The Indirect Efficacy Comparison of DNA Methylation in Sputum for Early Screening and Auxiliary Detection of Lung Cancer: A Meta-Analysis
Abstract
:1. Introduction
2. Materials and Methods
2.1. Search Strategy
2.2. Inclusion Criteria and Exclusion Criteria
2.3. Data Extraction and Quality Assessment
2.4. Statistical Analysis
3. Results
3.1. Subsection
3.1.1. Study Characteristics and Quality of Included Studies
3.1.2. Summary Performance of Diagnostic Estimates
3.1.3. Indirect Comparisons of Diagnostic Analysis
3.1.4. Test of Heterogeneity and Meta-Regression
4. Discussion
5. Conclusions
Supplementary Materials
Acknowledgments
Author Contributions
Conflicts of Interest
References
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Study/Year | Country | Cases/Controls | Biomarkers | STARD | QUADAS |
---|---|---|---|---|---|
Destro/2004 [41] | Italy | 24/100 | p16 | 21 | 12 |
Zhang/2004 [48] | China | 44/20 | p16 | 18 | 8 |
Wang/2004 [57] | China | 34/21 | p16 | 17 | 7 |
Konno/2004 [31] | Japan | 78/94 | p16, APC, RARβ | 20 | 11 |
Belinsky/2005 [39] | USA | 53/118 | p16, MGMT, RASSF1A, DAP, H-cadherin, PAX5 | 20 | 9 |
Olaussen/2005 [32] | France | 20/17 | HOXA9, p16, MAGE | 17 | 8 |
Cirincione/2006 [44] | Italy | 18/112 | RARβ, p16, RASSF1A | 15 | 7 |
Wang/2006 [45] | China | 79/22 | FHIT, p16, RARβ | 20 | 10 |
Liu/2006 [54] | China | 77/30 | MGMT | 18 | 8 |
Belinsky/2006 [47] | USA | 98/92 | p16, PAX5, MGMT, DAPK, GATA, RASSF1ASFRP1, HLHPBETA3, IGFBP3HCAD, LAMC2 | 20 | 10 |
Georgiou/2007 [30] | Greece | 80/40 | p16 | 16 | 9 |
Hsu/2007 [5] | China | 82/37 | p16, RARβ | 16 | 7 |
Liu/2008 [29] | China | 58/107 | p16 | 18 | 10 |
Guo/2008 [53] | China | 100/50 | p16 | 16 | 7 |
Van der Drift/2008 [33] | Netherlands | 28/68 | RASSF1A | 19 | 11 |
Hu/2009 [51] | China | 42/25 | p16 | 16 | 9 |
Ye/2010 [49] | China | 30/27 | RASSF1A | 16 | 7 |
Zhang/2010 [49] | China | 82/25 | RASSF1A, p16, DAPK | 18 | 8 |
Hwang/2011 [36] | Korea | 76/109 | HOXA | 20 | 9 |
Song/2011 [28] | China | 42/9 | p16, MGMT | 17 | 8 |
Zhang/2011 [52] | China | 41/15 | p16 | 17 | 9 |
Hang/2011 [38] | China | 47/24 | FHIT | 20 | 8 |
Sun/2012 [55] | China | 120/120 | p16, RASSF1A | 19 | 7 |
Hubers/2012 [46] | The Netherlands | 53/47 | RASSF1A, APC, CYGB | 18 | 10 |
Guzmán/2012 [14] | Chile | 26/33 | p16, CDH1, MGMT | 18 | 11 |
Shin/2012 [42] | Korea | 65/30 | MAGE, p16 | 17 | 9 |
Leng/2012 [35] | USA | 64/64 | p16, MGMT, DAPK, PAX5, GATA, Dal-1, PCDH20, Jph3, Kifla, SULF2, RASSFlA, GATA, Dab2, Dcr2, RASSF2, TCF2l | 20 | 11 |
Leng/2012 [35] | USA | 40/90 | p16, MGMT, DAPK, PAX5, GATA, Dal-1, PCDH20, Jph3, Kifla, SULF2, CXCL, RASSFlA, Dab2, Dcr2, RASSF2, TCF2l | 20 | 11 |
Pan/2013 [56] | China | 20/13 | p16 | 19 | 8 |
Hubers/2014 [34] | The Netherlands | 20/31 | RASSF1A, APC, CYGB, 3OST, PRDM14, FAM19A4, PHACTR3 | 19 | 8 |
Hubers/2014 [43] | The Netherlands | 98/90 | RASSF1A, APC, CYGB | 20 | 10 |
Hubers/2014 [43] | The Netherlands | 60/445 | RASSF1A, APC, CYGB | 20 | 10 |
Hubers/2015 [58] | The Netherlands | 73/86 | RASSF1A, APC, CYGB, 3OST2, PRDM14, FAM19A4, PHACTR3 | 21 | 11 |
Hubers/2015 [58] | The Netherlands | 159/154 | RASSF1A, APC, CYGB, 3OST2, PRDM14, FAM19A4, PHACTR3 | 21 | 11 |
Su/2016 [40] | China | 117/174 | RASSF1A, 3OST2, PRDM14 | 18 | 7 |
Hulbert/2016 [37] | USA | 90/24 | SOX17, TAC1, CDO1, HOXA, ZFP42 | 16 | 9 |
Genes | Study-Case/Control | SEN (95% CI) | SPE (95% CI) | PLR (95% CI) | NLR (95% CI) | DOR (95% CI) |
---|---|---|---|---|---|---|
CDH1 | 1–26/33 | 0.35 (0.17–0.56) | 0.70 (0.51–0.84) | 1.14 (0.55–2.39) | 0.94 (0.66–1.00) | 1.22 (0.41–3.65) |
SOX17 | 1–90/24 | 0.84 (0.75–0.91 | 0.88 (0.68–0.97) | 6.76 (2.34–19.54) | 0.18 (0.11–0.29) | 38.00 (9.98–144.73) |
CDO1 | 1–90/24 | 0.78 (0.68–0.86) | 0.67 (0.45–0.84) | 2.32 (1.31–4.15) | 0.33 (0.21–0.54) | 7.00 (2.62–18.72) |
ZFP42 | 1–90/24 | 0.87 (0.78–0.93) | 0.63 (0.41–0.81) | 2.31 (1.37–3.90) | 0.21 (0.12–0.39) | 10.83 (3.88–30.22 |
TAC1 | 1–90/24 | 0.86 (0.77–0.92) | 0.75 (0.53–0.90) | 3.42 (1.70–6.88) | 0.19 (0.11–0.33) | 17.77 (5.94–53.12) |
H-cadherin | 1–53/118 | 0.50 (0.23–0.77) | 0.57 (0.46–0.68) | 1.18 (0.66–2.11) | 0.87 (0.50–1.00) | 1.35 (0.43–4.22) |
FHIT | 2–126/46 | 0.52 (0.43–0.61) | 0.91 (0.79–0.98) | 5.93 (2.29–15.36) | 0.53 (0.43–0.65) | 11.19 (3.79–33.06) |
PCDH20 | 2–104/154 | 0.58 (0.48–0.67) | 0.49 (0.41–0.58) | 1.14 (0.91–1.43) | 0.86 (0.65–1.00) | 1.33 (0.80–2.19) |
Dab2 | 2–104/154 | 0.03 (0.01–0.08) | 0.99 (0.95–1.00) | 2.22 (0.38–13.06) | 0.98 (0.95–1.00) | 2.26 (0.37–13.75) |
Dcr2 | 2–104/154 | 0.41 (0.32–0.51) | 0.60 (0.52–0.68) | 1.03 (0.76–1.38) | 0.98 (0.80–1.00) | 1.05 (0.63–1.73) |
SULF2 | 2–104/154 | 0.51 (0.41–0.61) | 0.57 (0.49–0.65) | 1.19 (0.91–1.55) | 0.86 (0.68–1.00) | 1.39 (0.84–2.28) |
Kifla | 2–104/154 | 0.44 (0.34–0.54 | 0.62 (0.54–0.70 | 1.17 (0.87–1.58) | 0.89 (0.72–1.00) | 1.31 (0.79–2.18) |
Dal-1 | 2–104/154 | 0.30 (0.21–0.39 | 0.86 (0.80–0.91 | 2.17 (1.32–3.55) | 0.82 (0.71–0.94) | 2.65 (1.42–4.94) |
Jph3 | 2–104/154 | 0.31 (0.23–0.41 | 0.79 (0.721–0.85 | 1.47 (0.97–2.22) | 0.87 (0.75–1.00) | 1.68 (0.96–2.95) |
RASSF2 | 2–104/154 | 0.08 (0.03–0.15) | 0.95 (0.91–0.98) | 1.69 (0.63–4.52) | 0.97 (0.91–1.00) | 1.75 (0.61–4.98) |
TCF2l | 2–104/154 | 0.29 (0.20–0.39) | 0.71 (0.63–0.78) | 0.99 (0.67–1.46) | 1.01 (0.86–1.00) | 0.98 (0.57–1.70) |
CXCL | 2–80/180 | 0.36 (0.26–0.48 | 0.79 (0.72–0.85 | 1.72 (1.15–2.58) | 0.81 (0.67–0.97) | 2.12 (1.19–23.79) |
MAGE | 4–202/118 | 0.45 (0.34–0.55 | 0.82 (0.56–0.94 | 2.44 (0.75–7.96 | 0.68 (0.47–0.99 | 3.60 (0.76–16.98 |
HOXA | 4–276/174 | 0.79 (0.63–0.89) | 0.50 (0.16–0.84) | 1.56 (0.80–3.07) | 0.43 (0.28–0.66) | 3.63 (1.28–10.26) |
RARβ | 4–257/223 | 0.44 (0.29–0.60) | 0.79 (0.58–0.91) | 2.09 (0.93–4.70) | 0.71 (0.52–0.98) | 2.93 (0.99–8.69) |
FAM19A4 | 3–252/271 | 0.80 (0.74–0.85 | 0.25 (0.20–0.30) | 1.06 (0.97–1.16) | 0.82 (0.59–1.00) | 1.29 (0.86–1.96) |
PHACTR3 | 3–252/271 | 0.60 (0.53–0.66 | 0.68 (0.62–0.73) | 1.85 (1.52–2.27) | 0.60 (0.50–0.71) | 3.11 (2.17–4.45) |
DAPK | 5–337/389 | 0.45 (0.40–0.51) | 0.79 (0.64–0.89) | 2.16 (1.13–4.14) | 0.69 (0.58–0.86) | 3.12 (1.32–7.36) |
3OST2 | 4–369/445 | 0.50 (0.45–0.55) | 0.85 (0.82–0.88) | 3.36 (2.63–4.30) | 0.59 (0.53–0.66) | 5.71 (4.10–7.96) |
PRDM14 | 4–369/445 | 0.62 (0.57–0.67) | 0.76 (0.72–0.80) | 2.63 (2.19–3.17) | 0.50 (0.43–0.57) | 5.30 (3.91–7.17) |
GATA | 6–404/492 | 0.66 (0.31–0.90) | 0.53 (0.33–0.71) | 1.40 (1.16–1.69) | 0.64 (0.34–1.21) | 2.20 (1.01–4.83) |
MGMT | 8–447/460 | 0.42 (0.32–0.52) | 0.91 (0.77–0.97) | 4.78 (1.47–15.55) | 0.64 (0.50–0.81) | 7.48 (1.87–29.91) |
PAX5 | 8–510/728 | 0.37 (0.29–0.45) | 0.78 (0.70–0.84) | 1.65 (1.28–2.12) | 0.81 (0.74–0.90) | 2.02 (1.45–2.83) |
CYGB | 6–453/853 | 0.51 (0.45–0.57) | 0.79 (0.69–0.88) | 2.39 (1.61–3.56) | 0.62 (0.54–0.72) | 3.83 (2.28–6.44) |
APC | 8–588/928 | 0.43 (0.34–0.53) | 0.87 (0.71–0.95) | 3.30 (1.67–6.51) | 0.65 (0.59–0.72) | 5.06 (2.55–10.04) |
p16 | 24–1357/1249 | 0.48 (0.40–0.56) | 0.90 (0.82–0.95) | 4.71 (2.53–8.78) | 0.58 (0.50–0.68) | 8.11 (3.94–16.70) |
RASSF1A | 17–1160/1767 | 0.28 (0.20–0.38) | 0.95 (0.93–0.97) | 5.61 (3.73–8.43) | 0.76 (0.67–0.85) | 7.40 (4.54–12.06) |
Summary | 33–2238/2563 | 0.46 (0.41–0.50) | 0.83 (0.80–0.86) | 2.72 (2.32–3.22) | 0.64 (0.60–0.68) | 4.28 (3.50–5.20) |
Analysis | SEN (95% CI) | SPE (95% CI) | PLR (95% CI) | NLR (95% CI) | DOR (95% CI) |
---|---|---|---|---|---|
Ethnicity | |||||
Asian | 0.46 (0.44–0.48) | 0.84 (0.93–0.86) | 4.04 (2.91–5.62) | 0.61 (0.55–0.66) | 6.50 (4.73–8.92) |
Others | 0.47 (0.46–0.48) | 0.75 (0.74–0.75) | 1.88 (1.68–2.10) | 0.72 (0.68–0.77) | 2.92 (2.46–3.47) |
Sample size | |||||
0–100 | 0.48 (0.46–0.51) | 0.85 (0.83–0.88) | 4.13 (2.80–6.08) | 0.59 (0.54–0.65) | 7.80 (5.22–11.65) |
101–200 | 0.45 (0.44–0.46) | 0.75 (0.74–0.76) | 1.78 (1.58–2.00) | 0.73 (0.69–0.78) | 2.75 (2.29–3.31) |
201– | 0.51 (0.48–0.53) | 0.76 (0.74–0.77) | 2.52 (1.85–3.44) | 0.65 (0.59–0.73) | 3.94 (2.68–5.42) |
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Liu, D.; Peng, H.; Sun, Q.; Zhao, Z.; Yu, X.; Ge, S.; Wang, H.; Fang, H.; Gao, Q.; Liu, J.; et al. The Indirect Efficacy Comparison of DNA Methylation in Sputum for Early Screening and Auxiliary Detection of Lung Cancer: A Meta-Analysis. Int. J. Environ. Res. Public Health 2017, 14, 679. https://doi.org/10.3390/ijerph14070679
Liu D, Peng H, Sun Q, Zhao Z, Yu X, Ge S, Wang H, Fang H, Gao Q, Liu J, et al. The Indirect Efficacy Comparison of DNA Methylation in Sputum for Early Screening and Auxiliary Detection of Lung Cancer: A Meta-Analysis. International Journal of Environmental Research and Public Health. 2017; 14(7):679. https://doi.org/10.3390/ijerph14070679
Chicago/Turabian StyleLiu, Di, Hongli Peng, Qi Sun, Zhongyao Zhao, Xinwei Yu, Siqi Ge, Hao Wang, Honghong Fang, Qing Gao, Jiaonan Liu, and et al. 2017. "The Indirect Efficacy Comparison of DNA Methylation in Sputum for Early Screening and Auxiliary Detection of Lung Cancer: A Meta-Analysis" International Journal of Environmental Research and Public Health 14, no. 7: 679. https://doi.org/10.3390/ijerph14070679