Background: Lymphadenectomy is important in the surgical treatment of apparent early epithelial ovarian cancers (eEOC); however, its extent is not well defined. We evaluated the role of systematic lymphadenectomy, the risk factors related with lymph node metastases, the implications, and the morbidity of comprehensive surgical staging.
Methods: We prospectively recruited 124 patients diagnosed with apparent eEOC [International Federation of Gynecology and Obstetrics (FIGO) stage I and II] between January 2003 and January 2011. Demographics, surgical procedures, morbidities, pathologic findings, and correlations with lymph node metastases were assessed.
Results: A total of 111 patients underwent complete surgical staging, including lymphadenectomy, and were therefore analyzed. A median of 23 pelvic and 20 para-aortic nodes were removed. Node metastases were found in 15 patients (13.5 %). The para-aortic region was involved in 13 (86.6 %) of 15 cases. At univariate analysis, age, menopause, FIGO stage, grading, and laterality were found to be significant factors for lymph node metastases, while CA125 of >35 U/ml and positive cytology were not. No lymph node metastases were found in mucinous histotypes. At multivariate analysis, only bilaterality (p = 0.018) and menopause (p = 0.032) maintained a statistically significant association with lymph node metastases. Lymphadenectomy-related complications (lymphocyst formation and lymphorrhea) were found in 14.4 % patients.
Conclusions: The data of this prospective study demonstrate the prognostic value of lymphadenectomy in eEOC. Menopause, age, bilaterality, histology, and tumor grade are identifiable factors that can help the surgeon decide whether to perform comprehensive surgical staging with lymph node dissection. These parameters may be used in planning subsequent treatment.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1245/s10434-012-2439-7 | DOI Listing |
JAMA Surg
January 2025
Department of General and Minimally Invasive Surgery, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy.
Eur Radiol
January 2025
Department of Urological Surgical, JiangNan University Medical Center, Wuxi, China.
Objective: To conduct a meta-analysis assessing the diagnostic performance of the node reporting and data system (Node-RADS) for detecting lymph node (LN) invasion.
Method: We performed a systematic literature search of online scientific publication databases from inception up to July 31, 2024. We used the quality assessment of diagnostic accuracy studies-2 (QUADAS-2) to assess the study quality, and heterogeneity was determined by the Q-test and measured with I statistics.
Ann Surg Oncol
January 2025
Department of Surgery, University of California San Diego, La Jolla, CA, USA.
Background: Gastric cancer poses a major diagnostic and therapeutic challenge. Improved visualization of tumor margins and lymph node metastases with tumor-specific fluorescent markers could improve outcomes.
Methods: To establish orthotopic models of gastric cancer, one million cells of the human gastric cancer cell line, MKN45, were suspended in 50 μl of equal parts PBS and Matrigel and injected into the nude mouse stomach with a 29-gauge needle.
J Cancer Res Clin Oncol
January 2025
Department of Pathology, Theodor Bilharz Research Institute, Giza, 12411, Egypt.
Introduction: Pancreatic ductal adenocarcinoma (PDAC) is associated with poor prognosis. The roles of the transcription factor special AT-rich binding protein-2 (SATB2) and β-catenin in PDAC have been a subject of controversy. We aimed to assess the diagnostic and prognostic impact of SATB2 and β-catenin in PDAC.
View Article and Find Full Text PDFInt J Gynecol Cancer
January 2025
Division of Gynecologic Oncology, Koc University School of Medicine, Istanbul, Turkey.
Objective: This research was undertaken to identify risk factors for the involvement of sentinel lymph nodes (SLNs) in cases of endometrial cancer.
Methods: From February 2016 to April 2021, the cases of 874 women with endometrial cancer treated with the SLN algorithm at 11 institutions were analyzed in this retrospective study. Clinical and pathologic data were reviewed, and logistic regression was applied to identify predictive factors for SLN involvement.
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!