title: Preoperative predictors for residual tumor after surgery in patients with ovarian carcinoma.
abstract: OBJECTIVE
  Suboptimal debulking (>1 cm residual tumor) results in poor survival rates for patients with an advanced stage of ovarian cancer. The purpose of this study was to develop a prediction model, based on simple preoperative parameters, for patients with an advanced stage of ovarian cancer who are at risk of suboptimal cytoreduction despite maximal surgical effort.
  
  
  METHODS
  Retrospective analysis of 187 consecutive patients with a suspected clinical diagnosis of advanced-stage ovarian cancer undergoing upfront debulking between January 1998 and December 2003. Preoperative parameters were Karnofsky performance status, ascites and serum concentrations of CA 125, hemoglobin, albumin, LDH and blood platelets. The main outcome parameter was residual tumor >1 cm. Univariate and multivariate logistic regression was employed for testing possible prediction models. A clinically applicable graphic model (nomogram) for this prediction was to be developed.
  
  
  RESULTS
  Serum concentrations of CA 125 and blood platelets in the group with residual tumor >1 cm were higher in comparison to the optimally cytoreduced group (p < 0.0001 and <0.01, respectively). Serum albumin and hemoglobin levels were lower in the group with residual tumor (p < 0.0001 and <0.05, respectively). The frequency of preoperative ascites was higher in the group with residual tumor (p < 0.0005). The prediction model, consisting of CA 125 and albumin, for remaining with residual tumor showed an area under the receiver operating characteristics curve of 0.79. A nomogram for probability of residual tumor >1 cm based on serum levels of CA 125 and albumin was established.
  
  
  CONCLUSIONS
  Postoperative residual tumor despite maximal surgical effort can be predicted by preoperative CA 125 and serum albumin levels. With a nomogram based on these two parameters, probability of postoperative residual tumor in each individual patient can be predicted. This proposed nomogram may be valuable in daily routine practice for counseling and to select treatment modality.
authors.affiliation: Department of Public Health, Erasmus University Medical Center, Rotterdam, The Netherlands.
authors.forename: D
authors.initials: D
authors.lastname: de Jong
authors.forename: M J
authors.initials: MJ
authors.lastname: Eijkemans
authors.forename: S
authors.initials: S
authors.lastname: Lie Fong
authors.forename: C G
authors.initials: CG
authors.lastname: Gerestein
authors.forename: G S
authors.initials: GS
authors.lastname: Kooi
authors.forename: A
authors.initials: A
authors.lastname: Baalbergen
authors.forename: M E L
authors.initials: ME
authors.lastname: van der Burg
authors.forename: C W
authors.initials: CW
authors.lastname: Burger
authors.forename: A C
authors.initials: AC
authors.lastname: Ansink
mesh_terms: D000368:Aged; D015415:Biomarkers / Q000097:blood; D018394:CA-125 Antigen / Q000097:blood*; D005260:Female; D006801:Humans; D008875:Middle Aged; D008954:Models, Biological; D018365:Neoplasm, Residual / Q000097:blood / Q000175:diagnosis*; D049451:Nomograms; D010051:Ovarian Neoplasms / Q000097:blood / Q000175:diagnosis / Q000473:pathology / Q000601:surgery*; D011237:Predictive Value of Tests; D011300:Preoperative Care; D012189:Retrospective Studies; D012709:Serum Albumin / Q000032:analysis*
chemical_list: D015415:Biomarkers; D018394:CA-125 Antigen; D012709:Serum Albumin