Abstract:
OBJECTIVES: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. CONCLUSION: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.
journal_name
Oncologyjournal_title
Oncologyauthors
de Jong D,Eijkemans MJ,Lie Fong S,Gerestein CG,Kooi GS,Baalbergen A,van der Burg ME,Burger CW,Ansink ACdoi
10.1159/000113051subject
Has Abstractpub_date
2007-01-01 00:00:00pages
293-301issue
5-6eissn
0030-2414issn
1423-0232pii
000113051journal_volume
72pub_type
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