Comparison of the prognosis of medullary breast carcinoma and invasive ductal carcinoma: a SEER-based study

Introduction

Medullary breast carcinoma (MBC) is a distinctive type of invasive breast cancer, accounting for less than 5% of all cases of this malignancy (1). Research has demonstrated that immunohistochemical staining of patients with MBC reveals a greater prevalence of triple-negative status, which is characterized by negativity for estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2) (2). It is well known that both triple negative breast cancer (TNBC) and invasive breast cancer are linked to a poorer prognosis. Nonetheless, some studies have indicated that patients diagnosed with MBC had a favorable prognosis (3-7), whereas other studies have demonstrated that the prognosis for MBC was not dissimilar to that of invasive ductal carcinoma (IDC) (8,9). Hence, a consistent consensus has yet to be reached regarding the discernible distinctions in clinical characteristics and prognostic profiles between MBC and IDC.

Recent research suggested that MBC was not a strictly pathological diagnosis, but a heterogeneous, spectrum-based group of lesions (10). It is imperative to ascertain the prognostic factors of MBC in order to facilitate the provision of more targeted and tailored treatment options to patients. Park et al. noted that overall survival (OS) and disease-free survival (DFS) were poorer in MBC patients with lymph node (LN) metastases, whereas no discernible difference was identified in terms of tumor size, hormone receptor status, or treatment modalities (8). Wang et al. utilized the Cox proportional hazards model as a means of evaluating the prognostic factors associated with cancer-specific survival (CSS) and OS among patients with MBC (1). Owing to the limited sample size and the presence of confounding factors, the prognostic factors pertaining specifically to MBC patients remained relatively unclear. The nomogram, which is regarded as a reliable tool based on multivariate regression analysis, encompasses the integration of numerous predictors to construct models that can accurately predict the prognostic outcomes for various cancers (11,12).

Given the controversial prognostic factors for MBC patients, the aim of our research was to identify disparities in clinical characteristics and prognosis between MBC and IDC by using the Surveillance, Epidemiology and End Results (SEER) database, and to further build and validate nomograms based on clinicopathological features for MBC. We present this article in accordance with the TRIPOD reporting checklist (available at https://tcr.amegroups.com/article/view/10.21037/tcr-23-858/rc).

Methods

Patients

We utilized SEER *Stat version 8.4.0.1 (https://seer.cancer.gov/seerstat/) to obtain 179,613 patients diagnosed between 2010 and 2015 who satisfied the following inclusion criteria: female, pathologically confirmed IDC (8500/3: IDC-NOS) or MBC (8510/3: MBC-NOS, 8512/3: MBC with lymphoid stroma, 8513/3: atypical MBC), histological grades I–IV, American Joint Committee on Cancer (AJCC) stages I–IV, with breast conserving surgery (BCS) or mastectomy, ER, PR, HER2 statuses known. We excluded patients who had not undergone surgery or with incomplete information, as well as those with no record of radiotherapy and chemotherapy. As information on radiotherapy, chemotherapy, and HER2 was not available in the SEER database until 2010, we excluded patients before 2010. Additionally, due to the different versions of staging after 2015 and our desire to ensure a sufficiently long follow-up period, we also excluded those who diagnosed with breast cancer after 2015. The study was conducted in accordance with the Declaration of Helsinki (as revised in 2013).

Statistical analysis

The demographic and clinical features of the 2 histological patient groups were compared using chi-squared test. Survival curves were generated via the Kaplan-Meier method, with disparities in CSS and OS evaluated utilizing the log-rank test. Moreover, we opted to employ a propensity score matching (PSM) technique in order to pair each MBC patient with an IDC patient who best aligned with pertinent variables. Cox proportional models were utilized to undertake univariate analysis, thereby enabling the identification of hazard ratios (HRs) for all potential risk factors, along with corresponding 95% confidence intervals (CIs). In addition, multivariate analysis was implemented to identify all independent prognostic factors. Nomograms were constructed to enable the prediction of 1-, 3-, and 5-year OS and CSS, with the predictive ability of these models evaluated via receiver operating characteristic (ROC) curve analysis. Ultimately, the calibration curve was implemented to assess agreement between predicted prognosis and actual prognosis. The aforementioned analytical procedures were performed using the software SPSS (IBM Corp., Armonk, NY, 25.0) and R (version 4.2.2; http://www.r-project.org) with bilateral P values <0.05 considered statistically significant.

The limitations of the statistical methods

Certainly, the aforementioned statistical methods also have limitations. Firstly, PSM is based on matching observed data of known variables, but there may be unobserved important variables that can influence the comparison of outcomes. Although PSM is used to control confounding variables, residual confounding factors may still exist, which can lead to erroneous positive or negative results, limiting the generalizability of the study findings. Secondly, the nomogram has limited applicability and cannot cover all possible scenarios and target variables. Each nomogram is developed based on specific samples or populations, and its applicability may be limited to the characteristics and scope of the samples used.

Results

Demographic and clinical characteristics of patients

After data filtering, 179,613 patients met our inclusion criteria, including 596 (0.33%) MBC and 179,017 (99.67%) IDC (Figure 1). Table 1 presents a synopsis of demographic and clinical features in patients with distinct histological types. There were significant differences among age, marital status, race, grade, AJCC stage, radiation and chemotherapy experience, LN, ER, PR, HER2 status, and tumor size. Patients with MBC demonstrated a younger age (86.9% vs. 76.1%, P<0.001), a higher proportion of Black race (23.2% vs. 10.8%, P<0.001), more unmarried (45.0% vs. 40.4%, P=0.025), higher ER negative (66.3% vs. 18.6%, P<0.001), PR negative (82.2% vs. 28.5%, P<0.001), and HER2 negative (88.9% vs. 83.9%, P=0.001) rates, higher LN negative (80.0% vs. 70.1%, P<0.001) rate, and less experience of chemotherapy (24.8% vs. 55.7%, P<0.001) and radiation (49.2% vs. 56.6%, P<0.001) than those with IDC. Moreover, compared to IDC, MBC had larger tumor size (more tumors ≥2 and ≤5 cm in size, 56.2% vs. 34.7%, P<0.001). Additionally, patients with MBC were likely to have a significantly higher grade (grade III and IV, 94.6% vs. 36.5%, P<0.001) and a higher proportion of the AJCC stage of II (53.2% vs. 34.0%, P<0.001) than those with IDC. No statistically significant differences were observed in other characteristics, including laterality and surgical type, between the 2 histological types.

Figure 1 Flowchart of the study. SEER, Surveillance, Epidemiology and End Results; IDC, invasive ductal carcinoma; MBC, medullary breast carcinoma.

Survival comparison between patients with MBC and IDC

Comparisons of OS and CSS of the 2 histological types were conducted separately through Kaplan-Meier analysis (Figure 2). As shown in Figure 2, MBC patients exhibited superior OS (P=0.0025) and CSS (P=0.0098) to IDC patients. To account for any potential bias or confounding factors, PSM was employed to facilitate a 1:1 matched case-control analysis (Figure 3). After matching, we had a total of 1,192 patients, including 596 patients for each histological type. There was no significant difference in clinical characteristics between IDC and MBC (Table 2). However, we found that these 2 histological types had a similar outcome for OS and CSS (Figure 4, P=0.0073 and P<0.0001 for OS and CSS, respectively).

Figure 2 Kaplan-Meier plot and log-rank test compared OS (A) and CSS (B) by histology for all patients, MBC vs. IDC. OS, overall survival; CSS, cancer-specific survival; MBC, medullary breast carcinoma; IDC, invasive ductal carcinoma.

Figure 3 Standardized differences between MBC and IDC. MBC, medullary breast carcinoma; IDC, invasive ductal carcinoma; AJCC, American Joint Committee on Cancer; LN, lymph node; ER, estrogen receptor; PR, progesterone receptor; HER2, human epidermal growth factor receptor 2.

Figure 4 Kaplan-Meier plot and log-rank test compared OS (A) and CSS (B) by histology for 1:1 matched group, MBC vs. IDC. MBC, medullary breast carcinoma; IDC, invasive ductal carcinoma; OS, overall survival; CSS, cancer-specific survival.

The construction and validation of the nomograms of MBC

MBC patients were randomly allocated into training and validation groups, with a ratio of 7:3 (Table 3). After performing univariate analysis of variables for MBC patients in the training set, seven variables, including age (HR: 4.6, 95% CI: 2.48–8.53, P<0.001), AJCC stage (III/IV) (HR: 5.76, 95% CI: 2.6–12.74, P<0.001), chemotherapy (HR: 0.38, 95% CI: 0.21–0.69, P=0.002), radiotherapy (HR: 2.44, 95% CI: 1.28–4.67, P=0.007), LN (HR: 3.16, 95% CI: 1.74–5.75, P<0.001), type of surgery (HR: 2.05, 95% CI: 1.11–3.79, P=0.022), and tumor size (>5 cm) (HR: 5.11, 95% CI: 2.2–11.84, P<0.001), were found to be correlated with OS in MBC (Table 4). Meanwhile, age (HR: 3.88, 95% CI: 1.58–9.51, P=0.003), AJCC stage (III/IV) (HR: 4.88, 95% CI: 1.69–14.08, P=0.003), chemotherapy (HR: 0.28, 95% CI: 0.12–0.66, P=0.003), laterality (HR: 0.36, 95% CI: 0.14–0.91, P=0.031), LN (HR: 2.89, 95% CI: 1.24–6.77, P=0.014), type of surgery (HR: 4.59, 95% CI: 1.69–12.43, P=0.003), and tumor size (>5 cm) (HR: 7.12, 95% CI: 2.17–23.37, P=0.001) were correlated with CSS in MBC patients (Table 5). A subsequent multivariate analysis demonstrated that age (HR: 4.59, 95% CI: 2.32–9.06, P<0.001), race (other) (HR: 0.25, 95% CI: 0.07–0.95, P=0.042), radiotherapy (HR: 3.1, 95% CI: 1.38–6.98, P=0.006), LN (HR: 2.42, 95% CI: 1.05–5.55, P=0.037), and tumor size (>5 cm) (HR: 4.21, 95% CI: 1.12–15.83, P=0.033) were independent prognostic factors for OS (Table 4). In addition, multivariate analysis demonstrated that age (HR: 3.89, 95% CI: 1.49–10.19, P=0.006), AJCC stage (II) (HR: 0.23, 95% CI: 0.05–0.95, P=0.042), chemotherapy (HR: 0.33, 95% CI: 0.13–0.86, P=0.024), laterality (HR: 0.2, 95% CI: 0.07–0.56, P=0.002), type of surgery (HR: 5.69, 95% CI: 1.63–19.87, P=0.006), and tumor size (>5 cm) (HR: 8.44, 95% CI: 1.33–53.49, P=0.024) were independent prognostic factors of CSS of MBC patients (Table 5). Nomograms estimating the 1-, 3-, and 5-year OS and CSS of MBC patients were created based on independent prognostic factors. Figure 5A,5B present the nomograms for predicting the OS and CSS in MBC patients. The ROC curve reflected the sensitivity and accuracy of the nomograms when the same threshold or different thresholds were selected. The ROC curves for the training and validation sets of MBC patients’ OS and CSS were plotted, as depicted in Figure 6. As we can see, the concordance index (C-index) of the nomograms for the 1-, 3-, and 5-year OS were 0.852, 0.826, and 0.791, respectively, in the training set, whereas the C-index for the 1-, 3-, and 5-year CSS were 0.845, 0.786, and 0.795, respectively. In the validation set, the C-index was 0.803, 0.806, and 0.846 for the 1-, 3-, and 5-year OS, respectively, and 0.712, 0.754, 0.765 for the 1-, 3-, and 5-year CSS, respectively. The calibration plots demonstrated good correspondence between the predicted outcomes generated by the nomograms and the observed outcomes of MBC, for both sets, across the 1-, 3-, and 5-year timepoints (Figure 7).

Figure 5 Nomograms for predicting the 1-, 3-, and 5-year (A) OS and (B) CSS of MBC. OS, overall survival; CSS, cancer-specific survival; MBC, medullary breast carcinoma; LN, lymph node; AJCC, American Joint Committee on Cancer; BCS, breast conserving surgery.

Figure 6 The ROC curves for predicting the survival of MBC patients. The OS (A) and CSS (B) in the training cohort at 1-, 3-, and 5-year after diagnosis, and the OS (C) and CSS (D) in the validation cohort at 1-, 3-, and 5-year after diagnosis. ROC, receiver operating characteristic; MBC, medullary breast carcinoma; OS, overall survival; CSS, cancer-specific survival; AUC, area under the curve.

Figure 7 The calibration curves for predicting the survival of MBC patients. The OS (A-C) and CSS (D-F) in the training cohort at 1-, 3-, and 5-year after diagnosis, and the OS (G-I) and CSS (J-L) in the validation cohort at 1-, 3-, and 5-year after diagnosis. MBC, medullary breast carcinoma; OS, overall survival; CSS, cancer-specific survival.

Discussion

Given that MBC is a comparatively uncommon type of breast cancer observed in clinical practice, the SEER database was utilized for comparing the differences in prognosis between MBC and IDC and constructing nomograms to predict OS and CSS in MBC patients. Our study showed that MBC patients were younger, had a higher grade, larger tumor size, and higher ER, PR, HER2 negative rates compared to IDC patients. These results were partially identical to those of previous studies. For example, Dai et al. noted that MBC patients exhibited higher stage, higher grade, and larger tumor size compared to patients with IDC (13). Park et al. concluded that MBC presented with rare LN metastases, negative ER and PR, nuclear pleomorphism, and high tumor grade (8). In addition, Wang et al. demonstrated that, in comparison to the IDCs, the MBCs were younger and presented with more advanced tumor stage, higher grade level, larger tumor size, and a greater proportion of TNBC (1). Nevertheless, in the study by Zangouri et al., although the MBC patients were younger, there was no statistically significant difference in age compared to IDC; this may be due to its insufficient sample size, with ethnic differences also having an effect (14). Moreover, MBC patients in China exhibited less aggressive characteristics such as lower stage, smaller size of tumor, and a lesser proportion of LN metastases (3).

Our present study indicated that both OS and CSS were superior in the MBC cohort when compared to the IDC cohort, both before and after controlling for confounding factors. IDCs were more aggressive than MBCs, which was similar to the findings of several previous studies (15-18). In a previous study, there was no notable difference in OS between IDC and specific histological types, whereas after PSM, the MBC group had better OS than IDC, which might be explained by the greater difference in prognosis of patients with different specific histological types (19).

Despite existing research having identified risk factors that impact the prognosis of MBC patients, to date, nomograms have yet to be constructed for the purpose of predicting both OS and CSS in MBC patients. Nomograms can be used to calculate the probability of producing a clinical event by integrating various clinical variables, which have been found to be superior to the tumor-node-metastasis (TNM) staging system (20-22). As observed by Dai et al., race appeared to be a significant factor in the prognosis of MBC patients, with Asian populations exhibiting more favorable outcomes, whereas African Americans tended to have poorer prognoses (13). Our study also confirmed this, with Black patients having a worse prognosis than Whites. MBC patients were younger than IDC (7), which was also confirmed by our findings: younger patients in MBC showed better CSS and OS. A number of factors were discovered to be significantly linked to OS in MBC, including age, marital status, stage, breast cancer subtype, tumor size, and radiotherapy (1). Our study observed a correlation between AJCC stage and the OS of MBC patients, although after conducting a Cox multivariate analysis, AJCC stage was no longer identified as an independent prognostic factor for OS. However, AJCC stage was an independent prognostic factor for CSS. Furthermore, ER and PR positivity have often been considered good prognostic factors for breast cancer, as endocrine therapy might benefit patients (23). Conversely, our study showed that ER and PR status were not associated with the prognosis of MBC patients. Both chemotherapy and radiotherapy are indispensable to the therapeutic regimen for managing invasive breast cancer. Lim et al. concluded by multivariate analysis that chemotherapy significantly improved OS (P=0.007) and CSS (P=0.009), but the effect of chemotherapy was limited in patients with larger tumors (>2 cm) (24). Aihara et al. concluded that the risk of death in MBC patients with ER and HER2 negativity was approximately half that of IDC patients and that postoperative chemotherapy reduced mortality and recurrence rates (25). However, another study disclosed that neither radiotherapy nor chemotherapy showed any notable association with the prognosis of patients with MBC (13). Our study found that radiotherapy improved patients’ OS and chemotherapy improved patients’ CSS, which might be related to the higher proportion of patients with severe conditions in our cohort, such as patients with larger tumor size and higher grade. A meta-analysis demonstrated that patients who underwent BCS exhibited better OS compared to mastectomy (26). Our study showed that patients with MBC who underwent BCS had better CSS compared to mastectomy. In addition to the independent prognostic factors mentioned above, we found that tumor size, LN, and laterality were also independent prognostic factors. The calibration curve and ROC curve both evinced the high predictive accuracy of the nomograms, which effectively forecasted 1-, 3-, and 5-year OS and CSS for MBC.

There were some limitations in our study. Firstly, as the SEER database did not provide information on HER2 and radiochemotherapy until 2010, this could potentially have resulted in inadequate follow-up time for our selected patients. Secondly, in our study, we exclusively considered patients with complete information on all variables and excluded those with incomplete data, which might have influenced the generalizability of our findings by introducing selection bias and limiting the sample size. Thirdly, due to the absence of specific information on endocrinology, targeted therapy, and chemotherapy regimens in the SEER database, we were unable to generate more comprehensive treatment plans for patients. Lastly, the utilization of the same database for both creating and validating nomograms may have introduced selection bias; utilizing data from diverse clinical cohorts would be recommended for validation purposes to make the nomograms more reliable.

Conclusions

Our study revealed noticeable differences between MBC and IDC, including younger age, higher stage and grade, lower rates of LN metastasis, larger tumor size, and higher prevalence of ER, PR, and HER2 negativity in MBC patients. Nevertheless, MBC patients had a comparatively better prognosis with respect to both OS and CSS. Our research identified age, race, tumor size, LN, and radiation therapy as independent prognostic factors for OS, whereas age, tumor size, AJCC stage, laterality, type of surgery, and chemotherapy were deemed independent prognostic factors for CSS. We observed no association between ER, PR, or HER2 status, as well as marital status, and the prognosis of MBC. The nomogram that we developed functioned effectively as a predictive tool for survival risk in MBC patients, thereby providing healthcare professionals with practical guidance for treatment options.

Acknowledgments

The authors thank the patients included in this study.

Funding: This study was supported by the Medical Scientific Research Foundation of Zhejiang Province, China (Nos. 2022KY1078 and 2023KY1030).

Footnote

Reporting Checklist: The authors have completed the TRIPOD reporting checklist. Available at https://tcr.amegroups.com/article/view/10.21037/tcr-23-858/rc

Peer Review File: Available at https://tcr.amegroups.com/article/view/10.21037/tcr-23-858/prf

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tcr.amegroups.com/article/view/10.21037/tcr-23-858/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study was conducted in accordance with the Declaration of Helsinki (as revised in 2013).

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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