Sample | Method | Sample size/n | Cut off | TP/n | FP/n | FN/n | TN/n |
---|---|---|---|---|---|---|---|---|
HAN 2021[ | Bile | ddPCR | 46 | 1 500 copies·mL-1 | 20 | 0 | 22 | 4 |
Plasma | ddPCR | 20 | 60 copies·mL-1 | 3 | 0 | 13 | 4 | |
HE 2023[ | Bile | qPCR | 188 | NA | 74 | 0 | 21 | 93 |
Bile | NGS | 188 | NA | 80 | 2 | 15 | 91 | |
HUA 2021[ | 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[ | Bile | NGS | 43 | NA | 14 | 0 | 10 | 19 |
KUMARI 2019[ | 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[ | Serum | qPCR | 75 | 251.2 ng·mL-1 | 50 | 0 | 0 | 25 |
KUMARI 2017[ | Serum | qPCR | 56 | 372.92 ng·mL-1 | 30 | 0 | 4 | 22 |
Serum | qPCR | 51 | 218.55 ng·mL-1 | 34 | 0 | 0 | 17 | |
WANG 2021[ | Plasma | Low-coverage WGS | 47 | |Z|-score in UCAD test 2.32 | 26 | 2 | 3 | 16 |
WASENANG 2019[ | 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[ | Plasma | qPCR | 92 | 0.217 5 ng·µL-1 | 55 | 1 | 7 | 29 |
Plasma | qPCR | 95 | 0.338 8 ng·µL-1 | 51 | 14 | 11 | 19 | |
MO 2020[ | Plasma | qPCR | 85 | 18.06 ng·µL-1 | 26 | 2 | 19 | 38 |
表2 纳入研究数据提取
Tab 2 Collected data of the included studies
Study | Sample | Method | Sample size/n | Cut off | TP/n | FP/n | FN/n | TN/n |
---|---|---|---|---|---|---|---|---|
HAN 2021[ | Bile | ddPCR | 46 | 1 500 copies·mL-1 | 20 | 0 | 22 | 4 |
Plasma | ddPCR | 20 | 60 copies·mL-1 | 3 | 0 | 13 | 4 | |
HE 2023[ | Bile | qPCR | 188 | NA | 74 | 0 | 21 | 93 |
Bile | NGS | 188 | NA | 80 | 2 | 15 | 91 | |
HUA 2021[ | 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[ | Bile | NGS | 43 | NA | 14 | 0 | 10 | 19 |
KUMARI 2019[ | 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[ | Serum | qPCR | 75 | 251.2 ng·mL-1 | 50 | 0 | 0 | 25 |
KUMARI 2017[ | Serum | qPCR | 56 | 372.92 ng·mL-1 | 30 | 0 | 4 | 22 |
Serum | qPCR | 51 | 218.55 ng·mL-1 | 34 | 0 | 0 | 17 | |
WANG 2021[ | Plasma | Low-coverage WGS | 47 | |Z|-score in UCAD test 2.32 | 26 | 2 | 3 | 16 |
WASENANG 2019[ | 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[ | Plasma | qPCR | 92 | 0.217 5 ng·µL-1 | 55 | 1 | 7 | 29 |
Plasma | qPCR | 95 | 0.338 8 ng·µL-1 | 51 | 14 | 11 | 19 | |
MO 2020[ | Plasma | qPCR | 85 | 18.06 ng·µL-1 | 26 | 2 | 19 | 38 |
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) |
表3 亚组分析
Tab 3 Subgroup analysis
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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