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.
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.
Authors: G M Nieuwenhuyzen-de Boer; W Hofhuis; N Reesink-Peters; S Willemsen; I A Boere; I G Schoots; J M J Piek; L N Hofman; J J Beltman; W J van Driel; H M J Werner; A Baalbergen; A M L D van Haaften-de Jong; M Dorman; L Haans; I Nedelcu; P C Ewing-Graham; H J van Beekhuizen Journal: Ann Surg Oncol Date: 2022-05-13 Impact factor: 4.339
Authors: Joline F Roze; Jacob P Hoogendam; Fleur T van de Wetering; René Spijker; Leen Verleye; Joan Vlayen; Wouter B Veldhuis; Rob Jpm Scholten; Ronald P Zweemer Journal: Cochrane Database Syst Rev Date: 2018-10-08
Authors: Isabelle Thomassin-Naggara; Edouard Poncelet; Aurelie Jalaguier-Coudray; Adalgisa Guerra; Laure S Fournier; Sanja Stojanovic; Ingrid Millet; Nishat Bharwani; Valerie Juhan; Teresa M Cunha; Gabriele Masselli; Corinne Balleyguier; Caroline Malhaire; Nicolas F Perrot; Elizabeth A Sadowski; Marc Bazot; Patrice Taourel; Raphaël Porcher; Emile Darai; Caroline Reinhold; Andrea G Rockall Journal: JAMA Netw Open Date: 2020-01-03