title: Differentiating between borderline and invasive malignancies in ovarian tumors using a multivariate logistic regression model.
abstract: OBJECTIVE
  The objective of this study was to build a model to differentiate between borderline and invasive ovarian tumors.
  
  
  METHODS
  We performed a retrospective study involving 148 patients with borderline or invasive ovarian tumors in our institute between 1997 and 2012. Clinical and pathologic data were collected. Logistic regression was used to build the model.
  
  
  RESULTS
  The model was created based on the following variables (p < 0.05): menopausal status; preoperative serum level of cancer antigen 125; the greatest diameter of the tumor; and the presence of solid parts on ultrasound imaging. The sensitivity and specificity of the model were 94.6% [95% confidence interval (CI), 0.887-1] and 78.3% (95% CI, 0.614-0.952) for patients aged ≥ 50 years, and 76.0% (95% CI, 0.622-0.903) and 60.0% (95% CI, 0.438-0.762) for those aged < 50 years, respectively. The performance of the model was tested using cross-validation.
  
  
  CONCLUSIONS
  Differentiation between borderline and invasive ovarian tumors can be achieved using a model based on the following criteria: menopausal status; cancer antigen 125 level; and ultrasound parameters. The model is helpful to oncologists and patients in the initial evaluation phase of ovarian tumors.
authors.affiliation: Multidisciplinary Science Research Center, National Sun Yat-sen University, Kaohsiung, Taiwan.
authors.forename: Jiabin
authors.initials: J
authors.lastname: Chen
authors.affiliation: Department of Applied Mathematics, National Sun Yat-sen University, Kaohsiung, Taiwan.
authors.forename: Chung
authors.initials: C
authors.lastname: Chang
authors.affiliation: Department of Obstetrics and Gynecology, Kaohsiung Veterans General Hospital, Kaohsiung, Taiwan; Graduate School of Business and Operations Management, Chang Jung Christian University, Tainan, Taiwan.
authors.forename: Hung-Chi
authors.initials: HC
authors.lastname: Huang
authors.affiliation: Department of Applied Mathematics, National Sun Yat-sen University, Kaohsiung, Taiwan.
authors.forename: Yu-Che
authors.initials: YC
authors.lastname: Chung
authors.affiliation: Department of Applied Mathematics, National Sun Yat-sen University, Kaohsiung, Taiwan.
authors.forename: Huan-Jung
authors.initials: HJ
authors.lastname: Huang
authors.affiliation: Department of Obstetrics and Gynecology, Kaohsiung Veterans General Hospital, Kaohsiung, Taiwan.
authors.forename: Wen Shiung
authors.initials: WS
authors.lastname: Liou
authors.affiliation: Department of Obstetrics and Gynecology, Kaohsiung Veterans General Hospital, Kaohsiung, Taiwan; Department of Biological Sciences, National Sun Yat-sen University, Kaohsiung, Taiwan; Department of Obstetrics and Gynecology, National Defense Medical Center, Taipei, Taiwan. Electronic address: ajchiang490111@gmail.com.
authors.forename: An Jen
authors.initials: AJ
authors.lastname: Chiang
authors.affiliation: Division of Gynecologic Oncology, Department of Obstetrics and Gynecology, Stanford University School of Medicine, Stanford, CA, USA.
authors.forename: Nelson N H
authors.initials: NN
authors.lastname: Teng
mesh_terms: D000293:Adolescent; D000328:Adult; D000367:Age Factors; D000368:Aged; D000369:Aged, 80 and over; D014408:Biomarkers, Tumor / Q000097:blood*; D018394:CA-125 Antigen / Q000097:blood*; D015331:Cohort Studies; D003937:Diagnosis, Differential; D019160:Endosonography / Q000379:methods; D005260:Female; D006801:Humans; D016015:Logistic Models; D008875:Middle Aged; D015999:Multivariate Analysis; D009361:Neoplasm Invasiveness / Q000473:pathology; D009367:Neoplasm Staging; D010051:Ovarian Neoplasms / Q000097:blood / Q000175:diagnosis / Q000000981:diagnostic imaging* / Q000473:pathology*; D012372:ROC Curve; D012189:Retrospective Studies; D018570:Risk Assessment; D012680:Sensitivity and Specificity; D013624:Taiwan; D047368:Tumor Burden / Q000502:physiology; D055815:Young Adult
chemical_list: D014408:Biomarkers, Tumor; D018394:CA-125 Antigen
keywords: borderline ovarian tumor; cancer antigen 125; invasive ovarian tumor; logistic regression