Postmastectomy radiotherapy indications using pathological prognostic staging in node-positive breast cancer

Introduction

Breast cancer (BC) remains a significant public health concern worldwide (1), with treatment strategies evolving to optimize outcomes while minimizing unnecessary interventions (2,3). One contentious area in BC management revolves around the role of postmastectomy radiotherapy (PMRT). In the current clinical treatment guidelines, PMRT has been recommended for patients with node-positive BC to reduce locoregional recurrence (LRR) and potentially improve overall survival (OS) (4-6). However, the evidence supporting the indication for PMRT is largely based on studies from non-contemporary treatment modalities (7,8). Several studies, including patients receiving contemporary treatment modalities, have found that PMRT may not significantly impact LRR and OS in patients with stage T1–2N1 disease (tumor size ≤5 cm and one to three positive lymph nodes) despite historical recommendations (9-14). Similarly, for patients with four or more positive lymph nodes (stage N2/3 disease), not all patients may benefit from LRR or OS by using PMRT (15,16). These observations highlight the importance of precise risk stratification to identify patients benefiting from PMRT.

Advances in understanding BC biology have introduced molecular and genetic factors that may influence the risk of LRR and response to PMRT (17,18). Incorporating biologic factors such as tumor grade, estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2) status in the eighth edition of the American Joint Committee on Cancer (AJCC) pathological prognostic staging (PPS) system represents a shift towards personalized prognosis prediction in BC management (19). Theoretically, new PPS may help tailor PMRT decisions based on individualized risk assessment rather than solely relying on traditional anatomical staging (AS). However, unlike the traditional AS system that guides PMRT decisions for BC patients, the new National Comprehensive Cancer Network (NCCN) guidelines have not been updated to incorporate the new PPS system for PMRT decisions (4). In light of this, this study aimed to investigate the impact of PPS on PMRT selection in patients with node-positive BC. We present this article in accordance with the STROBE reporting checklist (available at https://gs.amegroups.com/article/view/10.21037/gs-2025-84/rc).

Methods

Patients

We included women diagnosed with BC between 2010 and 2015 from the Surveillance, Epidemiology, and End Results (SEER) database. The SEER program collects cancer data for around 30% of the United States population, including demographic and clinicopathological characteristics, initial treatments, and vital status (20). In this study, we included female patients with BC who met the following criteria: (I) aged 18 years or older; (II) diagnosed with stage T1–4N1–3 according to 7th AJCC staging criteria; (III) received mastectomy and chemotherapy; (IV) treated with or without PMRT; (V) had available data on tumor (T) stage, nodal (N) stage, grade, ER, PR, and HER2 status. Patients with stage T0, N1mic, M1, those receiving systemic therapy before surgery, or those receiving non-beam irradiation were excluded from the analysis. As the SEER program is a de-identified database, the institutional review board of the First Affiliated Hospital of Xiamen University waived the need for review for the current study. This study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments.

Variables

The included data in this study comprised age, race, histology, T stage, N stage, grade, ER, PR, HER2 status, and the utilization of PMRT. All patients had their stages reassigned based on the PPS system (19). The primary endpoint of this study was breast cancer-specific mortality (BCSM). The BCSM was defined as the interval from the initial diagnosis of BC to the date of death from BC. BCSM was assessed using the cause of death data recorded from the SEER registries provided by the National Center for Health Statistics.

Statistical analysis

Categorical data differences were assessed using Chi-square test. The receiver operating characteristics (ROC) curve was employed to compare the risk stratification capacities of the AS and PPS in predicting BCSM. A higher concordance index (C-index) suggested greater prognostic accuracy. Competing-risks analyses with the Fine and Gray model were used to determine the combined effect of the variables on BCSM, and results were reported as sub-distribution hazard ratios (sdHRs) and 95% confidence intervals (CIs). Sensitivity analyses were performed after stratifying by AS and PPS groups to identify further the specific subgroups that benefited from PMRT. All statistical analyses were carried out using SPSS version 26 (SPSS Inc., Chicago, IL, USA), MedCalc Statistical Software version 18.2.1 (MedCalc Software bvba, Ostend, Belgium), and Stata/SE version 14 (StataCorp, TX, USA). A P value <0.05 was considered statistically significant.

Results

Patient characteristics

A total of 14,830 patients met the inclusion criteria for analysis (Table 1). Among them, 11,757 (79.3%) were aged <65 years, 9,316 (62.8%) were White, 10,905 (73.5%) had invasive ductal carcinoma subtype, 12,091 (81.5%) were ER-positive, and 3,035 (20.5%) were HER2-positive. Regarding the N stage, 8,864 (59.8%), 3,868 (26.1%), and 2,098 (14.1%) had N1, N2, and N3 diseases, respectively. Overall, 8,807 (59.4%) patients received PMRT while 6,023 (40.6%) did not. Younger age (P<0.001), advanced T stage (P<0.001), and advanced N stage (P<0.001) were associated with a higher likelihood of receiving PMRT (Table 1).

Staging migration

In terms of AS, 3,008 (20.3%), 4,640 (31.3%), 4,765 (32.1%), 319 (2.2%), and 2,098 (14.1%) patients were classified as IIA, IIB, IIIA, IIIB, and IIIC diseases, respectively. Using the PPS, 2,135 (14.4%), 4,651 (31.4%), 1,900 (12.8%), 1,801 (12.1%), 2,343 (15.8%), 1,140 (7.7%), and 860 (5.8%) were restaged as IA, IB, IIA, IIB, IIIA, IIIB, and IIIC diseases, respectively. Among them, 11,767 patients (79.3%) had their stage changed, with 1,086 (7.3%) upstaged and 10,681 (72.0%) downstaged. Specifically, 75.6% (n=2,274), 68.9% (n=3,197), and 70.2% (n=3,347) of patients initially staged as IIA, IIB, and IIIA were downstaged, respectively. Individual patient stage discrepancies are detailed in Table 2. The ROC curve results comparing AS and PPS are displayed in Figure 1, with a significantly higher C-index for PPS compared to AS (0.715 vs. 0.664, P<0.001).

Figure 1 Receiver operating characteristic analyses for comparing the prognostic abilities between the AS and PPS. AS, anatomical staging; AUC, area under the curve; PPS, pathological prognostic staging; ROC, receiver operating characteristic.

Prognostic analysis

Multivariate prognostic analysis models were used to identify independent prognostic factors associated with BCSM. Model 1 included race, age, histology, tumor grade, AS, ER status, PR status, HER2 status, and PMRT, while Model 2 included race, age, histology, PPS, and radiotherapy. AS and PPS were both independent prognostic factors for BCSM (Table 3). Notably, PPS demonstrated superior discriminatory ability in distinguishing patient survival from AS, as depicted in Figure 2.

Figure 2 The cumulative incidence of breast cancer-specific mortality curves of the anatomical staging (A) and pathological prognostic staging (B) using competing-risks regression.

Furthermore, patients receiving PMRT exhibited lower BCSM. In Model 1, the receipt of PMRT was independently associated with a lower BCSM (sdHR 0.768, 95% CI: 0.697–0.846, P<0.001) compared to those who did not. In Model 2, the receipt of PMRT was also independently associated with a lower BCSM (sdHR 0.802, 95% CI: 0.730–0.882, P<0.001) compared to those who did not.

Sensitivity analysis

Sensitivity analyses were performed to assess the impact of PMRT on BCSM after stratification by BC subtypes, AS, and PPS groups. The results showed that PMRT was not associated with lower BCSM in patients with hormone receptor (HoR)⁺/HER2⁻ (Figure 3A), HoR⁺/HER2⁺ (Figure 3B), HoR⁻/HER2⁺ (Figure 3C), and HoR⁻/HER2⁻ (Figure 3D) subtypes.

Figure 3 The effect of PMRT on breast cancer-specific mortality according to the breast cancer subtypes: (A) HoR⁺/HER2⁻; (B) HoR⁺/HER2⁺; (C) HoR⁻/HER2⁺; (D) HoR⁻/HER2⁻. HER2, human epidermal growth factor receptor 2; HoR, hormone receptor; PMRT, postmastectomy radiotherapy.

Models stratified by AS included race, age, histology, ER status, PR status, HER2 status, and PMRT. Regarding AS, PMRT significantly decreased 5-year BCSM in patients with stage IIB (6.7% vs. 8.1%, P=0.043), IIIA (10.7% vs. 14.4%, P<0.001), IIIB (22.7% vs. 27.3%, P=0.045), and IIIC (21.0% vs. 29.9%, P<0.001) disease compared with those of other stages. Unadjusted survival curves are presented in Figure 4.

Figure 4 The effect of PMRT on breast cancer-specific mortality according to the anatomical staging. (A) IIA; (B) IIB; (C) IIIA; (D) IIIB; (E) IIIC. PMRT, postmastectomy radiotherapy.

The models, after stratification by PPS, included race, age, histology, and PMRT. Regarding PPS, PMRT significantly decreased 5-year BCSM in patients with stage IIIA (14.4% vs. 19.7%, P<0.001), IIIB (19.8% vs. 27.2%, P=0.003), and IIIC (38.5% vs. 45.7%, P=0.049) disease compared with those of other stages. Unadjusted survival curves are presented in Figure 5.

Figure 5 The effect of PMRT on breast cancer-specific mortality according to the pathological prognostic staging. (A) IA; (B) IB; (C) IIA; (D) IIB; (E) IIIA; (F) IIIB; (G) IIIC. PMRT, postmastectomy radiotherapy.

Discussion

In this study, we explored the value of PPS in predicting the benefit of PMRT in patients with node-positive BC. We found that PPS had potential in PMRT selection in patients with node-positive BC, providing a useful contribution to the literature relating to PMRT in this patient subset.

BC is a highly heterogeneous malignant tumor, and the recommendations for systemic treatment are mainly based on the ER, PR, and HER2 status (4-6). It was not until the new AJCC staging system in 2018 that the biological factors of patients were incorporated into the staging system (19). Several studies have found that the new PPS system can result in stage migration in 39.7–45.5% of patients, with a higher proportion of patients being downstaged (78.1–84.9%) (21,22). In our study, we similarly found a significant proportion of patients experiencing stage migration when comparing AS and PPS. Notably, 79.3% of patients had their stage changed, with a majority (72.0%) being downstaged. This discrepancy highlights the increasing complexity in accurately BC staging, as biomarker identification has improved our ability to assess disease extent and biological behavior, potentially explaining the discrepancies observed between AS and PPS. Additionally, our study revealed a higher C-index for PPS (0.715 vs. 0.664 for AS), indicating its superior prognostic accuracy and supporting the incorporation of biological features into staging systems for enhanced patient stratification. This is crucial for treatment planning, particularly regarding the decision to administer PMRT. Downstaging suggests a potentially reduced risk of LRR than initially estimated, impacting the necessity and intensity of PMRT.

Although the new PPS system plays a crucial role in optimizing prognostication, several BC treatment guidelines have not yet incorporated it for determining indications for PMRT (4,5,23). Several studies on gene expression profiles have found significant correlations between higher recurrence risk scores and LRR rates (24,25). However, the high cost of gene expression profiling may limit its widespread use, and it is not routinely recommended for HoR-negative patients or those with N2/3 diseases (4). The biological factors included in PPS, such as ER, PR, HER2, and tumor grade, are routine pathological tests postoperatively in BC, making them more accessible and easier to implement clinically, especially in developing countries. In our previous studies, we found that PPS may play a crucial role in PMRT selection of patients with stage T1–2N1 (26), T3N0 (27), and N2/3 groups (28). Given the heterogeneous nature of the patient cohorts studied, these findings may not be generalized to all populations. In the current study, we included patients with T1–4N1–3 disease, which corresponds to the current NCCN guidelines for the recommendation of PMRT (4). As an increasing advocate for a personalized medicine approach in BC management, utilizing advancements in genomics and molecular profiling to refine prognostication and treatment decisions. The evolving landscape of BC staging, as highlighted in our study, necessitates ongoing research to integrate PPS into the clinical management of BC.

Based on the AS system, we found that PMRT decreased BCSM in patients classified as stages IIB–IIIC diseases, with no significant improvement observed in stage IIA diseases. Similarly, based on PPS, we observed that PMRT did not decrease BCSM in stage IA–IIB patients, but decreased BCSM in stage IIIA–IIIC patients. Our findings indicate that PMRT provides survival benefits predominantly in patients with advanced disease stages (IIIA, IIIB, and IIIC) as defined by both AS and PPS criteria. Stratification by AS and PPS consistently shows differential benefits of PMRT based on disease severity according to AJCC staging criteria. This underscores the importance of PMRT in managing more advanced stages of BC using the PPS. Using PPS, we identified that 10.9% of patients initially classified as stage IIB by AS were upstaged to stage IIIA by PPS, representing a subgroup that benefited from PMRT in our study.

Furthermore, our study revealed that among AS IIIA patients, 70.3% were downgraded to PPS stage IB–IIB disease. However, among those downgraded IB–IIB patients, PMRT did not confer survival benefits. A study from the National Cancer Database found that PMRT was not a significant predictor of OS risk for pN2/N3 BC patients after adjusting for disease characteristics, socioeconomic factors, and interaction effects of hormonal therapy and chemotherapy (15). The findings from the DBCG 82b&c study also revealed a substantial 36% reduction in LRR but no reduction in 15-year mortality in patients with N2/3 diseases (16). In clinical practice, approximately one-third of stage N2/N3 patients did not receive PMRT due to various reasons (29,30). Our study emphasizes the significant value of PMRT for stage N2/N3 patients in decreasing BCSM. However, integrating biological factors for staging adjustments can potentially spare low-risk patients from unnecessary PMRT, particularly among AS stage IIIA patients. This suggests minimal standalone impact of PMRT even for high-risk BC patients with favorable biological profiles, advocating for the precision of treatment decisions under the recent PPS system for better risk stratification.

Several limitations should be acknowledged in our study. First, its retrospective nature may introduce biases despite efforts to adjust for confounding variables. Second, findings may be influenced by cohort-specific characteristics and might not be fully generalizable to all BC populations. Third, details on PMRT target volume and dosage, chemotherapy regimens, anti-HER2 therapy, and hormonal therapy were not recorded in the SEER database. Moreover, details of lymphovascular invasion and axillary soft tissue involvement were also not recorded in the SEER database (31,32). Finally, information regarding disease recurrence after LRR was also absent from the SEER database. Nevertheless, a primary strength of our study lies in its use of a population-based cohort reflecting contemporary treatment paradigms, and the use of 5-year survival endpoints provides meaningful insights into the long-term impacts of PMRT.

Conclusions

In conclusion, our study highlights significant staging differences between AS and PPS in patients with node-positive BC. The high rate of downstaging observed with PPS suggests its potential to enhance risk stratification and optimize treatment strategies, especially in guiding the appropriate use of PMRT. Future prospective studies are needed to validate these findings and further refine staging paradigms in BC management.

Acknowledgments

The authors acknowledge the efforts of the SEER Program tumor registries in the creation of the SEER database.

Footnote

Reporting Checklist: The authors have completed the STROBE reporting checklist. Available at https://gs.amegroups.com/article/view/10.21037/gs-2025-84/rc

Peer Review File: Available at https://gs.amegroups.com/article/view/10.21037/gs-2025-84/prf

Funding: This manuscript was partly funded by the National Natural Science Foundation of China (No. 81872459), Natural Science Foundation of Fujian Province (No. 2024J011363), Guangdong Basic and Applied Basic Research Foundation (No. 2023A1515010086), the Social Development Projects of Key R & D Programs in Hainan Province (No. ZDYF2023SHFZ118), and the Project of the Xiamen Municipal Health Commission (No. 3502Z20184020).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://gs.amegroups.com/article/view/10.21037/gs-2025-84/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. This study did not require approval from the institutional review board due to the de-identified information in the SEER program. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments.

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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