Evidence map›Paper›PMID 36238843›Full record

ArticleOncology letters2022

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

Juan Xu, Junzhi Li

Abstract read
In one paragraph

Article in Oncology letters, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

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0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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5 · Who and what money

Authors and funding

2 authors.

Juan XuDepartment of Interventional Ultrasound, Cangzhou Central Hospital, Cangzhou, Hebei 061000, P.R. China.
Junzhi LiDepartment of Interventional Ultrasound, Cangzhou Central Hospital, Cangzhou, Hebei 061000, P.R. China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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 × tumor diameter)-(4.490 × menopause) + (2.322 × ER) + (5.445 × 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.

Indexed as

breast cancerclinical featurescontrast-enhanced ultrasonographysentinel lymph node metastasis

Identifiers

PMID36238843
PMCPMC9494614

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LicenceCC BY-NC-ND
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.