Soo Kyung Ahn and Min Kyoon Kim contributed equally to this work.
The American College of Surgeons Oncology Group Z0011 trial reported that complete dissection of axillary lymph nodes (ALNs) may not be warranted in women with clinical T1-T2 tumors and one or two involved ALNs who were undergoing lumpectomy plus radiation followed by systemic therapy. The present study was conducted to identify preoperative imaging predictors of ≥ 3 ALNs.
The training set consisted of 1,917 patients with clinical T1-T2 and node negative invasive breast cancer. Factors associated with ≥ 3 involved ALNs were evaluated by logistic regression analysis. The validation set consisted of 378 independent patients. The nomogram was applied prospectively to 512 patients who met the Z0011 criteria.
Of the 1,917 patients, 204 (10.6%) had ≥ 3 positive nodes. Multivariate analysis showed that involvement of ≥ 3 nodes was significantly associated with ultrasonographic and chest computed tomography findings of suspicious ALNs (p < 0.001 each). These two imaging criteria, plus patient age, were used to develop a nomogram calculating the probability of involvement of ≥ 3 ALNs. The areas under the receiver operating characteristic curve of the nomogram were 0.852 (95% confidence interval [CI], 0.820 to 0.883) for the training set and 0.896 (95% CI, 0.836 to 0.957) for the validation set. Prospective application of the nomogram showed that 60 of 512 patients (11.7%) had scores above the cut-off. Application of the nomogram reduced operation time and cost, with a very low re-operation rate (1.6%).
Patients likely to have ≥ 3 positive ALNs could be identified by preoperative imaging. The nomogram was helpful in selective intraoperative examination of sentinel lymph nodes.
Major changes have occurred in the standard management of the axilla in patients with invasive breast cancer, with standard treatment progressing from axillary lymph node dissection (ALND) to sentinel lymph node biopsy (SLNB). Intraoperative pathologic evaluation of sentinel lymph nodes (SLNs) has changed surgical practice and has the advantage that it allows patients with positive SLNs to avoid reoperation by immediately proceeding to ALND.
Recently reported results of the American College of Surgeons Oncology Group (ACOSOG) Z0011 trial indicate that complete ALND does not improve survival in women with clinical T1-T2 tumors and one or two involved axillary nodes who are undergoing lumpectomy with radiation therapy followed by systemic therapy [
Advances in preoperative imaging have further changed the algorithm for axillary management. Preoperative knowledge of axillary lymph node (ALN) involvement has improved individualized multidisciplinary treatment options [
The Seoul National University Hospital Breast Care Center Database (SNUHBCC database) [
US, contrast-enhanced chest computed tomography (CT), and positron emission tomography (PET)–CT were conducted for preoperative staging of the axilla and distant organs. All images were reviewed by specialized radiologists who had been informed that the patients had invasive breast cancer.
Axillary US examination was performed 1 day before surgery. The maximum cortical thickness was measured on a cross-sectional plane perpendicular to the long axis of the lymph node [
All included patients underwent preoperative CT using the protocol described for asymptomatic lung and liver metastases [
Of the 1,917 patients in the training set, 364 (19.1%) were evaluated by fluorodeoxyglucose (FDG) PET-CT. Standard uptake values were calculated from the amount of FDG injected, body weight, and soft tissue uptake in attenuation-corrected regional images.
The SLNB technique, in which SLNs are detected using a radioisotope technique and/or with a blue dye, has been described previously [
The associations between having ≥ 3 involved ALNs with patient demographic characteristics, tumor characteristics on preoperative biopsy, and preoperative imaging results were evaluated by Fisher exact tests. Multivariate logistic regression analysis was conducted using a combination of continuous variables (age, tumor size on preoperative US, and ultrasonographic ALN classification) and dichotomized variables (finding suspicious of positive ALN on chest CT). A nomogram predicting the probability of involvement of ≥ 3 ALNs was then developed based on the multivariate logistic regression model, with a forward stepwise selection method and likelihood-ratio test used to select a subset of all analyzed factors.
The performance of the nomogram was evaluated by receiver operating characteristic (ROC) curve analysis, with calculation of the areas under the ROC curves. The nomogram was calibrated by plotting the observed probability against the predicted probability from the nomogram. A perfectly accurate nomogram prediction model would result in a plot in which the observed and predicted probabilities would fall along a 45° line. Thus, the distance between the pairs and the 45° line is a measure of the absolute error of prediction of the nomogram [
Patients, tumors, treatments, and preoperative image characteristics are shown in
Chest CT showed findings suspicious of ALN involvement in 198 patients (10.3%). PET-CT was performed in 364 patients (19.9%), among which 105 (28.8%) had findings suspicious of ALN involvement.
Univariate logistic regression analysis (
Since only 27.3% of the patients in the training set underwent PET-CT, another multivariate logistic regression analysis was performed excluding the PET-CT findings (
The results of the multivariate analysis were used to develop a nomogram predicting the likelihood of involvement of ≥ 3 positive ALNs for use in clinical practice. Points were assigned to each variable, such as patient age at diagnosis, axillary US grade, and positive ALN findings on chest CT, then summed to yield the total number of points. The latter was used to assign a probability of ≥ 3 positive ALNs for individual patients using the scale at the bottom of
To assess the accuracy of the nomogram, the actual probability was plotted against the calculated predicted probability of having ≥ 3 involved ALNs for each patient in the external validation set (
The specificity and NPV of the nomogram were calculated and the ability of the nomogram to correctly classify patients into two groups (those with ≤ 2 or ≥ 3 involved ALNs) was determined based on whether the predicted probability was more or less than 40%. When using ≤ 123 points as a cut-off, the specificity of the nomogram was 90% and its NPV was 95.8%. Of the 1,610 patients in the training set predicted to have ≤ 2 involved ALNs, only 68 (4.2%) showed false-negative results, resulting in a reoperation rate of ALND < 5%. Thus, this cut-off could be used to define a subset of patients that could avoid intraoperative frozen analysis. Use of the same cut-off in the validation set of 378 patients showed that 307 (81.2%) had ≤ 2 involved ALNs, of which only seven (2.3%) showed false-negative results (i.e., ≥ 3 involved ALNs).
The nomogram was subsequently applied to a prospective cohort of 512 patients (
The effectiveness of intraoperative evaluation of SLN biopsy remains unclear [
Predicting ALN status prior to surgery can facilitate surgical planning and informed discussions with patients regarding management options. Various nonsurgical methods including US, CT scan, PET imaging, and magnetic resonance imaging have been tried to predict lymph node involvement [
We hypothesized that, although it would be difficult to distinguish involvement of zero and at least one LN, it may be possible to predict high LN tumor burden, which was defined as involvement of ≥ 3 ALNs. Preoperative imaging was able to predict patients with ≥ 3 positive ALNs, enabling the avoidance of intraoperative analysis of SLNs in patients with low scores on the nomogram, thereby reducing operation times and costs. Using this method, the rate of reoperation was very low.
Findings suspicious of metastatic ALN on chest CT were a significant predictor of high tumor burden in the axilla, making chest CT results a major component of our nomogram. This is one of the limitations of this study, since chest CT is not a routinely performed imaging modality for early stage breast cancer patients in most institutions. However, our findings indicate the necessity of performing chest CT to use our nomogram in practice. In contrast to a small study of 35 breast cancer patients, which reported that chest CT had a low NPV (20%) for axillary metastases [
PET-CT has been utilized more frequently than chest CT to evaluate ALN metastasis. In our study, PET-CT had a low PPV (27.2%) and was not significant in multivariate analysis (p=0.163). This may have been due to the relatively low percentage (19.9%) of our patients evaluated by PET-CT. Further investigations are required to determine whether adding PET-CT to our nomogram would enhance its performance.
Two strategies are deemed feasible for patients who meet the criteria of the ACOSOG Z0011 trial: to never or always evaluate intraoperative frozen biopsy samples. Use of our nomogram could reduce the reoperation rate when compared with the non-use of frozen biopsy, while saving time and costs compared with universal use of frozen biopsy.
It should be noted that this model had several limitations in addition to those associated with the use of chest CT. Specifically, US classification of ALN may be subjective and has not been validated in other institutions.
In summary, we showed that patients with a high probability of having ≥ 3 positive ALNs can be identified using preoperative imaging methods, such as CT and US, as well as patient demographic and clinical characteristics. The developed nomogram may be useful for identifying patients who do not require intraoperative analysis of SLNs.
Supplementary materials are available at Cancer Research and Treatment website (
Conflict of interest relevant to this article was not reported.
This study was supported by grant of the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIP) (2015R1A2A2A01008264).
Nomogram for predicting the probability of having three or more involved axillary lymph node (ALNs). US, ultrasonography; CT, computed tomography.
Performance of the nomogram in the training set and the validation set were each measured using the area under the receiver operating characteristic curves. (A) Training set: 0.852 (95% confidence level, 0.820 to 0.883). (B) Validation set: 0.896 (95% confidence level, 0.836 to 0.957).
Calibration plot of the nomogram using validation cohort.
Patient characteristics of the training set
Characteristic | No. (%) (n=1,917) |
---|---|
Mean±SD | 50.5±10.2 |
Range | 24-85 |
Mean±SD | 2.28±1.02 |
Range | 0.4-5 |
≤ 2 | 1,713 (89.4) |
≥ 3 | 204 (10.6) |
1 | 657 (34.3) |
2 | 694 (36.2) |
3 | 292 (15.2) |
4 | 159 (8.3) |
5 | 105 (5.5) |
Unknown | 10 (0.5) |
Positive | 198 (10.3) |
Negative | 1,716 (89.5) |
Unknown | 3 (0.2) |
Positive | 105 (5.5) |
Negative | 259 (13.5) |
Unknown | 1,553 (81.0) |
Conservation | 1,368 (71.4) |
Mastectomy | 549 (28.6) |
Sentinel LN biopsy only | 1,490 (77.7) |
ALND | 427 (22.3) |
Ductal | 1,776 (92.6) |
Lobular | 71 (3.7) |
Other | 70 (3.7) |
≤ 2 | 1,079 (56.3) |
> 2 | 838 (43.7) |
Positive | 1,355 (70.7) |
Negative | 542 (28.3) |
Unknown | 20 (1.0) |
Positive | 1,116 (58.2) |
Negative | 785 (40.9) |
Unknown | 16 (0.9) |
Positive | 257 (13.4) |
Negative | 1,600 (83.5) |
Unknown | 60 (3.1) |
US, ultrasonography; LN, lymph node; CT, computed tomography; ALN, axillary lymph node; PET, positron emission tomography; ALND, axillary lymph node dissection; HER2, human epidermal growth factor receptor 2.
Factors associated with involvement of three or more ALNs
Variable | Three or more LN (+) (%) | Two or less LN (+) (%) | p-value |
---|---|---|---|
49.2 | 50.6 | 0.053 | |
2.66±1.07 | 2.23±1.0 | < 0.001 | |
2.86±1.58 | 2.17±1.46 | < 0.001 | |
≤ 2 | 68 (33.3) | 851 (49.7) | < 0.001 |
> 2-5 | 136 (66.7) | 862 (50.3) | |
Gr 1 | 11 (5.4) | 646 (37.7) | < 0.001 |
Gr 2 | 34 (16.7) | 660 (38.5) | |
Gr 3 | 38 (18.6) | 254 (14.8) | |
Gr 4 | 57 (27.9) | 102 (6.0) | |
Gr 5 | 62 (30.4) | 43 (2.5) | |
Positive | 106 (52.7) | 92 (5.4) | < 0.001 |
Negative | 95 (47.3) | 1,621 (94.6) | |
Positive | 34 (79.1) | 71 (22.1) | < 0.001 |
Negative | 9 (20.9) | 250 (77.9) | |
Positive | 134 (67.3) | 1,221 (71.9) | 0.177 |
Negative | 65 (32.7) | 477 (28.1) | |
Positive | 125 (62.2) | 991 (58.3) | 0.289 |
Negative | 76 (37.8) | 709 (41.7) | |
Positive | 34 (17.0) | 223 (13.5) | 0.171 |
Negative | 166 (83.0) | 1,434 (86.5) |
Values are presented as mean±standard deviation or number (%). ALN, axillary lymph node; LN, lymph node; US, ultrasonography; MRI, magnetic resonance imaging; CT, computed tomography; PET, positron emission tomography; HER2, human epidermal growth factor receptor 2.
Sensitivity, specificity, PPV, and NPV for each preoperative image-modality when predicting involvement of three or more axillary lymph nodes
Variable | Sensitivity (%) | Specificity (%) | PPV (%) | NPV (%) |
---|---|---|---|---|
Axillary US | 66.7 | 88.4 | 43.2 | 95.3 |
Chest CT | 55.2 | 92.8 | 50.8 | 93.9 |
PET-CT | 70.7 | 74.5 | 27.2 | 94.9 |
PPV, positive predictive value; NPV, negative predictive value; US, ultrasonography; CT, computed tomography; PET, positron emission tomography.
Multivariate logistic regression analysis of factors associated with involvement of three or more ALNs
Variable | Odds ratio | 95% CI | p-value |
---|---|---|---|
Age | 0.99 | 0.97-1.00 | 0.097 |
Tumor size by preoperative US (cm) | 1.08 | 0.91-1.28 | 0.392 |
Axillary US grade | 2.13 | 1.80-2.52 | < 0.001 |
Chest CT ALN positive | 4.78 | 3.07-7.45 | < 0.001 |
ALN, axillary lymph node; CI, confidence interval; US, ultrasonography; CT, computed tomography.