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 Christopher Dowdy, William Arthur Cliby, Steven Raman, John P. Weaver, Mojan Gabbay, Michael Ngo, Scott Lentz, Ilana Cass, Andrew J. Li, Beth Y. Karlan, Christine H. Holschneider

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Abstract

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.

Original languageEnglish (US)
Pages (from-to)384-389
Number of pages6
JournalJournal of Clinical Oncology
Volume25
Issue number4
DOIs
StatePublished - Feb 1 2007

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Validation Studies
Ovarian Neoplasms
Tomography
Mesentery
Diaphragm
Multivariate Analysis
Drug Therapy

ASJC Scopus subject areas

  • Cancer Research
  • Oncology
  • Medicine(all)

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Multi-institutional reciprocal validation study of computed tomography predictors of suboptimal primary cytoreduction in patients with advanced ovarian cancer. / Axtell, Allison E.; Lee, Margaret H.; Bristow, Robert E.; Dowdy, Sean Christopher; Cliby, William Arthur; Raman, Steven; Weaver, John P.; Gabbay, Mojan; Ngo, Michael; Lentz, Scott; Cass, Ilana; Li, Andrew J.; Karlan, Beth Y.; Holschneider, Christine H.

In: Journal of Clinical Oncology, Vol. 25, No. 4, 01.02.2007, p. 384-389.

Research output: Contribution to journalArticle

Axtell, AE, Lee, MH, Bristow, RE, Dowdy, SC, Cliby, WA, Raman, S, Weaver, JP, Gabbay, M, Ngo, M, Lentz, S, Cass, I, Li, AJ, Karlan, BY & Holschneider, CH 2007, 'Multi-institutional reciprocal validation study of computed tomography predictors of suboptimal primary cytoreduction in patients with advanced ovarian cancer', Journal of Clinical Oncology, vol. 25, no. 4, pp. 384-389. https://doi.org/10.1200/JCO.2006.07.7800
Axtell, Allison E. ; Lee, Margaret H. ; Bristow, Robert E. ; Dowdy, Sean Christopher ; Cliby, William Arthur ; Raman, Steven ; Weaver, John P. ; Gabbay, Mojan ; Ngo, Michael ; Lentz, Scott ; Cass, Ilana ; Li, Andrew J. ; Karlan, Beth Y. ; Holschneider, Christine H. / Multi-institutional reciprocal validation study of computed tomography predictors of suboptimal primary cytoreduction in patients with advanced ovarian cancer. In: Journal of Clinical Oncology. 2007 ; Vol. 25, No. 4. pp. 384-389.
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abstract = "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.",
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T1 - Multi-institutional reciprocal validation study of computed tomography predictors of suboptimal primary cytoreduction in patients with advanced ovarian cancer

AU - Axtell, Allison E.

AU - Lee, Margaret H.

AU - Bristow, Robert E.

AU - Dowdy, Sean Christopher

AU - Cliby, William Arthur

AU - Raman, Steven

AU - Weaver, John P.

AU - Gabbay, Mojan

AU - Ngo, Michael

AU - Lentz, Scott

AU - Cass, Ilana

AU - Li, Andrew J.

AU - Karlan, Beth Y.

AU - Holschneider, Christine H.

PY - 2007/2/1

Y1 - 2007/2/1

N2 - 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.

AB - 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.

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