p16, encoded by the
Bladder cancer is the most frequent malignancy of the urinary tract and the ninth most common cancer worldwide [
Numerous studies to date have explored the clinicopathological and prognostic significance of p16 in patients with bladder cancer. However, as a result of differences in sample sizes, accuracies of the statistical data, study populations, and interventions, the results remain inconclusive, and evidence-based confirmation by large-scale clinical trials is still lacking. We therefore conducted an in-depth systematic review and meta-analysis to investigate the correlation between abnormal expression of p16 and clinicopathological features, as well as prognosis in patients with bladder cancer. The specific mechanisms are shown in Figure
Main molecular pathways of bladder cancer (adapted from Mitra et al. [
The terms and combinations including “Cyclin Dependent Kinase Inhibitor p16,” “CDKN2A Protein,” “p16INK4A Protein,” “MTS1 Protein,” “Cyclin Dependent Kinase Inhibitor 2A,” “Multiple Tumor Suppressor 1,” “Cdk4 Associated Protein p16,” “TP16,” and “urinary bladder neoplasms,” “bladder tumors,” “bladder cancers,” “bladder carcinomas,” and “
Inclusion criteria were as follows: (1) patients diagnosed with bladder cancer; (2) immunohistochemical (IHC) detection of p16 expression levels in the tissues; (3) relationships between abnormal expression of p16 and prognostic indicators such as recurrence-free survival (RFS), progression-free survival (PFS), and overall survival (OS) or associations between p16 and clinicopathological features that were evaluated; (4) hazard ratio (HR), odds ratio (OR), relative risk (RR), and 95% confidence intervals (CI) that could be obtained directly from the full article or indirectly calculated with relevant software based on the data provided in the graphics and tables; (5) only the newest studies or the ones with higher quality were retained if the data were repeated in different studies; and (6) studies in English or Chinese.
Exclusion criteria were as follows: (1) cell or animal studies, case reports, letters, reviews, and meta-analyses; (2) articles with similar content or using the same data or those with small sample sizes (
Two independent investigators (Xiaoning Gan and Rongquan He) reviewed the articles that met the criteria and extracted data on author, year of publication, nationality, sample size, patient age, detection method of p16, antibody source and dilution, clinical stage, pathological degree, other costudied prognosis-associated genes, cut-off value, outcome, and extraction method of the study subjects. Discrepancies between the two independent investigators in terms of data extraction were resolved by discussion among all the authors.
Effects of p16 on the related prognostic indexes were detected by merging the HRs and 95% CI of the included literatures, which were evaluated through the Forest plot and related parameters after the merging. The HRs and 95% CI values mainly came from direct extraction of the original text or survival curve through extraction and calculation by software.
The relationships between p16 and the clinicopathological parameters were derived from the binary variable data extracted from the original articles. ORs and 95% CI values came from the binary variable data calculated by Stata software. The data were then combined, and their statistical significance was evaluated by Forest plot and related parameters, to clarify the relationship between p16 low-expression and clinicopathological parameters.
Heterogeneity was measured by
Publication bias was detected by Begg’s funnel plot and Egger’s test with Stata software. A two-sided
A total of 364 articles were identified from the databases, including 190 English and 174 Chinese articles, 222 of which were excluded because of discrepancies between the study theme and their abstracts. The full text of the remaining 142 articles was then reviewed for their fit with the current study, after which a further 105 articles were excluded because they met one or more of the exclusion criteria, such as the cell or animal studies, reviews, and letters and studies with identical data and no extractable HR, OR, and 95% CI data from the full text or language barrier. The remaining 37 articles [
Flow diagram of studies selection procedure.
The basic features of the included studies were presented in Table
Main features of all studies included in the meta-analysis.
Author | Year | Nation | No. |
Age | Stage | Grade | Cut-off value | Outcome | Data extraction | Other costudied genes | Antibody source (dilution) | Detection method of p16 |
---|---|---|---|---|---|---|---|---|---|---|---|---|
Orlow et al. [ |
1999 | Canada | 120 | NR | Ta–T1 | G1–G3 | Score = 3 | RFS/CP | Reported | P14 | Vector (1 : 500) | Immunohistochemistry |
Bartoletti et al. [ |
2007 | Italy | 56 (50/6) | 70.1 (45–89) | Ta–T1 | G1-G2 | 10% | RFS | Reported | 9p21 | Bio-Optica (1 : 25) | Immunohistochemistry |
Chakravarti et al. [ |
2005 | USA | 50 (36/14) | NR | T2–T4 | High | 20% | OS/FFS/DSS | Reported | Erb-1, Erb-2, P53, PRB | Zymed (NR) | Immunohistochemistry |
Hitchings et al. [ |
2004 | UK | 78 | 66 (24–90) | Ta–T1 | G1–G3 | 10% | PFS/RFS/CP | Reported | P53, PRB | Novocastra (1 : 50) | Immunohistochemistry |
Krüger et al. [ |
2005 | Germany | 73 (60/13) | 68 (NR) | T1 | G2-G3 | 10% | RFS/PFS | Reported | NR | Biocarta (1 : 50) | Immunohistochemistry |
Lee et al. [ |
2010 | Korea | 47 (4/43) | NR | Ta–T4 | Low and high | Score = 5 | OS/CP | Reported | P53, PRB | DAKO (1 : 200) | Immunohistochemistry |
Mhawech et al. [ |
2004 | Switzerland | 49 (44/5) | 70.3 (52–90) | T1 | Low and high | Score = 3 | PFS/CP | Reported | P21 | DAKO (1 : 20) | Immunohistochemistry |
Yang et al. [ |
2002 | China | 67 | NR | T1-T2 | G1–G3 | 5% | RFS/CP | Binary variable | Cyclin D1, CCNE, p27, p21, p53 | Santa Cruz (NR) | Immunohistochemistry |
Brunner et al. [ |
2008 | Switzerland | 99 | NR | Ta–T4 | Low and high | 1.5% or 23% | OS/RFS | Survival curve | MTS | NeoMarkers (1 : 50) | Immunohistochemistry |
Friedrich et al. [ |
2001 | Germany | 40 | NR | Ta–T1 | G1–G3 | 5% | RFS/CP | Survival curve | LOH | Pharmingen (1 : 100) | Immunohistochemistry |
Korkolopoulou et al. [ |
2001 | Greece | 23 | 72 (35–92) | T3-T4 | Low and high | 5% | OS/CP | Survival curve | P53 | Santa Cruz (1 : 100) | Immunohistochemistry |
Niehans et al. [ |
1999 | USA | 78 | 64.7 (48–82) | T1–T4 | G2–G4 | Score = 4 | DSS/CP | Survival curve | P53, PRB, cyclin D1 | Pharmingen (1 : 400) | Immunohistochemistry |
Røtterud et al. [ |
2002 | Norway | 59 | 64 (42–75) | T2–T4 | G2-G3 | Score = 3 | CSS/CP | Survival curve | p21, p27 | NeoMarkers (1 : 100) | Immunohistochemistry |
Vallmanya Llena et al. [ |
2006 | Spain | 97 | NR | Ta–T1 | Low and high | 15% | RFS/PFS/OS/CP | Survival curve | p53, p21 | DakoCytomation (NR) | Immunohistochemistry |
Sun et al. [ |
2000 | China | 60 | NR | Tis–T4 | G1–G3 | Score = 4 | OS | Survival curve | PRb | Santa Cruz (1 : 100) | Immunohistochemistry |
Santos et al. [ |
2003 | Portugal | 56 (40/16) | 70 (43–83) | Ta–T1 | G1-G2 | 20% | RFS/CP | Binary variable | p27, pRb, p53, Ki-67 | Pharmingen (1 : 500) | Immunohistochemistry |
Yin et al. [ |
2008 | USA | 18 | NR | T1–T4 | Low and high | Score = 4 | CP | Binary variable | 9p21 | Pharmingen (1 : 250) | Immunohistochemistry |
Primdahl et al. [ |
2002 | Denmark | 69 (55/14) | 71 (42–83) | Ta–T4 | G1–G4 | Score = 4 | CP | Binary variable | Rb, p27, p21, L-myc | NeoMarkers (1 : 50) | Immunohistochemistry |
Jin et al. [ |
2006 | USA | 39 (25/14) | 65 (42–84) | T2–T4 | G1–G4 | 10% | CP | Binary variable | P53, pRB | NR (1 : 50) | Immunohistochemistry |
Tzai et al. [ |
2004 | China (Taiwan) | 65 (44/21) | 61.5 (41–84) | T2–T4 | G2-G3 | Score = 4 | CP | Binary variable | P53, pRB | Santa Cruz (1 : 20) | Immunohistochemistry |
Jin et al. [ |
2004 | China | 62 (32/30) | 61 (18–80) | Tis–T4 | G1–G3 | OC | CP | Binary variable | Cyclin D1, PCNA | NR | Immunohistochemistry |
Fu and Li [ |
2011 | China | 50 (39/11) | 59.3 (32–81) | Tis–T4 | G1–G3 | 10% | CP | Binary variable | E-cadherin | NR | Immunohistochemistry |
Shi et al. [ |
2001 | China | 62 (52/10) | 58.5 (22–87) | Tis–T4 | G1–G3 | Score = 3 | RFS/CP | Binary variable | PCNA | Zymed (1 : 50) | Immunohistochemistry |
Wang [ |
2001 | China | 49 (39/10) | 61 (22–89) | NR | G1–G3 | 10% | RFS/CP | Binary variable | NR | NR | Immunohistochemistry |
Miao [ |
1999 | China | 50 | NR | Tis–T4 | G1–G3 | OC | RFS/OS/CP | Binary variable | Cyclin D1 | Santa Cruz (1 : 100) | Immunohistochemistry |
Shi et al. [ |
2003 | China | 82 (65/17) | 58.7 (24–72) | Tis–T4 | G1–G3 | OC | RFS/CP | Binary variable | Cyclin D1 | NR | Immunohistochemistry |
Yang [ |
2005 | China | 69 (62/7) | 61 (42–75) | Tis–T4 | G1–G3 | 5% | RFS/CP | Binary variable | P27/nm23 | NR | Immunohistochemistry |
Wang et al. [ |
2013 | China | 45 (30/15) | 65 (38–80) | NR | H/L | 5% | RFS/CP | Binary variable | PTEN/P53 | NR | Immunohistochemistry |
Leng et al. [ |
2000 | China | 51 (43/8) | 53.4 (28–72) | Tis–T3 | G1–G3 | OC | RFS/OS/CP | Binary variable | bcl-2 | Santa Cruz (1 : 50) | Immunohistochemistry |
Bai and Xiong [ |
2014 | China | 65 (50/15) | (57.7 ± 8.2) | Tis–T4 | H/L | 5% | CP | Binary variable | mfn2 | Zymed (NR) | Immunohistochemistry |
Wang et al. [ |
2000 | China | 75 (62/13) | 58.5 (24–81) | Tis–T4 | G1–G3 | OC | CP | Binary variable | c-erbB-2, p53 | Maxim (1 : 50) | Immunohistochemistry |
Wang et al. [ |
2006 | China | 55 (35/20) | 63 (24–75) | Tis–T4 | G1–G3 | 10% | CP | Binary variable | hTERT, cyclin D1, RB | NR | Immunohistochemistry |
Lu et al. [ |
2008 | China | 40 (30/10) | 54.2 (37–79) | Tis–T4 | G1–G3 | 10% | CP | Binary variable | p53, PCNA | NR (1 : 50) | Immunohistochemistry |
Xie et al. [ |
2003 | China | 72 (56/16) | NR (29–78) | Tis–T4 | G1–G3 | 5% | RFS/CP | Binary variable | Rb, cyclin D1 | Zymed (1 : 50) | Immunohistochemistry |
Qiu et al. [ |
2006 | China | 53 (46/7) | 61 (25–83) | Tis–T4 | G1–G3 | 15% | CP | Binary variable | NR | NR | Immunohistochemistry |
Rebouissou et al. [ |
2012 | France | 89 | NR | Ta–T1 | G1–G3 | Score = 3 | RFS/PFS | Survival curve | FGFR3 | NR | FISH |
Abat et al. [ |
2014 | Turkey | 34 (30/4) | NR | T1–T4 | Low and high | OC | PFS | Reported | p53 | NR | FISH |
M: male; F: female; RFS: recurrence-free survival; OS: overall survival; PFS: progression-free survival; DSS: disease-specific survival; CSS: cancer-specific survival; CP: clinicopathological parameters; OC: other criteria; NR: not reported; No.
A total of 17 studies with 1032 subjects were included in the final analysis of RFS [
Forrest plot of hazard ratio (HR) for the association of p16 with recurrence-free survival (RFS) (a), overall survival (OS) (b), and progression-free survival (PFS) (c) in patients with bladder cancer.
Cumulative meta-analysis based on year of publication and sample size demonstrated that the results tended to stabilize with increasing sample size, but there was no obvious relationship between the results and year of publication.
Based on sensitivity analysis, the study by Yang et al. [
Subgroup analysis based on geographic region showed that low expression of p16 was associated with RFS in patients with bladder cancer both in Asia (HR = 1.44, 95% CI = 1.15~1.81, and
Subgroup analysis based on clinical stage suggested that the effect of p16 on RFS was associated with clinical stage (Tis-T1 group: HR = 1.96, 95% CI = 1.23~3.14, and
Subgroup analysis based on histopathological grade showed that heterogeneity decreased from G1-G2 (HR = 4.12, 95% CI = 2.48~6.83, and
Subgroup analysis also showed an effect of cut-off value on the influence of p16 on RFS (cut-off value ≤ 10%: HR = 1.83, 95% CI = 1.34~2.51, and
In addition, subgroup analysis of early-stage data from 430 subjects from eight studies also demonstrated that low expression of p16 significantly affected RFS in patients with early-stage (Ta–T1) bladder cancer (HR = 1.96, 95% CI = 1.23~3.14, and
A total of 425 subjects in eight studies were included in the final analysis of OS [
Cumulative meta-analysis and sensitivity analysis indicated relatively low overall heterogeneity and no study with high sensitivity.
Subgroup analysis based on geographic area showed a subtle distinction between p16 expression and OS in patients with bladder cancer in Asia (HR = 1.61, 95% CI = 0.97~2.66, and
Subgroup analysis was also performed based on clinicopathological stages. However, limitations of sample size led to the impossibility of determining if the effects of p16 expression on OS were associated with these parameters in patients with bladder cancer (Ta–T1 group: HR = 1.57, 95% CI = 0.32~7.75, and
Subgroup analysis based on cut-off value indicated that the effects of p16 on OS in patients with bladder cancer were associated with cut-off value (cut-off value ≤ 10%: HR = 1.83, 95% CI = 1.17~2.86, and
A total of 470 subjects in seven studies were included in the ultimate analysis of PFS [
Cumulative meta-analysis revealed no obvious characteristics because of the limited range of publication dates and the sample sizes.
Sensitivity analysis identified two studies [
Despite a reduced sample size, subgroup analysis of the 347 subjects from five studies [
Subgroup analysis based on cut-off value demonstrated some relationship between cut-off value and the influence of p16 expression on PFS (cut-off value ≤ 10%: HR = 2.61, 95% CI = 1.42~4.77, and
The results from 297 subjects with early-stage (Ta–T1) bladder cancer from four studies [
A total of 187 subjects from three studies were included in the DSS/CSS analysis [
The relationship between low expression of p16 and clinicopathological parameters [
Analysis of the results for lymph node metastasis showed OR = 2.20, 95% CI = 1.26~3.83, and
Main meta-analysis results of p16 expression in patients with bladder cancer.
Analysis | No. |
HR (95% CI) |
|
|
Model | Heterogeneity | Publication bias | ||
---|---|---|---|---|---|---|---|---|---|
|
|
Begg’s |
Egger’s | ||||||
|
18 (1032) | 1.63 (1.36–1.94) | 5.40 |
|
F | 42.6 | 0.029 | 0.405 | 0.246 |
Europe | 8 (365) | 1.90 (1.13–3.19) | 2.43 |
|
R | 53.1 | 0.037 | 1.000 | 0.749 |
Asia | 9 (547) | 1.44 (1.15–1.81) | 3.15 |
|
F | 30.7 | 0.173 | 0.348 | 0.020 |
America | 1 (120) | 1.58 (0.77–3.25) | 1.24 |
|
F | 0.0 | / | / | / |
Ta–T1 | 8 (430) | 1.96 (1.23–3.14) | 2.82 |
|
R | 55.5 | 0.028 | 0.711 | 0.916 |
Ta–T4 | 10 (602) | 1.41 (1.12–1.77) | 2.96 |
|
F | 10.2 | 0.348 | 1.000 | 0.062 |
G1-G2 | 2 (75) | 4.12 (2.48–6.83) | 5.49 |
|
F | 0.0 | 0.924 | 1.000 | / |
G1–G3 | 14 (762) | 1.44 (1.18–1.75) | 3.50 |
|
F | 11.9 | 0.323 | 0.584 | 0.031 |
G2-G3 | 2 (95) | 1.37 (0.78–2.42) | 1.10 |
|
F | 0.0 | 0.802 | 1.000 | / |
Cut-off value (≤10%) | 13 (741) | 1.83 (1.34–2.51) | 3.79 |
|
R | 54.8 | 0.009 | 0.583 | 0.297 |
Cut-off value (>10%) | 5 (291) | 1.34 (0.86–2.09) | 1.28 |
|
F | 0.0 | 0.701 | 0.462 | 0.166 |
|
9 (425) | 1.70 (1.16–2.50) | 2.71 |
|
F | 0.0 | 0.584 | 0.602 | 0.165 |
Europe | 4 (167) | 2.54 (1.05–6.15) | 2.07 |
|
F | 27.0 | 0.250 | 1.000 | 0.289 |
Asia | 4 (208) | 1.61 (0.97–2.66) | 1.85 |
|
F | 0.0 | 0.703 | 0.734 | 0.166 |
America | 1 (50) | 1.41 (0.62–3.19) | 0.83 |
|
F | 0.0 | / | / | / |
Ta–T4 | 5 (230) | 1.59 (0.98–2.60) | 1.87 |
|
F | 3.1 | 0.389 | 1.000 | 0.232 |
Ta–T1 | 2 (122) | 1.57 (0.32–7.75) | 0.55 |
|
F | 0.0 | 0.750 | 1.000 | / |
T2–T4 | 2 (73) | 1.96 (0.99–3.88) | 1.94 |
|
R | 52.1 | 0.148 | 1.000 | / |
G1–G3 | 7 (353) | 1.82 (1.16–2.84) | 2.62 |
|
F | 3.9 | 0.397 | / | / |
L | 1 (22) | 1.41 (0.18–10.90) | 0.33 |
|
F | / | / | / | / |
H | 1 (50) | 1.41 (0.62–3.19) | 0.83 |
|
F | / | / | / | / |
Cut-off value (≤10%) | 7 (278) | 1.83 (1.17–2.86) | 2.63 |
|
F | 3.2 | 0.402 | 0.764 | 0.185 |
Cut-off value (>10%) | 2 (147) | 1.40 (0.66–2.96) | 0.87 |
|
F | 0.0 | 0.951 | 1.000 | / |
|
8 (470) | 2.18 (1.37–3.48) | 3.28 |
|
F | 26.3 | 0.219 | 0.174 | 0.325 |
IHC | 6 (347) | 1.84 (1.13–3.01) | 2.44 |
|
F | 0.0 | 0.487 | 1.000 | 0.754 |
FISH | 2 (123) | 11.28 (2.45–51.83) | 3.11 |
|
F | 0.0 | 0.718 | 1.000 | / |
Europe | 5 (297) | 2.09 (1.21–3.63) | 2.62 |
|
F | 0.0 | 0.484 | 1.000 | 0.607 |
America | 1 (50) | 1.14 (0.39–3.31) | 0.24 |
|
F | / | / | / | / |
Ta–T1 | 5 (297) | 2.09 (1.21–3.63) | 2.62 |
|
F | 0.0 | 0.484 | 1.000 | 0.607 |
T2–T4 | 1 (50) | 1.14 (0.39–3.31) | 0.24 |
|
F | / | / | / | / |
G1–G3 | 5 (297) | 2.09 (1.21–3.63) | 2.62 |
|
F | 0.0 | 0.484 | 1.000 | 0.607 |
H | 1 (50) | 1.14 (0.39–3.31) | 0.24 |
|
F | / | / | / | / |
Cut-off value (≤10%) | 4 (200) | 2.61 (1.42–4.77) | 3.10 |
|
F | 0.0 | 0.932 | 1.000 | 0.746 |
Cut-off value (>10%) | 2 (147) | 0.95 (0.41–2.18) | 0.13 |
|
F | 0.0 | 0.579 | 1.000 | / |
|
3 (187) | 1.52 (0.85–2.71) | 1.42 |
|
F | 0.0 | 0.825 | 0.296 | 0.517 |
|
|||||||||
Clinicopathological parameters | OR (95% CI) | ||||||||
|
|||||||||
Stage (T2–T4 versus Ta–T1) | 19 (1231) | 3.13 (2.42–4.06) | 8.63 |
|
F | 1.4 | 0.440 | 0.529 | 0.377 |
Asia | 14 (878) | 3.41 (2.51–4.64) | 7.87 |
|
F | 0.0 | 0.800 | 0.661 | 0.650 |
Europe | 3 (277) | 3.17 (1.79–5.60) | 3.96 |
|
F | 63.7 | 0.064 | 1.000 | 0.994 |
America | 2 (76) | 1.15 (0.41–3.20) | 0.26 |
|
F | 0.0 | 0.604 | 1.000 | / |
Stage (T1 versus Ta) | 5 (374) | 1.55 (0.87–2.76) | 1.50 |
|
F | 40.5 | 0.152 | 0.806 | 0.402 |
Grade (G3 versus G1-2) | 20 (1291) | 3.33 (2.51–4.42) | 8.32 |
|
F | 0.0 | 0.519 | 0.206 | 0.805 |
Asia | 15 (895) | 3.36 (2.44–4.63) | 7.41 |
|
F | 18.6 | 0.246 | / | / |
Europe | 3 (196) | 2.62 (1.23–5.57) | 2.50 |
|
F | 0.0 | 0.984 | / | / |
America | 2 (200) | 4.51 (1.61–12.61) | 2.87 |
|
F | 0.0 | 0.659 | / | / |
Grade (H versus L) | 8 (688) | 1.20 (0.62–2.33) | 0.55 |
|
R | 61.8 | 0.011 | 0.063 | 0.080 |
Lymph node metastasis (yes versus no) | 5 (319) | 2.20 (1.26–3.83) | 2.77 |
|
F | 27.2 | 0.240 | 1.000 | 0.487 |
Muscle Invasive (yes versus no) | 4 (248) | 2.18 (0.72–6.62) | 1.38 |
|
R | 71.8 | 0.014 | 0.497 | 0.998 |
Number of tumors (multiple versus single) | 2 (166) | 1.11 (0.43–2.85) | 0.22 |
|
F | 0.0 | 0.984 | 1.000 | / |
Tumor size (>3 versus ≤3) | 2 (193) | 2.93 (0.40–21.36) | 1.06 |
|
R | 79.2 | 0.028 | 1.000 | / |
RFS: recurrence-free survival; OS: overall survival; PFS: progression-free survival; DSS: disease-specific survival; CSS: cancer-specific survival; HR: hazard ratio; OR: odds ratio; CI: confidence interval; No.
Three studies [
Relationship between low expression of p16 and other prognostic factors in patients with bladder cancer.
Author | Year | Nation | No. |
Age | Stage | Grade | Cut-off value | Other related biomarkers | Measuring method | Antibody source (dilution) | Outcome |
|
||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Jin et al. [ |
2006 | USA | 39 (25/14) | 65 (42–84) | T2–T4 | G1–G4 | 10% | P53, pRB | Immunohistochemistry | NR (1 : 50) | OS/PFS (2-year survival) | 0.001 | <0.001 | |
Tzai et al. [ |
2004 | China (Taiwan) | 65 (44/21) | 61.5 (41–84) | T2–T4 | G2-G3 | Score = 4 | P53, pRB | Immunohistochemistry | Santa Cruz (1 : 20) | PFS/DSS | 0.74 | 0.49 | |
Yurakh et al. [ |
2006 | Spain | 55 | NR | Ta–T4 | G1–G3 | 10% | 9p21 (P14, P15, P16) | Immunohistochemistry | Santa Cruz (1 : 500) | RFS/OS/PFS (3-year survival) | 0.31 | 0.022 | 0.012 |
M: male; F: female; RFS: recurrence-free survival; OS: overall survival; PFS: progression-free survival; DSS: disease-specific survival; NR: not reported; No.
Publication bias was detected by Begg’s funnel plot and Egger’s test (Figure
The funnel plot of the meta-analysis of the impact of p16 expression on recurrence-free survival (RFS) (a), overall survival (OS) (b), and progression-free survival (PFS) (c) in patients with bladder cancer.
Pan et al. performed a meta-analysis of the prognostic significance of abnormal p16 and p21 expression in bladder cancer in 2006 [
The current study systematically analyzed the relationships between p16 expression and prognostic index and clinicopathological parameters in patients with bladder cancer and showed that low expression of p16 was closely correlated with poor prognosis (Figure
Our results illustrated and improved the relationship between p16 and prognosis, as well as clinicopathological features.
The current study had some limitations. First, tumors are the result of both environmental and genetic factors, and p16 may thus be only one of several factors involved in the whole process of bladder carcinogenesis. Secondly, heterogeneity may result from differences in intervention measures (surgery, radiotherapy, chemotherapy, or combination), immunohistochemical techniques (different antibodies, evaluation standards, etc.), and the HR extraction methods used in the included studies. Finally, the exclusion of articles because of language barriers and of studies that were not published because of a lack of sufficient data may have led to potential publication bias.
In conclusion, the results of the current study provide evidence for a relationship between p16 expression and prognosis and clinicopathological features in patients with bladder cancer. The results of this meta-analysis will help to inform about the development of clinical guidelines promoting best medical care for patients with bladder cancer. Further studies are required to investigate the combined influence of genetic and environmental factors on the development and progression of bladder cancer.
Recurrence-free survival
Overall survival
Progression-free survival
Disease-specific survival
Cancer-specific survival
Hazard ratio
Odds ratio
Confidence interval.
The authors declare that they have no competing interests.
Xiaoning Gan, Xiaomiao Lin, Rongquan He, Xinggu Lin, Hanlin Wang, Liyan Yan, Hong Zhou, and Hui Qin performed the literature search, data extraction, and statistical analysis and drafted the paper. Gang Chen supervised the literature search, data extraction, and analysis and reviewed the paper. Xiaoning Gan, Xiaomiao Lin, Rongquan He, Xinggu Lin, Hanlin Wang, Liyan Yan, Hong Zhou, Hui Qin, and Gang Chen read and approved the final paper.