A multicenter validation of computerized tomography models as predictors of non- optimal primary cytoreduction of advanced epithelial ovarian cancer

O. Gemer*, M. Gdalevich, M. Ravid, B. Piura, A. Rabinovich, T. Gasper, A. Khashper, M. Voldarsky, L. Linov, I. Ben Shachar, E. Y. Anteby, O. Lavie

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

39 Scopus citations

Abstract

Aims: To compare the validity of four predictive models of preoperative computerized tomography (CT) scans in predicting suboptimal primary cytoreduction in patients treated for advanced ovarian cancer. Patients and methods: Preoperative CT scans of patients with stage III/IV epithelial ovarian cancer who underwent primary cytoreductive surgery at one of four medical centers were reviewed by radiologists blinded to surgical outcome. The validity of each set of CT criteria previously published by Nelson, Bristow, Dowdy, and Qayyum as predictors of suboptimal cytoreduction was assessed. Results: Data of 123 patients were evaluated. Optimal cytoreduction (largest diameter of residual tumor ≤1 cm) was obtained in 90 (73.2%) patients. All CT models were able to significantly predict surgical outcome (p < 0.02). The respective sensitivity, specificity, and accuracy of the CT models to predict sub-optimal cytoreduction was 64%, 64% and 64% for Nelson's criteria, 70%, 64% and 66% for Bristow's criteria, 79%, 60%, and 65% for Dowdy's criteria, and 67% 57% and 60% for Qayyum's criteria. Conclusions: Apart from Dowdy's criteria, the accuracy rates of CT predictors of suboptimal cytoreduction in the original cohorts could not be confirmed in this cross validation. This study underscores the difficulty in devising universally applicable selection criteria or models that reliably predict surgical outcome across institutions and surgeons.

Original languageEnglish
Pages (from-to)1109-1112
Number of pages4
JournalEuropean Journal of Surgical Oncology
Volume35
Issue number10
DOIs
StatePublished - Oct 2009
Externally publishedYes

Keywords

  • Computerized tomography
  • Debulking
  • Ovarian cancer
  • Prediction

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