Table 1 Main characteristics of studies included in meta-analysis
Author (year) | Study region | Recruitment time | Follow-up time | Sample size | Cancer type | Detection method | Detected sample | Cutoff scores (high/low) | Analysis method | OS, HR estimation | Quality score |
|---|---|---|---|---|---|---|---|---|---|---|---|
Atsumi S. (2013) [26] | Japan | NS | 76.5 months (median) | 43 | Soft tissue sarcoma | qRT-PCR | Tissue | Optimal cutoff | Univariate analysis | 0.94 (0.38–2.31) | 7 |
Gong J. (2014) [27] | China | 2008 | 2008–2012 | 96 | Hepatocellular carcinoma | IHC | Tissue | Median | Univariate analysis | 0.9383 (0.8824–0.9977) | 8 |
Qu P. (2015) [28] | China | 2009–2011 | 20 months (median) | 174 | Hepatocellular carcinoma | IHC | Tissue | > 0a | Univariate/multivariate analysis | 0.518 (0.284–0.945) | 8 |
Nishiwada S. (2015) [32] | Japan | 1992–2010 | Until 2014 | 134 | Pancreatic cancer | IHC | Tissue | ≥ ++a | Univariate/multivariate analysis | 1.476 (1.019–2.139) | 8 |
Huang D. W. (2017) [33] | China | 2008–2015 | 19 months (median) | 90 | Cholangiocarcinoma | IHC | Tissue | > 3a | Univariate analysis | 5.443 (2.822–10.498) | 7 |
Stamm H. (2018) [31] | Germany/Australia | NS | NS | 139 | Acute myeloid leukemia | Flow cytometry | Cell lines | Optimal cutoff | Multivariate analysis | 1.52 (1.04–2.23) | 6 |
Stamm H. (2018) [31] | Germany/Australia | NS | NS | 290 | Acute myeloid leukemia | Flow cytometry | Cell lines | Optimal cutoff | Multivariate analysis | 3.39 (1.45–7.94) | 6 |
Zhang J. (2020) [34] | China | 2008–2015 | 45 months (median) | 228 | Bladder cancer | IHC | Tissue | ≥ 2a | Univariate/multivariate analysis | 2.37 (1.6–3.5) | 8 |
Xu Y. (2019) [35] | China | 2008–2014 | Until 2015 | 60 | Lung cancer | IHC | Tissue | Median | Multivariate analysis | 2.4 (1.05–5.5) | 7 |
Sun H. (2019 [29]) | China | 2006–2010 | Around 100 months | 236 | Hepatocellular carcinoma | Flow cytometry | Tissue | Optimal cutoff | Multivariate analysis | 1.61 (1.00–2.61) | 7 |
Yoshida J. (2019) [39] | Japan | 2015–2017 | NS | 47 | Esophageal cancer | ELISA | Serum | Optimal cutoff | Univariate/multivariate analysis | 0.311 (0.068–1.086) | 7 |
Yong H. (2019) [41] | China | 2016–2018 | NS | 216 | Breast cancer | IHC | Tissue | Optimal cutoff | Univariate/multivariate analysis | 2.029 (1.059–3.887) | 7 |
Stamm H. (2019) [42] | Germany | 1991–2002 | NS | 197 | Breast cancer | Flow cytometry | Tissue | Median | Multivariate analysis | 1.822 (1.050–3.161) | 7 |
Sun Y. (2020) [36] | China | NS | NS | 334 | Lung cancer | IHC | Tissue | > 0a | Univariate/multivariate analysis | 1.372 (1.027–1.833) | 6 |
Yao Y. (2020) [45] | China | 2014–2015 | NS | 115 | Head and neck squamous cell carcinoma | IHC | Tissue | Optimal cutoff | Univariate analysis | 1.58 (1.09–2.3) | 7 |
Li Y. C. (2020) [43] | China | 2012–2013 | 75 months (median) | 126 | Breast cancer | IHC | Tissue | ≥ ++a | Univariate/multivariate analysis | 5.47 (1.42–20.99) | 8 |
Wang J. B. (2020) [47] | China | 2010–2014 | More than 5 years | 444 | Gastric cancer | IHC | Tissue | ≥ 4a | Univariate analysis | 1.55 (1.19–2.01) | 7 |
Albrecht T. (2021) [48] | Germany | 1995–2016 | NS | 95 | Gallbladder cancer | IHC | Tissue | Optimal cutoff | Univariate analysis | 2.72 (1.35–5.47) | 6 |
Murakami T. (2021) [49] | Japan | 2004–2014 | NS | 67 | Cervical adenocarcinoma | IHC | Tissue | ≥ ++a | Univariate analysis | 6.39 (2.04–19.98) | 7 |
Yoshikawa K. (2021) [44] | Japan | 2006–2018 | NS | 61 | Breast cancer | IHC | Tissue | ≥ 50a | Univariate analysis | 2.99 (0.6–15.01) | 6 |
Zhao K. (2021) [51] | China | 2006–2018 | Until 2019 | 114 | Esophageal cancer | IHC | Tissue | ≥ 2a | Univariate/multivariate analysis | 1.646 (1.006–2.691) | 7 |
Lee J. B. (2021) [37] | Korea | 1998–2020 | NS | 259 | Lung cancer | IHC | Tissue | Optimal cutoff | Univariate/multivariate analysis | 1.36 (1.01–1.83) | 6 |
Lim S. M. (2021) [46] | Korea | 2005–2012 | NS | 375 | Head and neck squamous cell carcinoma | IHC | Tissue | > 23a | Univariate analysis | 1.4 (1.03–1.90) | 6 |
Oyama R. (2022) [38] | Japan | 2003–2006 | NS | 96 | Lung cancer | IHC | Tissue | Optimal cutoff | Univariate analysis | 3.74 (1.71–8.15) | 8 |
Jin A. L. (2022) [30] | China | 2012–2013 | Until 2018 | 189 | Hepatocellular carcinoma | IHC | Tissue | Optimal cutoff | Univariate/multivariate analysis | 2.87 (1.51–5.45) | 8 |
Murakami D. (2022) [50] | Japan | 2013 | More than 5 years | 100 | Colorectal cancer | IHC | Tissue | ≥ ++a | Univariate analysis | 2.17 (1.12–4.21) | 7 |