search button
Open Access

A model for the early identification of sentinel lymph node metastasis in patients with breast cancer based on contrast‑enhanced ultrasound and clinical features

  • Authors:
    • Juan Xu
    • Junzhi Li

  • View Affiliations

  • Published online on: September 8, 2022     https://doi.org/10.3892/ol.2022.13498
  • Article Number: 378

  • Copyright: © Xu et al. This is an open access article distributed under the terms of Creative Commons Attribution License.

Metrics: Total Views: 0 (Spandidos Publications: | PMC Statistics: )
Total PDF Downloads: 0 (Spandidos Publications: | PMC Statistics: )


Abstract

The present study was designed to establish a model for the early identification of sentinel lymph node (SLN) metastasis in patients with breast cancer (BC). The SLN metastasis predictive model was established with a retrospective training set of 365 patients with BC and was re‑evaluated using a prospective validation set of 402 patients with BC. The multivariable analysis indicated that the tumor diameter [odds ratio (OR), 1.189; 95% confidence interval (CI), 1.124‑1.257; P<0.001], menopause (OR, 1.011; 95% CI, 0.603‑1.436; P<0.001), estrogen receptor (ER) expression (OR, 3.199; 95% CI, 1.077‑6.567; P=0.043) and contrast‑enhanced ultrasonography (CEUS) type (OR, 10.563; 95% CI, 6.890‑28.372; P<0.001) were independent predictors of SLN status in patients with BC. The SLN metastasis predictive model was as follows: (0.173 x tumor diameter)‑(4.490 x menopause) + (2.322 x ER) + (5.445 x CEUS type)‑1.9521. In the training set, the model was highly sensitive (83.6%) and specific (94.3%) for the early identification of SLN metastasis. Similarly, in the validation set, the model was highly sensitive (70.4%) and specific (89.5%) for the early identification of SLN metastasis in patients with BC. Overall, in the present study, a model was successfully established to predict SLN metastasis in patients with BC that includes tumor diameter, menopausal status, ER expression and CEUS detection.
View Figures
View References

Related Articles

Journal Cover

October-2022
Volume 24 Issue 4

Print ISSN: 1792-1074
Online ISSN:1792-1082

Sign up for eToc alerts

Recommend to Library

  • Journal Metrics
  • Impact Factor: 2.5
  • Ranked Oncology
    (total number of cites)
  • CiteScore: 5.7
  • CiteScore Rank: Q2: #139/404 Oncology
  • Source Normalized Impact per Paper (SNIP): 0.574
  • SCImago Journal Rank (SJR): 0.644
International Symposium on Molecular Medicine Conference Banner
The Cancer Story
World Congress on Advances in Oncology and International Symposium on Molecular Medicine Conference Banner
World Academy Of Sciences Banner
Heyday Road Banner

0

Copy and paste a formatted citation
x
Spandidos Publications style
Xu J and Li J: A model for the early identification of sentinel lymph node metastasis in patients with breast cancer based on contrast‑enhanced ultrasound and clinical features. Oncol Lett 24: 378, 2022.
APA
Xu, J., & Li, J. (2022). A model for the early identification of sentinel lymph node metastasis in patients with breast cancer based on contrast‑enhanced ultrasound and clinical features. Oncology Letters, 24, 378. https://doi.org/10.3892/ol.2022.13498
MLA
Xu, J., Li, J."A model for the early identification of sentinel lymph node metastasis in patients with breast cancer based on contrast‑enhanced ultrasound and clinical features". Oncology Letters 24.4 (2022): 378.
Chicago
Xu, J., Li, J."A model for the early identification of sentinel lymph node metastasis in patients with breast cancer based on contrast‑enhanced ultrasound and clinical features". Oncology Letters 24, no. 4 (2022): 378. https://doi.org/10.3892/ol.2022.13498