Male breast cancer (MBC) is a rare cancer that comprises less than 1% of all breast cancer cases (1, 2) and less than 1% of all cancers of male. With the development of social economy and the progress of breast cancer diagnosis technology, the global incidence of MBC has been on the rise (3).

Given the infrequency of MBC cases, current clinical practices for diagnosing, treating, and evaluating the prognosis of MBC often rely on female breast cancer protocols, despite physiological differences between men and women (4, 5). For example, a multicenter study found that CDK 4–6 inhibitors, were effective and safe options for men with hormone receptor-positive (HR+) and human epidermal growth factor receptor 2-negative (HER2-) metastatic breast cancer, similar to their effectiveness in female breast cancer (6). Furthermore, MBC is frequently overlooked, and men are inclined to receive diagnoses at later stages of the disease and at more advanced ages than their female counterparts (7, 8). Common risk factors associated with the prognosis of breast cancer, such as age, ethnicity, tumor size, histological differentiation grade, estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2) and Ki-67, have been well-recognized (9–12). Inflammatory biomarkers, such as lymphocyte-to-monocyte ratio (LMR), platelet-to-lymphocyte ratio (PLR), and neutrophil-to-lymphocyte ratio (NLR), have been shown to be associated with the prognosis of esophageal, cervical, and lung cancers (13–17). However, evidence on the relationship between these inflammatory biomarkers and female breast cancer was still limited and inconsistent (18–21). More importantly, the study examining the association between these inflammatory biomarkers and the prognosis of MBC was scarce. So we aimed to investigate the prognostic factors of MBC, including clinical features and inflammatory biomarkers, and construct a nomogram for MBC. Our study might provide important clues for clinical prognosis of MBC.

The age at diagnosis of the cases ranged from 20 to 82 years, with a median (IQR) age of 59.0 (16.0) years, mean (SD) age of 58.6(13.5) years. The clinical features of MBC patients were shown in Table 1 . Among the cases with MBC, 111 (96.5%) were married, 42 (36.5%) had a history of smoking, and 38 (33.0%) reported a history of alcohol consumption. A family history of tumors was observed in 33.9% of cases, with 6 cases specifically having a family history of breast cancer. 54.8% of tumors were located in the left breast, and the histopathological characteristics were primarily composed of tumors with a size of ≥ 2.0 cm (57.4%), invasive type (83.5%), and poorly differentiated histology (42.6%). Lymph node metastasis was present in 42.6% of cases. The molecular subtypes of the tumors were predominantly estrogen receptor (ER) positive (80%), progesterone receptor (PR) positive (79.2%), human epidermal growth factor receptor 2 (HER2) negative (48.7%), and 66(57.4%) patients had Ki67 levels no higher than 15%. Triple-negative (ER negative, PR negative, and HER2 negative) cases comprised only 1.7% of the total, while 4.3% of cases exhibited HER2 overexpression. The median (IQR) values of LMR, PLR and NLR were 3.67 (2.17), 113.20 (66.33), and 2.13 (1.60), respectively.108 (93.9%) cases underwent radical mastectomy, while only 3 (2.6%) received breast-conserving surgery. In addition, among the 13 MBC patients diagnosed with TNM stage of IV, only one of them did not undergo surgery, while the remaining 12 individuals all received radical mastectomy. Among all patients, 63 (54.8%) individuals received at least one of the postoperative adjuvant treatment of radiotherapy, chemotherapy, or hormone therapy. During follow-up period, 85 (73.9%) cases did not experience cancer distant metastasis, while in patients with metastases, the most frequent metastatic site was lungs (12 patients), followed by lymph nodes and bones (both were 10 patients), with 11 of them developing metastases in two or more locations. After a median follow-up time of 78 months, 29 (25.2%) cases passed away during the follow-up period, and 36 (31.3%) cases had a recurrence.

The median survival time of the 115 cases was 146 months, with a 5-year overall survival rate of 76.8% and a 10-year overall survival rate of 66.9%. Univariable Cox regression analysis for prognostic factors of MBC related to OS and DFS was shown in - Tables 2 , 3 and Supplementary Tables 1 , 2 . The results showed that 7 factors were associated with worse OS in MBC: age (hazard ratio [HR] 1.11, 95% confidence interval [CI] 1.07-1.16), tumor size (HR 4.42, 95%CI 1.68-11.61), TNM stage (stage IV vs. I: HR 7.41, 95%CI 2.13-25.73), Ki67 (HR 2.30, 95%CI 1.07-4.92), distant metastasis (HR 4.56, 95%CI 2.17-9.58),PLR (HR 2.83, 95%CI 1.29-6.24), and NLR (HR 3.16, 95%CI 1.39-7.19),while 4 factors were associated with better OS in MBC: ER (HR 0.31, 95%CI 0.11-0.92), PR(HR 0.31, 95%CI 0.10-0.94), type of surgery(radical mastectomy vs. no surgery: HR 0.17, 95%CI 0.04-0.75), and LMR(HR 0.38, 95%CI 0.17-0.86). As for DFS, there were six factors associated with DFS in MBC: age (HR 1.06. 95%CI 1.02-1.09), tumor size (HR 3.19, 95%CI 1.57-6.47), histological differentiation grade (poorly differentiated/undifferentiated vs. well-differentiated: HR 3.98, 95% CI 1.37-11.55), TNM stage (stage IV vs. I: HR 29.50, 95%CI 7.62-114.18), Ki67 (HR 2.74, 95%CI 1.41-5.35), and LMR (HR 0.50, 95%CI 0.26-0.96). Furthermore, above statistically significant factors were included in multivariate Cox regression analysis. We only observed a positive association between age and OS in MBC ( Table 2 ), as well as age, tumor size, histological differentiation grade, and TNM stage with DFS ( Table 3 ). Regarding the three inflammatory biomarkers LMR, PLR, and NLR, we plotted their associations with the OS and DFS of MBC using Kaplan-Meier survival curves. The Logrank test revealed that LMR was significantly negatively associated with both OS and DFS of MBC, while PLR and NLR were only positively associated with OS (all P-values < 0.05) ( Supplementary Figures 1A–D ).

Nomograms for predicting DFS in MBC cases by incorporating the statistically significant factors in multivariate Cox regression analysis were shown in Figure 1 . The prognostic nomograms showed good discrimination, with C-index values of 0.782 (95% CI: 0.578-0.904) for DFS. The bootstrapped calibration curves of the nomograms for the predicted vs. actual survival probability demonstrated a good fit ( Figure 2 ).

Our study identified older age as significant prognostic predictors for both OS and DFS in MBC cases, and poor tumor histological differentiation, bigger tumor size, TNM stage of IV were only found to be associated with a shorter DFS. Although LMR were all significantly associated with both OS and DFS in univariate analysis, and PLR and NLR were only significantly associated with OS, all these three biomarkers did not show statistically significant in multivariate analysis.

The median age of MBC cases in our study was 59 years (range 20-82 years) at diagnosis, which was in line with previous study reporting a similar median age of around 60 years old in MBC cases of different races (9, 22–24). Of the MBC cases in our study, 33.9% had a family history of malignant tumors, including 5.2% with a family history of breast cancer, which is consistent with previous research indicating that 5% to 10% of MBC cases have a family history of cancer (9, 25). Invasive ductal carcinoma was reported to be the most common histopathological subtype of MBC cases (2, 7). Similarly, in our study, 72.2% of MBC cases were diagnosed with invasive ductal carcinoma. In addition, the majority of MBC cases of our study had a TNM stage of I or II, which was consistent with previous research (22, 24). Previous studies have indicated that most MBC patients have ER and PR positive tumors while being HER2 negative (2, 23, 26). In our study, approximately 80% of MBC patients exhibited positive expression of ER and PR, but negative expression of HER2. Previous studies have reported that the primary tumor was commonly found in the left breast (25), and the most frequent sites of distant metastasis were the bone, lung, and lymph nodes (25, 27). Similarly, 54.8% of patients in our study were diagnosed with breast cancer in the left breast, and the three most common sites of metastasis were the bones, lungs, and lymph nodes.

Previous studies have reported inconsistent findings regarding the prognostic factors in MBC cases. A study of 10,873 MBC cases from the National Cancer Data Base in the US showed that older age, black race, higher Charlson comorbidity index, higher tumor grade and stage, and receipt of total mastectomy were associated with poorer OS, while residing in a high income area, positive PR expression and administration of chemotherapy, radiation or endocrine therapy were associated with better OS (22). For immunohistochemistry indicators of MBC, a study based on the SEER database found that MBC cases with HER2-negative having longer OS and higher 4-year OS rates, but did not significantly affect disease-specific survival (DSS) (28). A case-control study involving 65 male breast cancer patients from the Department of Veteran’s Affairs (DVA) Cancer Registry found that the survival rate was higher for ER-positive patients, while PR status and Ki67 were not associated with survival in men with breast cancer (29). A cohort study including 643 MBC cases from Danish found that increased age, bigger tumor size, positive lymph node status, higher grade and Luminal B subtype were risk factors for OS in MBC cases (30). For Chinese population, a study with 152 MBC cases reported that tumor size, radical mastectomy, and hormone therapy were risk factors for both OS and DFS in MBC cases (31), while another study of 77 Chinese MBC cases only found that M stage was significant prognostic factor, and ER, PR, and HER2 status had no impact on OS of MBC (9). In our study, multivariate analysis showed that age were significant prognostic factors for OS of MBC, and age, tumor size, histological differentiation grade, and TNM stage were significant prognostic factors for DFS, and only univariate analysis showed that Ki67>15% was associated with shorter OS and DFS of MBC, while ER and PR positive was associated with longer OS. However, HER2 expression was not significantly associated with either OS or DFS of MBC. Our study’s results might differ from other studies due to differences in ethnicity, sample size, and consideration of confounding factors.

Previous studies have reported inconsistent results regarding the association between inflammatory markers and prognosis of breast cancer. Several studies suggested that higher levels of LMR were associated with better prognosis of breast cancer, while higher levels of PLR were associated with worse prognosis (20, 32–34). However, another study indicated that NLR, PLR, and LMR in MBC had no statistically significant correlation with either DFS or OS (18). The potential mechanisms of LMR, PLR, and NLR might involve that T lymphocytes such as CD4 and CD8 play a role in tumor suppression mechanisms such as cancer immunosurveillance and cancer immunosedition by inducing tumor cell apoptosis, thereby inhibiting tumor cell proliferation and migration (35). Our study reported that higher LMR levels were associated with better prognosis of MBC, and higher PLR and NLR levels were associated with worse prognosis of MBC.

A nomogram is a simple graphical representation of a statistical prediction model that estimates the probability of an event and is widely used in cancer prognosis (36). As the fifth year after surgery is the high-risk period for recurrence and metastasis of breast cancer cases (32), and the 10-year survival rate of breast cancer is over 50% (37), predicting the 5-year and 10-year survival rates of MBC cases is of great clinical significance. Therefore, we constructed nomograms for DFS for MBC cases, with predictors of age, tumor size, histological differentiation grade, and TNM stage. The C-index of nomogram showed a high degree of discrimination (C-index: 0.782, 95%CI: 0.578-0.904), and the calibration curves displayed good accuracy, suggesting that this nomogram can effectively predict the 5-year and 10-year DFS of MBC cases and provide a basis for predicting their prognoses.

There were some limitations in the present study. Firstly, this is a single-center, retrospective study, and some cases’ basic data was not complete, which may lead to bias. Secondly, nomogram model for MBC was only validated internally, and external validation was needed. Thirdly, we were unable to conduct subgroup analyses according to different subtypes or other characteristics due to the limited sample size of MBC cases. Fourthly, previous studies have reported the correlation between breast cancer and genetic factors (5), however, genetic data were not collected in current study.

In conclusion, MBC cases were mainly ER and PR positive, HER2 negative. Age was significant factors influencing OS of MBC, whereas age, tumor size, histological differentiation grade, and TNM stage were significant factors influencing DFS of MBC. Inflammatory markers might hold certain predictive value for the prognosis of MBC. Hence, future clinical practice needs to allocate appropriate attention to inflammation biomarkers, while larger sample studies are warranted to further verify our findings.

The original contributions presented in the study are included in the article/ Supplementary Material . Further inquiries can be directed to the corresponding authors.

The studies involving humans were approved by the Ethical Committee of Zhejiang Cancer Hospital (No.IRB-2020-237). The studies were conducted in accordance with the local legislation and institutional requirements. The participants provided their written informed consent to participate in this study.

HL: Investigation, Resources, Software, Writing – original draft. BH: Conceptualization, Software, Visualization, Writing – original draft. YM: Validation, Writing – review & editing. WC: Investigation, Resources, Writing – review & editing. CM: Investigation, Resources, Writing – review & editing. SY: Methodology, Supervision, Writing – review & editing, Funding acquisition. JL: Methodology, Supervision, Writing – review & editing.