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Multi-Institutional Reciprocal Validation Study of Computed Tomography Predictors of Suboptimal Primary Cytoreduction in Patients With Advanced Ovarian Cancer

Allison E. Axtell, Margaret H. Lee, Robert E. Bristow, Sean C. Dowdy, William A. Cliby, Steven Raman, John P. Weaver, Mojan Gabbay, Michael Ngo, Scott Lentz, Ilana Cass, Andrew J. Li, Beth Y. Karlan, Christine H. Holschneider

From the University of California Los Angeles (UCLA) Medical Center; Olive View-UCLA Medical Center; Cedars-Sinai Medical Center; Kaiser Permanente Sunset Medical Center, Los Angeles, CA; Johns Hopkins Medical Institutions, Baltimore, MD; and the Mayo Clinic, Rochester, MN

Address reprint requests to Christine H. Holschneider, MD, Olive View-UCLA Medical Center, Department of Obstetrics and Gynecology, 14445 Olive View Dr, Rm 2B-163, Sylmar, CA 91342; e-mail: CHolschneider{at}ladhs.org

Purpose Identify features on preoperative computed tomography (CT) scans to predict suboptimal primary cytoreduction in patients treated for advanced ovarian cancer in institution A. Reciprocally cross validate the predictors identified with those from two previously published cohorts from institutions B and C.

Patients and Methods Preoperative CT scans from patients with stage III/IV epithelial ovarian cancer who underwent primary cytoreduction in institution A between 1999 and 2005 were retrospectively reviewed by radiologists blinded to surgical outcome. Fourteen criteria were assessed. Crossvalidation was performed by applying predictive model A to the patients from cohorts B and C, and reciprocally applying predictive models B and C to cohort A.

Results Sixty-five patients from institution A were included. The rate of optimal cytoreduction ( 1 cm residual disease) was 78%. Diaphragm disease and large bowel mesentery implants were the only CT predictors of suboptimal cytoreduction on univariate (P < .02) and multivariate analysis (P < .02). In combination (model A), these predictors had a sensitivity of 79%, a specificity of 75%, and an accuracy of 77% for suboptimal cytoreduction. When model A was applied to cohorts B and C, accuracy rates dropped to 34% and 64%, respectively. Reciprocally, models B and C had accuracy rates of 93% and 79% in their original cohorts, which fell to 74% and 48% in cohort A.

Conclusion The high accuracy rates of CT predictors of suboptimal cytoreduction in the original cohorts could not be confirmed in the cross validation. Preoperative CT predictors should be used with caution when deciding between surgical cytoreduction and neoadjuvant chemotherapy.

Presented in part during plenary presentations at the 34th Annual Meeting of the Western Association of Gynecologic Oncologists, Santa Fe, NM, June 15-18, 2005; and at the 37th Annual Meeting of the Society of Gynecologic Oncologists, Palm Springs, CA, March 22-26, 2006.

Authors' disclosures of potential conflicts of interest and author contributions are found at the end of this article.

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