MBC is a rare histological subtype of BC, most of which commonly present with a triple negative phenotype [34, 35]. Compared with invasive ductal carcinoma, MBC is characterized by lower differentiation, larger tumor size, less LNM and poorer clinical outcomes [36, 37]. In this study, among all 2205 patients, 1803 (81.8%) were poorly differentiated or undifferentiated, 402 (18.2%) were ER-positive, 286 (13.0%) were PR-positive, 76 (6.5%) were HER-2-positive, 1633 (74.1%) had tumors greater than 2 cm, 546 (24.8%) observed LNM. These results are consistent with the findings of previous studies.
LNM is considered a significant negative prognostic factor and is vitally important for therapeutic decision-making for MBC patients. But, current preoperative imaging modalities do not have high sensitivities and specificities in the diagnosis of LNM. Moreover, MBC has a wide range of histological patterns and extremely minimal metaplastic area, so it is difficult to identify by fine-needle aspiration or core biopsy before operation [38]. Leyrer CM et al. reported only 41% (46/113) patients were identified preoperatively as MBC on initial image-guided core biopsy [31]. Furthermore, nomogram, as a simple and advanced prediction tool, can estimate individualized risk by integrating substantial clinicopathological characteristics [39]. Therefore, it is necessary to establish a simple and sensitive preoperative prediction model of regional LNM in MBC patients.
In our study, grade, ER status and tumor size were considered independent predictors for regional LNM in patients with MBC. Then, those three clinicopathological variables were incorporated into a preoperative estimation model of regional LNM risk. To the best of our knowledge, this is the first population-based study to develop and validate a nomogram for predicting the preoperative individualized risk of regional LNM in MBC patients. In both training set and validation set, the AUC of the nomogram was higher than 0.6 and the calibration curves corresponded with the idealized 45° line, which demonstrated excellent discrimination and calibration of the nomogram. Nevertheless, great discrimination and calibration of the nomogram are not sufficient because they do not equal to clinical utility. In addition, MBC has a low incidence rate, and most available studies are retrospective studies of small samples. Hence, we used DCA to estimate the clinical usefulness, and DCA curves revealed greater net benefit of the established nomogram model. In other words, through this nomogram, we can accurately predict the regional lymph node status of MBC patients.
ER status as one of the most influential independent predictors of LNM has been reported in some studies. Gann PH et al. studied data from 18,025 breast carcinoma cases and suggested tumors lacking ER had a significantly lower risk of LNM than tumors containing ER [40]. Additionally, Ye FG et al. revealed ER status was an independently associated with a higher likelihood of LNM (OR = 5.254, 95% CI: 0.392–19.834, P < 0.014) [41]. Compared with the previous studies, we achieved a consistent conclusion. In our study, 30.9% of women with ER positive cancers were found to have positive regional lymph nodes compared to 23.2% of women with ER negative cancers (P = 0.006).
Several studies demonstrated that histologic grade was related to LNM status. Kollias J et al. retrospectively analyzed the medical records of 2684 BC patients, and showed that 29% of the patients with grade III cancers had positive lymph nodes, while the proportion of positive lymph nodes with grade I and grade II was 11% and 18%, respectively (P = 0.006) [42]. Besides, Bruno C et al. revealed the high pathological grade indicated high axillary nodal involvement in BC. The risk of axillary nodal involvement in grade III tumors doubled compared to grade I tumors (37.8% versus 18.3%) [43]. In our study, the highest positive rate of regional lymph nodes was observed in grade III MBC, which is consistent with the above conclusion.
The relationship between tumor size and LNM in BC patients have been widely reported in previous researches. In 1989, Carter et al. showed the incidence of LNM was approximately 31.1% (2591/8319) in the BC patients with tumors less than 2 cm, while the proportion of LNM was as high as 70.0% (1889/2698) in the BC patients with tumors 5 cm or greater [44]. Moreover, in 2006, Wada et al. reported nearly 50% (62/116) of the BC patients with T2 tumor (> 2.0cm) had positive non-sentinel lymph nodes [45]. Similarly, our study found that tumor size was an independent risk factor significantly associated with LNM in MBC patients. In our data, the percentages of regional lymph node positive tumors with greatest dimensions less than or equal to 2 cm and greater than 5 cm were 12.2% (70/572) and 42.6% (203/476).
We successfully constructed a nomogram based on a large population-based cohort for assessing the potential risk of regional LNM in MBC patients by utilizing grade, ER status, and tumor size. The established predictive model exhibited excellent performance, and was based on easily available clinicopathological factors. Therefore, the preoperative prediction of regional LNM could be accurately and conveniently identified on the nomogram by collecting the readily accessible information.
Although the nomogram had good accuracy for LNM prediction in MBC patients, some potential limitations of our study should be noted. First, due to the nature of retrospective analyses, we could not exclude selection bias. For example, some patients were excluded due to missing data, which may cause selection bias. Second, Ki-67 has been identified as an independent predictor of LNM in BC [46]. Unfortunately, it was not recorded in the SEER database. Thus we cannot incorporate this important factor into our nomogram. Finally, both training and validation sets came from the SEER database, which may lead to overfitting the model. The nomogram needs to be validated in more external force columns from other institutions to demonstrate its reproducibility.