title: Prognostic role of hormone receptors in ovarian cancer: a systematic review and meta-analysis.
abstract: OBJECTIVE
  The aim of this study was to summarize the global predicting role of hormone receptors for survival in ovarian cancer.
  
  
  METHODS
  Eligible studies were identified and assessed for quality through multiple search strategies. Data were collected from studies comparing overall or progression-free/disease-free/relapse-free survival in patients with elevated levels of estrogen receptor (ER), progesterone receptor (PR), or human epidermal growth factor receptor 2 (HER2) with those in patients with lower levels. Studies were pooled, and combined hazards ratios (HRs) of ER, PR, and HER2 for survival were calculated, respectively.
  
  
  RESULTS
  A total of 35 studies were included for meta-analysis (23 for ER, 19 for PR, and 8 for HER2). For overall survival, the pooled HR of PR reached 0.88 [95% confidence interval (CI), 0.82-0.95], which means that elevated PR level could significantly indicate better survival. In contrast, elevated levels of HER2 could predict worse outcome with an HR of 1.41 (95% CI, 1.05-1.89). Increased level of ER was not significantly prognostic (HR, 0.94; 95% CI, 0.87-1.01). For progression-free survival/disease-free survival/recurrence-free survival, elevated PR level also had predictive value for better outcome with a pooled HR of PR of 0.80 (95% CI, 0.67-0.95). Oppositely, elevated HER2 level could predict poorer outcome with an HR of 1.55 (95% CI, 1.11-2.16). Estrogen receptor failed to predict outcome with an HR of 0.90 (95% CI, 0.78-1.03).
  
  
  CONCLUSIONS
  In patients with ovarian cancer, elevated level of PR predicted favorable survival, and elevated level of HER2 was associated with worse survival.
authors.affiliation: Department of Minimally Invasive Gynecologic Surgery, Shanghai First Maternity and Infant Hospital, Tongji University School of Medicine, Shanghai, PR China.
authors.forename: Dong
authors.initials: D
authors.lastname: Zhao
authors.forename: Fengmei
authors.initials: F
authors.lastname: Zhang
authors.forename: Wei
authors.initials: W
authors.lastname: Zhang
authors.forename: Jing
authors.initials: J
authors.lastname: He
authors.forename: Yulan
authors.initials: Y
authors.lastname: Zhao
authors.forename: Jing
authors.initials: J
authors.lastname: Sun
mesh_terms: D000465:Algorithms; D014408:Biomarkers, Tumor / Q000235:genetics / Q000378:metabolism / Q000502:physiology; D002277:Carcinoma / Q000175:diagnosis* / Q000453:epidemiology / Q000235:genetics / Q000401:mortality; D005260:Female; D006801:Humans; D010051:Ovarian Neoplasms / Q000175:diagnosis* / Q000453:epidemiology / Q000235:genetics / Q000401:mortality; D011237:Predictive Value of Tests; D011379:Prognosis; D018160:Receptors, Cytoplasmic and Nuclear / Q000235:genetics / Q000378:metabolism / Q000502:physiology*; D016019:Survival Analysis
chemical_list: D014408:Biomarkers, Tumor; D018160:Receptors, Cytoplasmic and Nuclear