Borley J, Wilhelm-Benartzi C, Yazbek J, Williamson R, Bharwani N, Stewart V, Carson I, Hird E, McIndoe A, Farthing A, Blagden S, Ghaem-Maghami S. Radiological predictors of cytoreductive outcomes in patients with advanced ovarian cancer.
BJOG 2015;
122:843-849. [PMID:
25132394 DOI:
10.1111/1471-0528.12992]
[Citation(s) in RCA: 30] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/10/2014] [Indexed: 11/29/2022]
Abstract
OBJECTIVE
To assess site of disease on preoperative computed tomography (CT) to predict surgical debulking in patients with ovarian cancer.
DESIGN
Two-phase retrospective cohort study.
SETTING
West London Gynaecological Cancer Centre, UK.
POPULATION
Women with stage 3 or 4, ovarian, fallopian or primary peritoneal cancer undergoing cytoreductive surgery.
METHODS
Preoperative CT images were reviewed by experienced radiologists to assess the presence or absence of disease at predetermined sites. Multivariable stepwise logistic regression models determined sites of disease which were significantly associated with surgical outcomes in the test (n = 111) and validation (n = 70) sets.
MAIN OUTCOME MEASURES
Sensitivity and specificity of CT in predicting surgical outcome.
RESULTS
Stepwise logistic regression identified that the presence of lung metastasis, pleural effusion, deposits on the large-bowel mesentery and small-bowel mesentery, and infrarenal para-aortic nodes were associated with debulking status. Logistic regression determined a surgical predictive score which was able to significantly predict suboptimal debulking (n = 94, P = 0.0001) with an area under the curve (AUC) of 0.749 (95% confidence interval [95% CI]: 0.652, 0.846) and a sensitivity of 69.2%, specificity of 71.4%, positive predictive value of 75.0% and negative predictive value of 65.2%. These results remained significant in a recent validation set. There was a significant difference in residual disease volume in the test and validation sets (P < 0.001) in keeping with improved optimal debulking rates.
CONCLUSIONS
The presence of disease at some sites on preoperative CT scan is significantly associated with suboptimal debulking and may be an indication for a change in surgical planning.
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