Micrometastases in Sentinel Lymph Nodes Represent a Significant Negative Prognostic Factor in Early-Stage Cervical Cancer: A Single-Institutional Retrospective Cohort Study.
Roman KocianJiri SlamaDaniela FischerovaAnna GermanovaAndrea BurgetovaLadislav DusekPavel DundrKristýna NěmejcovaJiri JarkovskySilvie SebestovaFilip FruhaufLukas DostalekTereza BallaschovaDavid CibulaPublished in: Cancers (2020)
The data on the prognostic significance of low volume metastases in lymph nodes (LN) are inconsistent. The aim of this study was to retrospectively analyze the outcome of a large group of patients treated with sentinel lymph node (SLN) biopsy at a single referral center. Patients with cervical cancer, stage T1a-T2b, common tumor types, negative LN on preoperative staging, treated by primary surgery between 01/2007 and 12/2016, with at least unilateral SLN detection were included. Patients with abandoned radical surgery due to intraoperative SLN positivity detected by frozen section were excluded. All SLNs were postoperatively processed by an intensive protocol for pathological ultrastaging. Altogether, 226 patients were analyzed. Positive LN were detected in 38 (17%) cases; macrometastases (MAC), micrometastases (MIC), isolated tumor cells (ITC) in 14, 16, and 8 patients. With the median follow-up of 65 months, 22 recurrences occurred. Disease-free survival (DFS) reached 90% in the whole group, 93% in LN-negative cases, 89% in cases with MAC, 69% with MIC, and 87% with ITC. The presence of MIC in SLN was associated with significantly decreased DFS and OS. Patients with MIC and MAC should be managed similarly, and SLN ultrastaging should become an integral part of the management of patients with early-stage cervical cancer.
Keyphrases
- sentinel lymph node
- lymph node
- early stage
- prognostic factors
- neoadjuvant chemotherapy
- free survival
- minimally invasive
- coronary artery bypass
- newly diagnosed
- end stage renal disease
- patients undergoing
- ejection fraction
- randomized controlled trial
- surgical site infection
- big data
- machine learning
- acute coronary syndrome
- label free
- percutaneous coronary intervention
- atrial fibrillation
- real time pcr