Table 2 Characteristics of eligible studies for clinicopathological features
Author | Year | Country | Sample size | Cut-offa | Protein | T | N | M | ER | PR | HER2 | S | G | NOS |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Talvensaari-Mattila [51] | 1998 | Finland | 169 | P > 1% | MMP2 | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | 8 | |
Talvensaari-Mattila [50] | 1999 | Finland | 108 | P > 1% | MMP2 | ✓ | ✓ | ✓ | ✓ | 8 | ||||
Talvensaari-Mattila [49] | 2001 | Finland | 100 | P > 1% | MMP2 | ✓ | ✓ | 7 | ||||||
Scorilas | 2011 | Greece | 210 | HSCORE> 175 | MMP9 | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | 7 | ||
Hirvonen [47] | 2003 | Finland | 137 | P > 1% | MMP2 | ✓ | ✓ | ✓ | ✓ | 6 | ||||
Nakopoulou | 2003 | Greece | 135 | P > 10% | MMP2 | ✓ | ✓ | ✓ | ✓ | 6 | ||||
Fan [45] | 2003 | China | 66 | SI ≥ 1 | MMP2, MMP9 | ✓ | ✓ | ✓ | ✓ | ✓ | 6 | |||
Talvensaari-Mattila [44] | 2003 | Finland | 453 | P > 1% | MMP2 | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | 8 | ||
Li [19] | 2004 | China | 270 | P > 1% | MMP2, MMP9 | ✓ | ✓ | ✓ | ✓ | 6 | ||||
Rahko [23] | 2004 | Finland | 168 | P > 1% | MMP9 | ✓ | ✓ | ✓ | ✓ | ✓ | 7 | |||
Ban [52] | 2004 | China | 60 | SI ≥ 3 | MMP2 | ✓ | ✓ | 7 | ||||||
Sivula | 2005 | Finland | 194 | P > 20% | MMP2 | ✓ | ✓ | ✓ | ✓ | 7 | ||||
Zhou [42] | 2005 | China | 112 | P > 5% | MMP2 | ✓ | ✓ | ✓ | ✓ | ✓ | 7 | |||
Mylona | 2007 | Greece | 175 | P > 20% | MMP9 | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | 6 | ||
Hao | 2007 | China | 76 | SI ≥ 5 | MMP9 | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | 7 | ||
Wu | 2008 | China | 60 | P > 50% | MMP9 | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | 7 | ||
Sullu [22] | 2011 | Turkey | 140 | SI ≥ 5 | MMP9 | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | 8 | |
Zhao [18] | 2013 | China | 127 | SI ≥ 6 | MMP9 | ✓ | ✓ | ✓ | ✓ | 6 | ||||
Zeng [36] | 2013 | China | 253 | P > 20% | MMP9 | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | 8 | ||
Wu | 2014 | China | 41 | SI ≥ 1 | MMP9 | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | 7 | ||
Tang | 2014 | China | 156 | SI ≥ 6 | MMP9 | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | 8 | |
Min [32] | 2014 | Korea | 177 | SI ≥ 1, SI ≥ 5 | MMP2, MMP9 | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | 7 | |
Youssef | 2014 | Egypt | 67 | P > 10% | MMP9 | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | 7 | |
Huang [55] | 2014 | China | 147 | P > 10% | MMP9 | ✓ | ✓ | 6 | ||||||
Ramos [29] | 2016 | Brazil | 44 | P > 10% | MMP2 | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | 7 | |
Li [16] | 2017 | China | 80 | P > 25% | MMP2, MMP9 | ✓ | ✓ | ✓ | 7 | |||||
Yang [28] | 2018 | Korea | 173 | SI ≥ 2 | MMP9 | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | 8 | |
Zhang [56] | 2019 | China | 127 | SI ≥ 6 | MMP9 | ✓ | ✓ | ✓ | ✓ | 7 | ||||
Zhou [54] | 2009 | China | 43 | SI ≥ 3 | MMP9 | ✓ | ✓ | ✓ | ✓ | 7 | ||||
Joseph [27] | 2020 | British | 675 | SI | MMP9 | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | 8 |