Estimation of Number of Involved Lymph Nodes in Breast Cancer Patients using Bayesian Regression Approach

Swain, Prafulla Kumar; Grover, Gurprit; Chakravorty, Sangeeta Sangeeta; Goel, Komal; Singh, Vikas

doi:10.18576/jsapl/040103

Cited by 1 publication

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“…Our results showed a trend that the risk of ALN metastases increases consistently with tumor size increases. This finding agrees with a recent study using Bayesian NBR 8 , and is also supported by several studies showing larger tumor size is correlated with an increased risk of a higher number of positive ALNs 10 , 26 . We may conclude that patients with different tumor sizes might undergo surgery to remove individual axillary nodes for refining treatment.…”

Section: Discussionsupporting

confidence: 93%

A negative binomial regression model for risk estimation of 0–2 axillary lymph node metastases in breast cancer patients

Zeng

Lin

Zhang

et al. 2020

Sci Rep

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Extensive clinical trials indicate that patients with negative sentinel lymph node biopsy do not need axillary lymph node dissection (ALND). However, the ACOSOG Z0011 trial indicates that patients with clinically negative axillary lymph nodes (ALNs) and 1–2 positive sentinel lymph nodes having breast conserving surgery with whole breast radiotherapy do not benefit from ALND. The aim of this study is therefore to identify those patients with 0–2 positive nodes who might avoid ALND. A total of 486 patients were eligible for the study with 212 patients in the modeling group and 274 patients in the validation group, respectively. Clinical lymph node status, histologic grade, estrogen receptor status, and human epidermal growth factor receptor 2 status were found to be significantly associated with ALN metastasis. A negative binomial regression (NBR) model was developed to predict the probability of having 0–2 ALN metastases with the area under the curve of 0.881 (95% confidence interval 0.829–0.921, P < 0.001) in the modeling group and 0.758 (95% confidence interval 0.702–0.807, P < 0.001) in the validation group. Decision curve analysis demonstrated that the model was clinically useful. The NBR model demonstrated adequate discriminative ability and clinical utility for predicting 0–2 ALN metastases.

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Section: Discussionsupporting

confidence: 93%