[A nomogram to predict non-sentinel lymph node metastasis for breast cancer patients with positive axillary sentinel lymph node].
Zhonghua Zhong Liu Za Zhi
; 42(8): 653-659, 2020 Aug 23.
Article
in Zh
| MEDLINE
| ID: mdl-32867457
ABSTRACT
Objective:
To identify the risk factors of non-sentinel lymph node (nSLN) metastasis in breast cancer patients with 1~2 positive axillary sentinel lymph node (SLN) and construct an accurate prediction model.Methods:
Retrospective chart review was performed in 917 breast cancer patients who underwent surgery treatment between 2002 and 2017 and pathologically confirmed 1-2 positive SLNs. According to the date of surgery, patients were divided into training group (497 cases) and validation group (420 cases). A nomogram was built to predict nSLN metastasis and the accuracy of the model was validated.Results:
Among the 917 patients, 251 (27.4%) had nSLN metastasis. Univariate analysis showed tumor grade, lymphovascular invasion (LVI), extra-capsular extension (ECE), the number of positive and negative SLN and macro-metastasis of SLN were associated with nSLN metastasis (all P<0.05). Multivariate Logistic regression analysis showed the numbers of positive SLN, negative SLN and macro-metastasis of SLN were independent predictors of nSLN metastasis (all P<0.05). A nomogram was constructed based on the 6 factors. The area under the receiver operating characteristic curve was 0.718 for the training group and 0.742 for the validation group.Conclusion:
We have developed a nomogram that uses 6 risk factors commonly available to accurately estimate the likelihood of nSLN metastasis for individual patient, which might be helpful for radiation oncologists to make a decision on regional nodal irradiation.Key words
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Main subject:
Breast Neoplasms
/
Sentinel Lymph Node Biopsy
/
Nomograms
/
Sentinel Lymph Node
/
Lymph Node Excision
/
Lymphatic Metastasis
Type of study:
Observational_studies
/
Prognostic_studies
/
Risk_factors_studies
Limits:
Humans
Language:
Zh
Journal:
Zhonghua Zhong Liu Za Zhi
Year:
2020
Document type:
Article
Affiliation country:
China