Chinese Medical Sciences Journal ›› 2020, Vol. 35 ›› Issue (3): 262-271.doi: 10.24920/003668
收稿日期:
2020-01-08
出版日期:
2020-09-30
发布日期:
2020-09-25
通讯作者:
张玉石
E-mail:beijingzhangyushi@126.com
Wang Zhan,Wang Xu,Wang Wenda,Zheng Guoyang,Guo Hao,Zhang Yushi()
Received:
2020-01-08
Published:
2020-09-30
Online:
2020-09-25
Contact:
Zhang Yushi
E-mail:beijingzhangyushi@126.com
摘要:
目的 术前中性粒细胞与淋巴细胞比值(NLR)与多种恶性肿瘤的预后密切相关,但是,NLR对可切除泌尿系肿瘤预后的影响尚不确定。因此,此系统综述和荟萃分析旨在探讨术前NLR在预测可切除泌尿系肿瘤预后方面的价值。
方法 我们通过检索Embase、PubMed/MEDLINE和Cochrane数据库,依据纳入和排除标准筛选文献,最终纳入25项研究,其中包括15950例受试对象。采用风险比(HRs)及其95%可信区间(CIs)评估术前NLR与可切除泌尿系肿瘤患者的总生存期(OS)及肿瘤特异性生存期(CSS)的关系。
结果 结果表明对于患有可切除泌尿系恶性肿瘤的患者,术前NLR能预测其预后。NLR越高,患者的OS(HR=1.40,95%CI:1.26~1.54,P<0.001)和CSS越短(HR=1.43,95%CI:1.27~1.59,P<0.001)。此外,不论患者种族或术前NLR阈值高低,术前NLR升高均能提示肾细胞癌(OS:HR=2.06,95%CI=1.54~2.76,P=0.131;CSS:HR=2.46,95%CI=1.46~4.16,P=0.178)、上尿路上皮癌(OS:HR=1.91,95%CI=1.50~2.42,P=0.616;CSS:HR=1.84,95%CI=1.41~2.39,P=0.001)、膀胱癌(OS:HR=1.09,95%CI=1.02~1.17,P<0.001;CSS:HR=1.05,95%CI=1.01~1.09,P=0.163)和前列腺癌(OS:HR=1.69,95%CI=1.19~2.41,P=0.714)预后较差。
结论 术前NLR升高能够作为预测泌尿系可切除恶性肿瘤不良预后的指标,包括肾癌、膀胱癌、前列腺癌和上尿路上皮癌。
Wang Zhan, Wang Xu, Wang Wenda, Zheng Guoyang, Guo Hao, Zhang Yushi. Value of Preoperative Neutrophil-to-Lymphocyte Ratio in Predicting Prognosis of Surgically Resectable Urinary Cancers: Systematic Review and Meta-Analysis[J].Chinese Medical Sciences Journal, 2020, 35(3): 262-271.
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Author | Year | Country | Tumor type | No. of Patients | Age (yrs) | Gender (M:F) | Cut-off value | Follow-up (months) | Outcomes | Analysis type |
---|---|---|---|---|---|---|---|---|---|---|
Son et al.[ | 2018 | Korea | UTUC | 1137 | 69 (61-74)* | 825:312 | 3.3 | 39.1 (18.3-63.8)* | RFS, CSS | UV, MV |
Azuma et al.[ | 2013 | Japan | UTUC | 137 | 69.4 (40-88) | 106:31 | 2.5 | 60.9 (1.9-187.3) | RFS, CSS | UV, MV |
Kohada et al.[ | 2018 | Japan | UTUC | 148 | 71 (64-78)* | 112:36 | 3 | 35.5 (12-66)* | RFS, CSS | UV, MV |
Tanaka et al.[ | 2014 | Japan | UTUC | 665 | 70 (62-76)* | 493:172 | 3 | 28 (14-57)* | RFS, CSS | UV, MV |
Cao et al.[ | 2017 | China | UTUC | 656 | 68 (39-88) | 290:366 | 2.4 | 46 (12-144) | IVRFS, CSS | UV, MV |
Cheng et al.[ | 2016 | China | UTUC | 195 | 68±10.3 | 79:116 | 2.7 | 36 | OS, CSS | UV, MV |
Luo et al.[ | 2014 | China | UTUC | 234 | N | 102:132 | 3 | 40.7±23.8 | MFS, CSS | UV, MV |
Tan et al.[ | 2018 | China | UTUC | 717 | 67 (59-74)* | 408:309 | 2.5 | 42 (18-76)* | OS, DFS, CSS, MFS | MV |
Dalpiaz et al.[ | 2014 | Austria | UTUC | 202 | 69.3 (32-85) | 122:80 | 2.7 | 45 (0-199) | CSS, OS | UV, MV |
Vartolomei et al.[ | 2017 | Austria | UTUC | 2274 | 69 (61-76) | 1527:747 | 2.7 | 40 (20-76) | RFS, CSS | UV, MV |
Byun et al.[ | 2016 | Korea | RCC | 1284 | 55.9±12.9 | 913:371 | 3.7 | 39 (19-69)* | RFS, CSS | MV |
Widz et al.[ | 2020 | Poland | RCC | 196 | 61 (24-85)* | 116:80 | 2.69 | 68 (44.5-78) | OS | UV, MV |
Agizamhann et al.[ | 2018 | China | RCC | 82 | 37 (2-71) | 33:49 | 2.45 | 31 (2-108) | OS, DFS | UV, MV |
Chen et al.[ | 2019 | China | RCC | 414 | 56.3 (24-80) | 257:157 | 2.17 | 69.2 (1-151) | OS, CSS | MV |
Wen et al.[ | 2015 | China | RCC | 327 | 56 (3-86) | 211:116 | 1.7 | 43 (0-97) | OS, DFS | UV, MV |
Hu et al.[ | 2017 | China | RCC | 484 | 56 (21-81) | 278:206 | 2.78 | 36 | OS | UV, MV |
Gu et al.[ | 2016 | China | RCC | 103 | 56 (16-79) | 71:32 | 4.1 | 19.9 (10.8-35.1)* | OS | UV, MV |
Pichler et al.[ | 2013 | Austria | RCC | 678 | N | N | 3.3 | 44 (0-130) | OS, CSS | UV, MV |
Jang et al.[ | 2016 | Korea | Pca | 2067 | 66 (61-70) | N | 1.76 | 78 (65-6)* | BCRFS, CSS, OS | UV, MV |
Sun et al.[ | 2018 | China | Pca | 226 | N | N | 2.31 | 24 (1-73) | OS, DFS | UV, MV |
Viers et al.[ | 2014 | USA | Bca | 899 | 69 (62-76)* | 723:176 | 2.7 | 130.8 (99.6-166.8)* | DFS, CSS, OS | UV, MV |
Tan et al.[ | 2017 | Singapore | Bca | 84 | 67 (37-82) | 63:21 | 2.7 | 30.1 (3.2-161.7) | DFS, OS | UV, MV |
Kang et al.[ | 2017 | Korea | Bca | 1551 | 65 (57-72)* | 1302:249 | 2 | 52 (27-82)* | OS | UV, MV |
Rajwa et al.[ | 2018 | Poland | Bca | 144 | N | N | 3 | 14 (7-40)* | OS, CSS | UV, MV |
Vartolomei et al.[ | 2018 | Italy | Bca | 1046 | 70 (29-91) | 864:182 | 3 | 26 (10-47)* | OS, DFS, CSS | MV |
"
Subgroups | No. of studies | No. of patients | HR | 95%CI | Pheterogeneity |
---|---|---|---|---|---|
Tumor type | |||||
RCC | 7 | 2284 | 2.06 | 1.54-2.76 | 0.131 |
UTUC | 3 | 1114 | 1.91 | 1.50-2.42 | 0.616 |
Bca | 5 | 3724 | 1.09 | 1.02-1.17 | <0.001 |
Pca | 2 | 2293 | 1.69 | 1.19-2.41 | 0.714 |
Ethnicity | |||||
Asian | 11 | 3165 | 1.89 | 1.58-2.25 | 0.203 |
Caucasian | 6 | 6250 | 1.09 | 1.02-1.16 | 0.001 |
Cut-off value | |||||
< 2.7 | 8 | 5580 | 1.77 | 1.49-2.11 | 0.268 |
≥2.7 | 9 | 3835 | 1.15 | 1.05-1.26 | <0.001 |
Overall | 17 | 9415 | 1.40 | 1.26-1.54 | <0.001 |
"
Subgroups | No. of studies | No. of patients | HR | 95%CI | Pheterogeneity |
---|---|---|---|---|---|
Tumor type | |||||
RCC | 3 | 2376 | 2.46 | 1.46-4.16 | 0.178 |
UTUC | 10 | 6365 | 1.84 | 1.41-2.39 | 0.001 |
Bca | 3 | 2089 | 1.05 | 1.01-1.09 | 0.163 |
Pca | 1 | 2067 | * | * | * |
Ethnicity | |||||
Asian | 11 | 7654 | 2.02 | 1.67-2.44 | 0.185 |
Caucasian | 6 | 5243 | 1.06 | 1.00-1.12 | 0.049 |
Cut-off value | |||||
< 2.7 | 5 | 3991 | 2.10 | 1.68-2.61 | 0.349 |
≥2.7 | 12 | 8906 | 1.19 | 1.08-1.31 | <0.001 |
Overall | 17 | 12897 | 1.43 | 1.27-1.59 | <0.001 |
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