Document Type

Article

Publication Date

8-22-2018

Comments

This article has been peer reviewed. It is the authors' final version prior to publication in Journal of Surgical Research,Volume 233, August 2018, Pages 149-153.

The published version is available at https://doi.org/10.1016/j.jss.2018.07.042. Copyright © Elsevier

Abstract

Introduction: Sentinel lymph node biopsy (SLNB) is an important adjunct in the staging of patients with melanoma. Preoperative lymphoscintigraphy (LS) with radiolabeled isotopes is essential to localize sentinel nodes for removal. Our study compared the effectiveness of Lymphoseek to standard sulfur colloids (SC) in patients with melanoma undergoing SLNB.

Methods: We queried our IRB-approved melanoma database to identify 370 consecutive patients who underwent SLNB from 2012-2016 with at least one year of follow up. There were 185 patients in each group. Data points included characteristics of the primary melanoma lymphoscintigraphy, and SLNB. Student’s t-test and Chi-Square were used to analyze the data with a p-value of <0.05 being considered significant.

Results: Patients were equally matched in regard to age, sex, and primary characteristics of their melanoma. In comparison to SC, Lymphoseek required lower radiation dosages (p<0.001), shorter mapping times (p=0.008), and decreased number of sentinel nodes removed (p=0.03). There was no difference in the number of patients with positive nodes (p=0.5). Additionally, there were no statistical differences between the two radioactive tracers in regard to the number of patients with false negative SLNB.

Conclusion: Lymphoseek has the potential to decrease radioactivity and mapping time in patients who need SLNB. With a decrease in the number of nodes removed without loss of sensitivity, there is a potential to avoid unnecessary node removal and thus complications such as lymphedema. Longer follow-up will help to determine if there is any increase in false negative rates despite fewer nodes removed.

Creative Commons License

Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Language

English

Available for download on Thursday, August 22, 2019

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