Table 1 Characteristics of qualified records in meta-analysis
Author | Year | Region | Study period | Cases | Cancer type | Stage | Detective method | Cut-off value | Outcomes | EGFR-TKIs | NOS scoresa |
|---|---|---|---|---|---|---|---|---|---|---|---|
Yoon B. W [26]. | 2020 | Korea | 2014.1–2019.12 | 131 | NSCLC | III–IV | IHC (22C3) | TPS: 1%, 50% | PFS, OS | Gefitinib, Erlotinib, and Afatinib | 9 |
Yang C. Y [24]. | 2020 | China | 2012–2017 | 153 | ADC | IIIB–IV | IHC (22C3) | TPS: 1%, 50% | PFS | Gefitinib, Erlotinib, and Afatinib | 9 |
Hsu K. H [22]. | 2019 | Korea | 2012–2017 | 123 | ADC | IIIB–IV | IHC (SP263) | TPS: 1%, 25%, 50% | PFS, OS | Gefitinib, Erlotinib, and Afatinib | 8 |
Matsumoto Y [23]. | 2019 | Japan | 2013.8–2017.12 | 52 | NSCLC | III–IV | IHC (28-8) | TPS: 50% | PFS | Gefitinib, Erlotinib, Afatinib, Gefitinib + Erlotinib, Afatinib + Gefitinib and Erlotinib + Afatinib | 8 |
Kobayashi K [19]. | 2018 | Japan | 2001–2009 | 32 | NSCLC | NA | IHC (SP263) | 5% of tumor cells | PFS, OS | Gefitinib and Erlotinib | 7 |
Su S [20]. | 2018 | China | 2016.4–2017.12 | 84 | NSCLC | IV | IHC (SP142) | TC3/IC3, TC1-2/IC1-2, and TC0/IC0 | PFS | Gefitinib | 7 |
Yoneshima Y [21]. | 2018 | Japan | 2013.1–2017.12 | 80 | ADC | III–IV | IHC (22C3) | TPS: 1%, 50% | PFS | NA | 7 |
Bai Y. C [18]. | 2018 | China | 2011–2015 | 73 | NSCLC | IIIB–IV | IHC (E1L3N) | Moderate staining: 5% | OS | NA | 6 |
Soo R. A [17]. | 2017 | Korea | 2011–2014 | 90 | NSCLC | III–IV | IHC (SP142) | H scoreb: 109.23(mean) | PFS, OS | Gefitinib, Erlotinib, and Dacomitinib | 7 |
Tang Y [16]. | 2015 | China | 2008.1–2014.3 | 89 | NSCLC | IIIB–IV | IHC (E1L3N) | H scoreb: 5 | PFS, OS | 1st TKIs and 2nd TKIs | 8 |
Lin C [15]. | 2015 | China | 2010.4–2014.7 | 56 | ADC | III–IV | IHC (ab58810) | H scoreb: mean of all patients | PFS, OS | Gefitinib and Erlotinib | 6 |
D’ Incecco A [14]. | 2015 | Italy | NA | 95 | NSCLC | III–IV | IHC (ab58810) | Moderate staining: 5% | OS | Gefitinib and Erlotinib | 6 |