Sentinel Lymph Node Biopsy Mapped With Carbon Nanoparticle Suspensions in Patients With Breast Cancer: A Systematic Review and Meta-Analysis
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Updated: Sep 27, 2025
Sentinel Lymph Node Mapping and Biopsy for Endometrial Cancer at Early Stage with Laparoscopy
Published on: August 19, 2021
Yan Jiang1, Jiayang Li2, Baolin Chen1
1Breast and Thyroid Surgery, Department of General Surgery, The Affiliated Hospital of Zunyi Medical University, Zunyi, China.
Background:
The mapping method represents a crucial factor affecting the rate of sentinel lymph node detection in breast cancer. We carried out this meta-analysis to assess the clinical utility of carbon nanoparticle suspensions (CNSs) in guiding sentinel lymph node biopsy (SLNB) for breast cancer patients.
Methods:
Electronic databases, which comprised the China National Knowledge Infrastructure, the Wanfang electronic database, the Cochrane Library, EMBASE, and PubMed, were explored to identify relevant studies from database inception to July 2021 that studied the detection rate of CNSs-guided SLNB. A meta-analysis was performed to generate pooled sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), a summary receiver operator characteristic curve (SROC), and a diagnostic odds ratio (DOR).
Results:
A total of 33 publications that enrolled 2,171 patients were analyzed. The pooled sensitivity, specificity, PLR, and NLR were 0.93 (95% CI: 0.91-0.95, I = 0.0%), 0.99 (95% CI: 0.98-0.99, I = 56.5%), 42.85 (95% CI: 29.73-61.77, I = 47.0%), and 0.09 (95% CI: 0.07-0.11, I = 0.0%), respectively. The area under the curve (AUC) of the SROC curve was 0.98. There were no significant differences when analyzed based on the dose and site of CNS injection. There was significant publication bias among the included publications based on Deeks' funnel plot [Slope (Bias) = -7.35, P = 0.00]. Nonetheless, the sensitivity analysis identified the results to be reliable and stable.
Conclusion:
This meta-analysis highlights the accuracy and feasibility of using CNSs for SLNB in patients with breast cancer. Clinically, the identification and predictive values of CNSs as an optimal tracer for SLNB remains undisputed.
