Accuracy of Sentinel Lymph Node Biopsy in Nodal Staging of High Risk Endometrial Cancer (EndoSLN)
|Endometrial Cancer Sentinel Lymph Node Indocyanine Green||Biological: Indocyanine Green (ICG)|
|Study Design:||Intervention Model: Single Group Assignment
Masking: None (Open Label)
Primary Purpose: Diagnostic
|Official Title:||Accuracy of Sentinel Lymph Node Biopsy in Nodal Staging of High Risk Endometrial Cancer: A Prospective Trial|
- Performance Analysis [ Time Frame: Year 3 ]Performance analyses of SLN mapping will be performed. In particular, sensitivity, specificity, and predictive accuracy of mapping and detection of sentinel lymph nodes with metastatic disease will be calculated using the pathology results of the surgical intervention as the Standard of Reference. Performance analyses will be evaluated at both the lesion and patient level. Generalized estimating equations will be used to adjust for correlations of repeated measures within patients. Raw performance estimates will be reported with adjusted 95% confidence intervals.
|Study Start Date:||March 2012|
|Estimated Study Completion Date:||June 2018|
|Estimated Primary Completion Date:||June 2018 (Final data collection date for primary outcome measure)|
Experimental: Indocyanine Green
All patients on study will have ICG injection for SLN mapping
Biological: Indocyanine Green (ICG)
ICG (Indocyanine Green) will be used as a fluorescent agent to identify sentinel lymph nodes intraoperatively. The ICG will be administered in solution (1.25mg/ml) as four 1ml injections into the cervix (superficial and deep) at 3 and 9 o'clock.
If the SLN can be accurately identified and the detection of metastatic lymph nodes in women with early stage high risk endometrial cancer can be improved then the majority of women could avoid a complete systematic pelvic lymphadenectomy. Pelvic lymphadenectomy is associated with many intraoperative and postoperative complications such as hemorrhage, lymphocyst formation, nerve injury and chronic lower extremity lymphedema. If less invasive techniques to assess regional lymph node involvement, such as SLN mapping, replaced routine pelvic lymphadenectomy the complications associated with more extensive pelvic surgery could be avoided.
This will be a prospective cohort study. The population to be studied will be patients with newly diagnosed early stage high risk endometrial cancer who will undergo primary surgical intervention that includes hysterectomy and bilateral pelvic and inframesenteric para-aortic lymphadenectomy via laparotomy, laparoscopy or robotic-assisted. Patients will be taken to the operating room for their planned procedure. After initiation of general anesthesia, fluorescent dye (indocyanine green, ICG) will be injected into the patient's cervix. The dye will be visualized by excitation with an infrared light (an attachment on the Novadaq Pinpoint system for laparoscopy). The surgery will proceed and all lymph nodes that are "green" will be removed surgically and their anatomic location and laterality documented. These "green" sentinel nodes will be assessed by a study pathologist by frozen section and the result read out intraoperatively. The hysterectomy and complete lymphadenectomy will then be performed. The SLN status will be compared to the status of the other nodes removed at complete lymphadenectomy. All data on these patients will be prospectively collected.
Please refer to this study by its ClinicalTrials.gov identifier: NCT01886066
|Contact: Sarah Ferguson, MD||416-946-4501 ext 6597||Sarah.Ferguson@uhn.ca|
|Contact: Aysha Zia||416-946-4658||Aysha.Zia@uhnresearch.ca|
|Sunnybrook Health Sciences Center||Recruiting|
|Toronto, Ontario, Canada, M4N3M5|
|Contact: Danielle Vicus, MD 416-480-4378 ext 4026 firstname.lastname@example.org|
|Contact: Gabrielle Ene 416-946-4501 ext 3969 Gabrielle.Ene@uhnresearch.ca|
|University Health Network - Princess Margaret Hospital||Recruiting|
|Toronto, Ontario, Canada, M5T 2M9|
|Contact: Sarah Ferguson, MD 416-946-4501 ext 6597 Sarah.Ferguson@uhn.ca|
|Contact: Aysha Zia 416-946-4658 Aysha.Zia@uhnresearch.ca|