Preoperative ct or pet/ct to assess pelvic and para-aortic lymph node status in epithelial ovarian cancer? A systematic review and meta-analysis

International audienceBackground: In advanced epithelial ovarian cancer (EOC), the LION trial restricted lym-phadenectomy indication to patients with suspect lymph nodes before and during surgery. Preoperative imaging is used to assess lymph node status, and particularly CT and PET/CT. The aim of this systematic review and meta-analysis was to evaluate the diagnostic accuracy of preoperative CT and PET/CT to detect lymph node metastasis (LNM) in patients with EOC;Methods: Databases were searched from January 1990 to May 2019 for studies that evaluated the diagnostic accuracy of preoperative CT and PET/CT to detect LNM in patients with EOC with histology as the gold standard. Pooled diagnostic accuracy was calculated using bivariate random-effects models and hierarchical summary receiver operating curve (HSROC). This study is registered with PROSPERO number CRD42020179214Results: A total of five studies were included in the meta-analysis: four articles concerned preoperative CT and four articles concerned preoperative PET/CT, involving 106 and 138 patients, respectively. For preoperative CT, pooled sensitivity was 0.47 95% CI [0.20–0.76], pooled specificity was 0.99 95% CI [0.75–1.00] and area under the curve (AUC) of the HSROC was 0.91 95% CI [0.88–0.93]. For preoperative PET/CT, pooled sensitivity was 0.81 95% CI [0.61–0.92], pooled specificity was 0.96 95% CI [0.91–0.99] and AUC of the HSROC was 0.97 95% CI [0.95–0.98]Conclusions: PET/CT has a very high diagnostic accuracy, especially for specificity, to detect LNM in EOC and should be realized systematically, additionally to CT recommended to evaluate peritoneal spread, in the preoperative staging of patients with an advanced disease

A pre-operative score to discriminate fibroepithelial lesions of the breast: Phyllode tumor or fibroadenoma?

International audienceBackground/Aim: Fibroepithelial lesions (FEL) of the breast include fibroadenomas and phyllodes tumors (PT). Their histologic characteristics on core needle biopsy can overlap, while their clinical management is different. The aim of this study was to develop and to validate a pre-operative score for the diagnosis of PT with surgical decision rules. Patients and Methods: We developed a pre-operative score for the diagnosis of PT by performing logistic regression on 217 FEL of the Rene Huguenin Hospital. This score and the surgical decision rules were validated on 87 FEL of the Lariboisiere Hospital. Results: Three variables were independently and significantly associated with PT: Age ≤40 years, mammography's tumor size ≤3 cm and PT diagnosed by CNB. The pre-operative score was based on these three criteria with values ranging from 0 to 10. Surgical decision rules were created: The low-risk group of PT (score≥2) had a sensitivity of 92.6% and a LR-of 0.2, the high-risk group (score>7) had a specificity of 93.5% and a LR+ of 4.4. In the validation sample, surgical decision rules were applied. Conclusion: These surgical decision rules may prove useful in deciding which FEL needs surgical resection

A pre-operative radiological score to predict lymph node metastasis in advanced epithelial ovarian cancer

International audienceBackground: Lymphadenectomy is part of cytoreductive surgery for patients with advanced epithelial ovarian cancer (AEOC) in case of abnormal lymph nodes before and during surgery. The aim of this study was to develop and validate a pre-operative radiological score to predict pelvic and/or para-aortic lymph node metastasis (LNM) in patients with AEOC undergoing cytoreductive surgery. Methods: We conducted a multicentre retrospective study. The construction sample was composed of 53 patients operated within two referral centers. The validation sample was composed of 39 patients operated in a third referral center. The score was built with a logistic regression model with internal validation by bootstrap. Results: Two variables were associated with the prediction of pelvic and/or para-aortic LNM at computerized tomography (CT) and/or positron emission tomography (PET/CT): “para-aortic lymph node involvement” (adjusted diagnostic odds ratio) (aDOR) = 8.77 95CI [1.42–54.09], p = 0.02) and “colon involvement” (aDOR = 7.97 95CI [1.28–49.58], p = 0.03). Bootstrap procedure showed that the model was stable. The 2-points LNM pre-operative radiological score was derived from these 2 radiological variables and a high-risk group was identified for a score ≥ 1: the probability of pelvic and/or para-aortic LNM was 76%, the specificity was 85.7% 95CI [67.3–96.0] and the positive likelihood ratio was 3.6 95CI [1.4–9.7]. In the validation sample, a score ≥ 1 had a specificity of 78.3% and a LR+ of 1.2. Conclusion: LNM pre-operative radiological score could help the surgeon's decision to perform pelvic and para-aortic lymphadenectomy in patients with AEOC undergoing cytoreductive surgery. Trial registration: The research protocol was approved by the Ethics Committee for Research in Obstetrics and Gynecology (CEROG 2016-GYN 1003)

Using a new diagnostic tool to predict lymph node metastasis in advanced epithelial ovarian cancer leads to simple lymphadenectomy decision rules: A multicentre study from the francogyn group

International audienceObjective The aim of this study was to develop a new diagnostic tool to predict lymph node metastasis (LNM) in patients with advanced epithelial ovarian cancer undergoing primary cytoreductive surgery. Materials and method The FRANCOGYN group’s multicenter retrospective ovarian cancer cohort furnished the patient population on which we developed a logistic regression model. The prediction model equation enabled us to create LNM risk groups with simple lymphadenectomy decision rules associated with a user-friendly free interactive web application called shinyLNM. Results 277 patients from the FRANCOGYN cohort were included; 115 with no LNM and 162 with LNM. Three variables were independently and significantly (p<0.05) associated with LNM in multivariate analysis: pelvic and/or para-aortic LNM on CT and/or PET/CT (p<0.00), initial PCI ≥ 10 and/or diaphragmatic carcinosis (p = 0.02), and initial CA125 ≥ 500 (p = 0.02). The ROC-AUC of this prediction model after leave-one-out cross-validation was 0.72. There was no difference between the predicted and the observed probabilities of LNM (p = 0.09). Specificity for the group at high risk of LNM was 83.5%, the LR+ was 2.73, and the observed probability of LNM was 79.3%; sensitivity for the group at low-risk of LNM was 92.0%, the LR- was 0.24, and the observed probability of LNM was 25.0%. Conclusion This new tool may prove useful for improving surgical planning and provide useful information for patients. Copyright