Establishing a prediction model of axillary nodal burden based on the combination of CT and ultrasound findings and the clinicopathological features in patients with early-stage breast cancer

Abstract

Background: Axillary lymph node (ALN) management in early-stage breast cancer (ESBC) patients has become less invasive during the past decades. Here, we tried to explore whether high nodal burden (HNB) in ESBC patients could be predicted preoperatively, so as to avoid unnecessary sentinel lymph node biopsy (SLNB).

Methods: The clinicopathological and imaging data of patients with early invasive breast cancer (cT_1-2N₀M₀) were analyzed retrospectively. Univariate and multivariate analyses were performed for the risk factors of axillary HNB in ESBC patients, and a risk prediction model of HNB was established.

Results: HNB was identified in 105 (8.0%) of 1,300 ESBC patients. Multivariate analysis showed that estrogen receptors (ER) status, human epidermal growth factor receptor 2 (HER2) status, number of abnormal lymph nodes (LNs) on computed tomography (CT), and axillary score on ultrasound (US) were the risk factors of HNB (all P<0.05). The area under the receiver operating characteristic (ROC) curve in the prediction model was 0.914, with the sensitivity being 85.7% and the specificity being 82.4%. The calibration curve showed that the prediction model had good performance.

Conclusions: As a valuable tool for predicting HNB in ESBC patients, this newly established model helps clinicians to make reasonable axillary surgery decisions and thus avoid unnecessary SLNB.

Keywords: High nodal burden; axillary lymph node dissection (ALND); early-stage breast cancer (ESBC); sentinel lymph node (SLN).

Figure 1

Sonography of lymph nodes (The green color indicates the starting point of the short axis of the axillary LNs). (A) A 53-year-old woman with invasive carcinoma in her left breast. Horizontal gray scale US of the left axillary LNs shows (I) a long-to-short axis ratio ≤2 (1 point), (II) the loss of fatty hilum (2 points), and (III) a maximum cortical thickness ≥0.3 cm (1 point). The total score of axillary LNs is 4 points on US (arrow). (B) A 47-year-old woman with invasive carcinoma in her right breast. Horizontal grayscale US of the right axillary LNs shows (I) a long-to-short axis ratio ≤2 (1 point), (II) uneven presence of fatty hilum (1 point); and a (III) maximum cortical thickness ≥0.3 cm (1 point). The total score of axillary LNs is 3 points on US (arrow). LN, lymph node; US, ultrasound.

Figure 2

Lymph nodes on CT. (A) A 50-year-old woman with invasive carcinoma of the right breast. Axial CT shows that the level I LNs at the right axillary are normal, the fatty hilum are evenly present, and the maximum cortical thickness is <0.3 cm (arrow). (B) A 48-year-old woman with invasive carcinoma of the left breast. Axial CT shows that the level I LNs at the left axillary are abnormal, the fatty hilum has disappeared, and the maximum cortical thickness is ≥0.3 cm (arrows). CT, computed tomography; LN, lymph node.

Figure 3

Study flow. ALND, axillary lymph node dissection; HNB, high nodal burden; LNB, low nodal burden.

Figure 4

ROC curve for predicting high nodal burden in early-stage breast cancer. The AUC was 0.914. ROC, receiver operating characteristic; AUC, area under the curve.

Figure 5

Nomogram for predicting the probability of HNB in early-stage breast cancer. US, ultrasound; LNs, lymph nodes; CT, computed tomography; ER, estrogen receptor; HER2, human epidermal growth factor receptor 2; HNB, high nodal burden.

Figure 6

Calibration plot of the nomogram.