Predictors of uncommon location of sentinel nodes in endometrial and cervical cancers.

Yfat Kadan, Alexandra Baron, Yoav Brezinov, Alon Ben Arie, Ami Fishman, Mario Beiner
Author Information
  1. Yfat Kadan: Gynecologic Oncology Division, Department of Obstetrics and Gynecology, HaEmek Medical Center, affiliated with Technion Institute of Technology, Haifa, Israel.
  2. Alexandra Baron: Gynecologic Oncology Division, Department of Obstetrics and Gynecology, Meir Medical Center, affiliated with Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel.
  3. Yoav Brezinov: Department of Obstetrics and Gynecology, Kaplan Medical Center, Rehovot, Affiliated to the Hebrew University, Medical School, Jerusalem, Israel.
  4. Alon Ben Arie: Department of Obstetrics and Gynecology, Kaplan Medical Center, Rehovot, Affiliated to the Hebrew University, Medical School, Jerusalem, Israel.
  5. Ami Fishman: Gynecologic Oncology Division, Department of Obstetrics and Gynecology, Meir Medical Center, affiliated with Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel.
  6. Mario Beiner: Gynecologic Oncology Division, Department of Obstetrics and Gynecology, Meir Medical Center, affiliated with Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel.

Abstract

OBJECTIVE: Sentinel node mapping is widely used in the treatment of gynecologic cancers. The current study aimed to identify predictors of uncommon sentinel lymph node (SLN) locations.
METHODS: The current study included women who were operated for endometrial or cervical cancer with attempted sentinel lymph node mapping during surgical staging. Data were collected from electronic charts. The pelvis and the external ilia and obturator basins were common node locations. Para-aortic, pre-sacral, common iliac, internal iliac, and parametrial nodes were considered uncommon locations. We conducted analyses stratified according to common, uncommon, and very uncommon (-aortic, pre-sacral, parametrial) node location sites.
RESULTS: A total of 304 women were enrolled in the current study; 15.8% had SLN in uncommon locations and 4.3% had very uncommon node locations. Body mass index (BMI) was a negative predictor for uncommon SLN locations (OR 0.88, p = 0.03). The use of either indocyanine green (ICG) or Tc & blue dye was an independent predictor for uncommon SLN locations (OR 8.24, p = 0.006). More recent surgeries and the presence of positive nodes were independent predictors for very uncommon node locations (OR 2.13, p = 0.011, and OR 9.3, p = 0.002, respectively).
CONCLUSIONS: BMI, tracer type, surgical year, and positive nodes were independent predictors for uncommon SLN locations. These findings suggest that surgical effort, technique and experience may result in better identification of uncommon SLN locations.

References

  1. Gynecol Oncol. 2017 Oct;147(1):18-23 [PMID: 28716308]
  2. Int J Gynecol Cancer. 2017 Jan;27(1):154-158 [PMID: 27792042]
  3. Gynecol Oncol. 2010 Jan;116(1):28-32 [PMID: 19875161]
  4. Gynecol Oncol. 2006 Oct;103(1):35-44 [PMID: 16600355]
  5. Lancet Oncol. 2017 Mar;18(3):384-392 [PMID: 28159465]
  6. Gynecol Oncol. 2019 Jul;154(1):102-109 [PMID: 31003746]
  7. Eur J Surg Oncol. 2015 Jan;41(1):1-20 [PMID: 25454828]
  8. Am J Obstet Gynecol. 2017 May;216(5):459-476.e10 [PMID: 27871836]

Word Cloud

Created with Highcharts 10.0.0uncommonlocationsnodeSLNnodesORp = 0currentstudypredictorssentinelsurgicalcommonindependentmappingcancerslymphwomenendometrialcervicalpre-sacraliliacparametriallocationBMIpredictorpositiveOBJECTIVE:SentinelwidelyusedtreatmentgynecologicaimedidentifyMETHODS:includedoperatedcancerattemptedstagingDatacollectedelectronicchartspelvisexternaliliaobturatorbasinsPara-aorticinternalconsideredconductedanalysesstratifiedaccording-aorticsitesRESULTS:total304enrolled158%43%Bodymassindexnegative08803useeitherindocyaninegreenICGTc&bluedye824006recentsurgeriespresence21301193002respectivelyCONCLUSIONS:tracertypeyearfindingssuggestefforttechniqueexperiencemayresultbetteridentificationPredictors

Similar Articles

Cited By (1)