title: Prognostic value of combined serum biomarkers in predicting outcomes in cervical cancer patients.
abstract: BACKGROUND
  We evaluated the prognostic value of pretreatment serum biomarkers in predicting outcomes in cervical cancer patients subjected to treatment.
  
  
  METHODS
  Serum samples collected from 60 cervical cancer patients and 60 age-matched healthy individuals were used for the detection of 22 biomarkers, prior to therapy. Cox multivariate analysis and classification and regression tree analysis (CART) were performed to evaluate the prognostic factors.
  
  
  RESULTS
  Cox multivariate analysis disclosed that carbohydrate antigen 153 (CA153), squamous cell carcinoma antigen (SCC) and tumor necrosis factor-α (TNF-α) are associated with prognosis in cervical cancer. CART analysis led to the stratification of patients into 3 groups: (1) serum concentrations of CA153 ≥17.60 μg/l, (2) serum concentrations of CA153 <17.60 μg/l and TNF-α ≥10.60 pg/ml, and (3) serum concentrations of CA153 <17.60 μg/l and TNF-α <10.60 pg/ml. The 2-y overall survival rates for Groups 1, 2 and 3 were 33.3%, 60.0% and 93.9%, respectively.
  
  
  CONCLUSIONS
  Higher serum concentrations of TNF-α, SCC and CA153 before therapy are independently associated with poor prognosis in patients with stage I and II disease. Combined usage of these three biomarkers allows efficient evaluation of outcomes in cervical cancer patients.
authors.affiliation: Department of Clinical Biochemistry, State Key Laboratory of Kidney Disease, Chinese PLA General Hospital, Beijing 100853, China.
authors.forename: Juan
authors.initials: J
authors.lastname: Li
authors.forename: Hao
authors.initials: H
authors.lastname: Cheng
authors.forename: Pengjun
authors.initials: P
authors.lastname: Zhang
authors.forename: Zhennan
authors.initials: Z
authors.lastname: Dong
authors.forename: Hong-li
authors.initials: HL
authors.lastname: Tong
authors.forename: Jing-Dong Jackie
authors.initials: JD
authors.lastname: Han
authors.forename: Fei
authors.initials: F
authors.lastname: Guo
authors.forename: Ya-ping
authors.initials: YP
authors.lastname: Tian
mesh_terms: D000230:Adenocarcinoma / Q000097:blood / Q000175:diagnosis* / Q000235:genetics / Q000401:mortality; D000328:Adult; D000368:Aged; D000951:Antigens, Neoplasm / Q000097:blood / Q000235:genetics; D014408:Biomarkers, Tumor / Q000097:blood* / Q000235:genetics; D018196:Carcinoma, Adenosquamous / Q000097:blood / Q000175:diagnosis* / Q000235:genetics / Q000401:mortality; D002294:Carcinoma, Squamous Cell / Q000097:blood / Q000175:diagnosis* / Q000235:genetics / Q000401:mortality; D016022:Case-Control Studies; D005260:Female; D015870:Gene Expression; D006801:Humans; D008875:Middle Aged; D018396:Mucin-1 / Q000097:blood / Q000235:genetics; D009367:Neoplasm Staging; D011379:Prognosis; D016016:Proportional Hazards Models; D012189:Retrospective Studies; D015843:Serpins / Q000097:blood / Q000235:genetics; D016019:Survival Analysis; D014409:Tumor Necrosis Factor-alpha / Q000097:blood / Q000235:genetics; D002583:Uterine Cervical Neoplasms / Q000097:blood / Q000175:diagnosis* / Q000235:genetics / Q000401:mortality
chemical_list: D000951:Antigens, Neoplasm; D014408:Biomarkers, Tumor; D018396:Mucin-1; D015843:Serpins; D014409:Tumor Necrosis Factor-alpha; C051072:squamous cell carcinoma-related antigen
keywords: Cox regression model; Kaplan–Meier curve; Prognosis; Uterine cervical neoplasm