Prediction score model for non-sentinel and four or more nodal metastases using a combined method of one-step nucleic acid amplification and histology in sentinel node-positive breast cancer patients

Clinical significance of discordances in sentinel lymph node reactivity between radioisotope and indocyanine green fluorescence in patients with cN0 breast cancer

BACKGROUND

/Objective: To evaluate the usefulness of combining radioisotopes (RI) and indocyanine green (ICG) and investigate discordances in sentinel lymph node (SN) reactivity using each tracer in cN0 breast cancer patients.

METHODS

In total, 338 cN0 primary breast cancer patients who underwent SN biopsy with RI and ICG and axillary lymph node (ALN) dissection were included. SN positivity with RI, ICG, and a combination of RI and ICG was denoted as SN(RI), SN(ICG), and SN(RI+ICG), respectively. We retrospectively estimated metastatic SN detection rates, each method's discordance rate, and the correlation of discordances in SN reactivity with postoperative N staging.

RESULTS

The combination of RI and ICG had higher metastatic SN detection rates (99.7%) than RI or ICG alone (91.7% and 96.4%, respectively; p < 0.01). The discordance rate between SN(RI) and SN(ICG) in detecting metastatic SNs was 11.3% (38/337 cases). The absence of SN(RI), cT stage (cT2-3), higher histological grade (G3), and histological type (special type) were identified as risk factors of pN2-3 disease (odds ratios: 8.64, 2.56, 1.92, and 3.28, respectively; p < 0.01).

CONCLUSION

Discordances in SN reactivity between RI and ICG helps in identifying SN metastasis. Although the absence of SN(RI) is rare, it is a significant sign of advanced ALN metastases. The findings of our study indicate that ALN dissection should be considered for accurate nodal staging in such cases.

Development and validation of a pre- and intra-operative scoring system that distinguishes between non-advanced and advanced axillary lymph node metastasis in breast cancer with positive sentinel lymph nodes: a retrospective study

Background

There are currently no scoring-type predictive models using only easily available pre- and intraoperative data developed for assessment of the risk of advanced axillary lymph node metastasis (ALNM) in patients with breast cancer with metastatic sentinel lymph nodes (SLNs). We aimed to develop and validate a scoring system using only pre- and intraoperative data to distinguish between non-advanced (≤ 3 lymph nodes) and advanced (> 3 lymph nodes) ALNM in patients with breast cancer with metastatic SLNs.

Methods

We retrospectively identified 804 patients with breast cancer (cT1-3cN0) who had metastatic SLNs and had undergone axillary lymph node dissection (ALND). We evaluated the risk factors for advanced ALNM using logistic regression analysis and developed and validated a scoring system for the prediction of ALNM using training (n = 501) and validation (n = 303) cohorts, respectively. The predictive performance was assessed using the receiver operating characteristic (ROC) curve, area under the curve (AUC), and calibration plots.

Results

Ultrasound findings of multiple suspicious lymph nodes, SLN macrometastasis, the ratio of metastatic SLNs to the total number of SLNs removed, and the number of metastatic SLNs were significant risk factors for advanced ALNM. Clinical tumor size and invasive lobular carcinoma were of borderline significance. The scoring system based on these six variables yielded high AUCs (0.90 [training] and 0.89 [validation]). The calibration plots of frequency compared to the predicted probability showed slopes of 1.00 (training) and 0.85 (validation), with goodness-of-fit for the model. When the cutoff score was set at 4, the negative predictive values (NPVs) of excluding patients with advanced ALNM were 96.8% (training) and 96.9% (validation). The AUC for predicting advanced ALNM using our scoring system was significantly higher than that predicted by a single independent predictor, such as the number of positive SLNs or the proportion of positive SLNs. Similarly, our scoring system also showed good discrimination and calibration ability when the analysis was restricted to patients with one or two SLN metastases.

Conclusion

Our easy-to-use scoring system can exclude advanced ALNM with high NPVs. It may contribute to reducing the risk of undertreatment with adjuvant therapies in patients with metastatic SLNs, even if ALND is omitted.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12957-022-02779-9.

Development and Validation of a Preoperative Scoring System to Distinguish Between Nonadvanced and Advanced Axillary Lymph Node Metastasis in Patients With Early-stage Breast Cancer

BACKGROUND

It has been determined that axillary lymph node dissection after the detection of limited axillary lymph node metastasis does not improve the prognosis of patients with breast cancer. Thus, a need exists for less-invasive axillary surgery. However, it remains unclear whether a predictive model based on preoperative data would be sufficient to accurately predict the probability of pN2-N3 (> 3 lymph node metastases). We sought to develop an easy-to-use scoring system to distinguish between pN0-N1 (0-3 lymph node metastases) and pN2-N3 using only preoperative data and validate its predictive performance.

PATIENTS AND METHODS

We retrospectively identified 2687 patients diagnosed with cT1-3cN0-N1 who had undergone surgery in our hospital from 2013 to 2019. We evaluated the risk factors associated with pN2-N3 by logistic regression analysis and developed a scoring system. Predictive performance was assessed by calculating the receiver operating characteristic area under the curve (AUC) and was validated using K-fold cross-validation.

RESULTS

We identified 1987 patients with stage pN0, 522 with pN1, and 178 with pN2-N3. Multivariate analysis revealed tumor size, number of suspicious lymph nodes on axillary ultrasound examination, histologic type, histologic grade, and receptor status were significant risk factors for pN2-N3. The AUC value was 0.87, and the mean AUC of the 10-fold cross-validation was 0.88. When the cutoff score was set at 6, the negative predictive value for excluding patients with pN2-N3 was 98.4%.

CONCLUSION

Our easy-to-use scoring system could be useful to preoperatively identify patients at lower risk of pN2-N3 and avoid unnecessary axillary lymph node dissection.