The importance of extranodal extension in penile cancer: a meta-analysis

BMC Cancer. 2015 Oct 28:15:815. doi: 10.1186/s12885-015-1834-4.

Abstract

Background: The role of extranodal extension (ENE) in penile cancer is controversial and has not been well studied. The aim of this study was to investigate the importance of ENE in predicting prognosis and presence of pelvic lymph node metastasis (PLNM) in penile cancer patients.

Methods: We searched related studies in Medline, Embase, Cochrane Library, and Scopus database. Hazard ratio (HR) and odds ratio (OR) were directly extracted or indirectly estimated from the included studies.

Results: A total of ten studies with 1,142 patients were included in this meta-analysis. Patients with ENE showed a worse cancer-specific survival (CSS) (HR = 1.90, 95 % confidence interval [CI] = 1.35-2.67, P = 0.0002) and overall survival (HR = 4.04, 95 % CI = 1.02-16.1, P = 0.05) than those without ENE. Further subgroup analysis revealed that the predictive value of ENE for CSS in penile cancer patients was significant regardless of the study's country of origin, but not in the subgroup with shorter follow-up time (<36 months, P = 0.38). Patients with ENE also showed a higher incidence of presenting with PLNM (OR = 4.95, 95 % CI = 2.58-9.49, P < 0.001). A stratified analysis demonstrated that the predictive role of ENE for PLNM was only detected in studies with a larger sample size (> 100 cases). No significant publication bias was observed, as suggested by Begg's and Egger's tests.

Conclusions: ENE is associated with worse prognosis and high risk of PLNM in penile cancer patients. Due to the limited number of studies included in this meta-analysis, a large-scale, well-designed study will be required to verify our results.

Publication types

  • Meta-Analysis
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Humans
  • Lymph Nodes / pathology
  • Lymphatic Metastasis
  • Male
  • Odds Ratio
  • Penile Neoplasms / diagnosis
  • Penile Neoplasms / mortality*
  • Penile Neoplasms / pathology*
  • Prognosis
  • Proportional Hazards Models
  • Publication Bias