| Literature DB >> 33863308 |
Liu-Qing Zhou1, Yao Hu2, Hong-Jun Xiao3.
Abstract
BACKGROUND: Survivin has been recently identified as a promising novel therapeutic target and prognostic marker in different types of cancer. Here we conducted a comprehensive meta-analysis to better clarify they the precise prognostic and diagnostic value of survivin in head and neck squamous cell carcinoma (HNSCC).Entities:
Keywords: Head and neck squamous cell carcinoma; Meta-analysis; Prognosis; Survivin
Year: 2021 PMID: 33863308 PMCID: PMC8052826 DOI: 10.1186/s12885-021-08170-3
Source DB: PubMed Journal: BMC Cancer ISSN: 1471-2407 Impact factor: 4.430
Fig. 1Flow diagram of the selection of relevant studies included in the meta-analysis
Characteristics of the studies examined in the meta-analysis
| Author | Year | Country | Ethnicity | Cancer type | Sample size | Age | Follow-up (month) | Survival analysis | Method | Cut-off value | HR | NOS/REMARK score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Elhadj [ | 2019 | Tunisia | Non-Asian | LSCC | 70 | 63 (45–88) | NR | OS, DFS | IHC | 5% | Reported | 7/12 |
| Erpolat [ | 2012 | Turkey | Non-Asian | HNSCC | 58 | 56.7 (35–80) | 56.5 (38.7–112.5) | OS | IHC | 5% | Reported | 7/11 |
| Fiedler [ | 2018 | Germany | Non-Asian | HNSCC | 139 | 60.5 (43.4–83.6) | 17.4 (0–120.9) | OS,DSS | IHC | median value | Reported | 6/14 |
| Jin [ | 2019 | China | Asian | NPC | 164 | 45.0 (24–70) | 49.2 (9–60) | OS,DMFS, LRFS,DFS | IHC, RT-PCR | 0% | Reported | 6/13 |
| Li [ | 2008 | China | Asian | NPC | 280 | 46 (14–86) | NR | OS | IHC | 5% | Reported | 7/11 |
| Li [ | 2011 | China | Asian | LSCC | 86 | 51 (37–84) | NR | OS | IHC | 0% | Reported | 7/12 |
| Lin [ | 2005 | China | Asian | OSCC | 96 | NR | NR | OS | IHC | 25% | Reported | 6/12 |
| Muzio [ | 2005 | Italy | Non-Asian | OSCC | 78 | 66.5 (18–87) | 72 | DSS | IHC | 75% | Reported | 7/12 |
| Preuss [ | 2008 | Australia | Non-Asian | OSCC | 106 | 57 (34–82) | 20.3 (0.33–79.8) | DFS | IHC | 5% | Reported | 7/13 |
| Tastekin [ | 2017 | Turkey | Non-Asian | OSCC | 46 | 59.48 (31–91) | NR | OS | IHC | 13.00% | Reported | 6/11 |
| Wang [ | 2011 | China | Asian | NPC | 1268 | 46 (15–90) | 69 (1–20) | DSS | IHC | median value | Reported | 7/13 |
| Xiang [ | 2006 | China | Asian | NPC | 80 | NR | 60 | OS, DFS | IHC | 25% | Reported | 7/13 |
| Yip [ | 2006 | Canada | Non-Asian | NPC | 198 | NR | 136.8 | OS | IHC | 5% | Reported | 8/15 |
| Zhao [ | 2008 | China | Asian | LSCC | 146 | 54.6 (42–76) | 41.4 (36–72) | DFS | IHC | 5% | Reported | 7/14 |
| Dong [ | 2002 | Japan | Asian | LSCC | 102 | 63.49 (38–89) | NR | OS,DFS | IHC | 5% | Reported | 7/13 |
| Kim [ | 2005 | South Korea | Asian | OSCC | 113 | 58 (18–78) | NR | OS | RT-PCR | 50% | Estimated | 6/12 |
| Zhang [ | 2013 | China | Asian | OSCC | 110 | 58 (37–78) | > 60 | OS | IHC | median value | Estimated | 7/13 |
| Farnebo [ | 2013 | Sweden | Non-Asian | HNSCC | 40 | 68 | 30 | OS | IHC | 0% | Estimated | 6/11 |
| Freier [ | 2007 | Germany | Non-Asian | OSCC | 296 | 60 (16–92) | 34 (0–147) | OS | IHC | 10% | Estimated | 7/13 |
| Hansson [ | 2017 | Sweden | Non-Asian | LSCC | 149 | NR | 67 (9–163) | DFS | IHC | 10% | Estimated | 7/11 |
| Munscher [ | 2019 | Germany | Non-Asian | HNSCC | 452 | NR | 41.3 (1–306) | OS,RFS | IHC | 50% | Estimated | 7/11 |
| Pickhard [ | 2014 | Germany | Non-Asian | HNSCC | 180 | 53 (35–72) | 60–162 | OS | IHC | 10% | Estimated | 6/11 |
| Su [ | 2010 | China | Asian | OSCC | 78 | NR | NR | OS | IHC,RT-PCR | median value | Estimated | 6/11 |
| Troiano [ | 2018 | Italy | Non-Asian | OSCC | 342 | NR | NR | OS | IHC | 60% | Estimated | 7/11 |
| Pizem [ | 2004 | Slovenia | Non-Asian | LSCC | 68 | 59.2 (37–78) | NR | OS | IHC | 50% | Estimated | 6/12 |
| Marioni [ | 2013 | Italy | Non-Asian | LSCC | 33 | NR | 43 | DFS | IHC | 10.00% | Estimated | 6/11 |
| Marioni [ | 2017 | Italy | Non-Asian | LSCC | 75 | 63.6 | 67.3 | DFS | IHC | 6% | Estimated | 7/13 |
| Kim [ | 2010 | South Korea | Asian | OSCC | 38 | 58.5 (40–75) | NR | OS | IHC | 20% | Estimated | 6/11 |
Fig. 2Forest plot indicating the association between survivin expression and OS in HNSCC
Fig. 3Forest plot examining the association between survivin expression and DFS/DSS in HNSCC
Fig. 4Forest plot of OS in association with survivin in different types of HNSCC
Fig. 5Forest plot of OS in association with survivin in different types of geographic populations
Fig. 6The sensitivity analyses were conducted to evaluate the effects of each single study on the overall effect
Fig. 7Publication bias and trim and fill analysis of the enrolled analysis. a The Begg’s funnel plots; b The Egger’s test. c Trim and fill analysis