Abstract
Background and aims:
Breast cancer-related death is attributable mainly to metastasis. Inflammatory breast cancer (IBC) is an infrequent subtype of breast cancer that shows a relatively high rate of metastasis. In this study, we aimed to compare the metastatic patterns and prognostic outcomes of IBC and non-inflammatory breast cancer (non-IBC).
Methods:
We extracted data between 2010 and 2014 from the Surveillance, Epidemiology and End Results (SEER) database. The Chi-square test and Fisher’s exact test were used to compare the categorical parameters among different groups. Logistic regression was applied for multivariate analysis. The Kaplan–Meier method and multivariate Cox regression models were performed to analyze prognosis.
Results:
We enrolled 233,686 breast cancer patients between 2010 and 2014 in our research, including 2806 IBC and 230,880 non-IBC patients. Compared with the non-IBC group, the IBC group tended to have a higher incidence of the human epidermal growth factor receptor 2 positive (HER2+) and triple-negative breast cancer (TNBC) subtypes, older age, a higher rate of unmarried status, a lower incidence of black race, poorer tumor differentiation, larger tumor sizes, and a higher frequency of regional lymph node invasion. IBC and non-IBC shared similar trends in molecular subtypes among different metastatic organs. The percentage of the hormone receptor positive (HR+)/human epidermal growth factor receptor 2 negative (HER2–) subtype decreased gradually in patients with lung (IBC 42.5%, non-IBC 55.7%), distant lymph node (IBC 41.5%, non-IBC 54.6%), liver (IBC 31.1%, non-IBC 46.7%), and brain (IBC 30.6%, non-IBC 47.9%) metastases compared with that in patients with bone (IBC 50.8%, non-IBC 69.0%) metastasis in both cohorts. In both the IBC and non-IBC cases, the proportion of visceral metastases increased in the TNBC subtype, especially brain metastasis (IBC 26.4%, non-IBC 21.2%), which had the largest increase. The frequencies of all sites (bone, lung, liver, brain, and distant lymph node) in IBC were much higher than those in non-IBC (bone: IBC 21.1%, non-IBC 3.0%; lung: IBC 11.4%, non-IBC 1.4%; liver: IBC 9.6%, non-IBC 1.2%; brain: IBC 2.6%, non-IBC 0.3%; distant lymph node: IBC 12.9%, non-IBC 1.0%). The most frequent bi-site metastasis was the bone and liver (IBC 2.5%, non-IBC 0.3%), and the most frequent tri-site combination was the bone, lung, and liver (IBC 1.1%, non-IBC 0.2%). Kaplan–Meier curves and multivariate Cox regression models suggested that the IBC cohort had poorer overall survival [hazard ratio (HR) 1.602, 95% confidence interval (CI) 1.496–1.716, p < 0.001] and breast cancer-specific survival (HR 1.511, 95% CI 1.402–1.628, p < 0.001) than the non-IBC cohort. Furthermore, univariate and multivariate analyses indicated that IBC was an independent prognostic factor in patients with different metastatic sites.
Conclusion:
IBC and non-IBC patients presented with different metastatic frequencies, clinical features and prognostic outcomes. Our findings provide more information for therapeutic decision making and clinical study designs.
Keywords: advanced breast cancer, metastasis, molecular subtype, prognosis, SEER
Introduction
Breast cancer is the most common neoplasm in women.1 Breast cancer-related death is attributable mainly to metastasis.2 Despite the rapid advances in treatment methods in recent years, the prognostic outcome for metastatic breast cancer patients remains frustrating.3 Thus, a deep understanding of distant metastatic patterns is beneficial for diagnostic and therapeutic decisions in clinical practice.
Cancer metastasis is a multistep process that involves the escape of tumor cells from the primary location, systemic translocation in the body, and adaptation to the foreign microenvironment of distant sites.4 The spread of cancer cells is mediated by the interaction between tumor cells (seeds) and the microenvironment of the host organ (soil).5 Extensive studies have clarified several stages of the invasion-metastasis cascade, including epithelial-mesenchymal transition, angiogenesis, and immune invasion.6 Moreover, host organs could develop premetastatic niches and be prepared for cancer cell colonization.7 Therefore, specific organ microenvironments seem to be hospitable for the colonization and growth of certain types of cancer cells.8 By elucidating the distribution of metastatic sites in breast cancer, we can obtain a better understanding of the “seed and soil” interaction.
Inflammatory breast cancer (IBC) is an invasive type of breast cancer.9 IBC is characterized by tumor embolism of the dermal lymphatics, resulting in the rapid onset of skin changes. Compared with non-inflammatory breast cancer (non-IBC), IBC tends to show unfavorable prognosis, attributable mainly to a high risk of early distant metastasis.10 According to previous studies, more than 80% of IBC patients were reported to have regional lymph node invasion, and 30% presented with distant metastasis at the time of diagnosis.11 Therefore, it is vital to perform careful screening and start precise treatment for IBC.
Among different metastatic sites, bone seems to be the most frequent lesion for breast cancer.12 Several studies have indicated that breast cancer patients with bone metastasis survived longer than patients with visceral metastasis.13 Another retrospective study suggested that IBC patients with bone metastasis had a poorer prognosis than non-IBC patients with bone metastasis.14 Moreover, IBC patients have a relatively high risk of visceral metastasis and brain metastasis, leading to a dismal prognostic outcome.15,16
However, the metastatic profiles of IBC and non-IBC and their comparisons still need further elaboration. The clinical and prognostic values of different metastatic lesions need to be illustrated. Thus, in our research, we compared distant metastatic patterns between IBC and non-IBC, by analyzing accessible information from the Surveillance, Epidemiology and End Results (SEER) database. We also aimed to clarify the impact of IBC on prognosis in patients with different metastatic lesions.
Methods
Cohort population
A population-based retrospective study was conducted with data from the SEER national database. The patient selection process is illustrated in Figure 1. A total of 233,686 patients with a diagnosis of breast cancer between 2010 and 2014 were enrolled in this research. Patients were excluded if their metastatic status, follow-up information, or molecular type was unknown. Patients were classified into the IBC group and the non-IBC group. Data on metastasis to the bone, lung, liver, brain, and distant lymph node (DL) were recorded in the database.
Figure 1.

Flowchart of the patient selection process in this study.
SEER, Surveillance, Epidemiology and End Results database.
Ethics statement
This research was based on publicly available data from the SEER database (https://seer.cancer.gov/), and a data use agreement was assigned. This study received exemption from ethics approval by the ethics committee of Ruijin Hospital, Shanghai Jiao Tong University School of Medicine. The requirement for informed consent was also waived by the ethics committee of Ruijin Hospital because no direct interaction with patients was performed and no personal identification was applied in this study. In addition, this research was conducted in compliance with the Declaration of Helsinki.
Statistical analysis
We used descriptive statistics to summarize the patients’ clinical characteristics. The Chi-square test and Fisher’s exact test were used to compare the categorical parameters among different groups. Logistic regression was applied for multivariate analysis. Overall survival (OS) and breast cancer-specific survival (BCSS) were compared by the Kaplan–Meier method and log-rank test. We also performed multivariate Cox regression models to assess independent prognostic factors. A two-sided p value < 0.05 was defined as statistically significant. We used GraphPad Prism 6 (GraphPad Software, San Diego, CA, USA) and SPSS 22.0 (SPSS Inc. Chicago, IL, USA) to perform statistical analyses.
Results
Patient characteristics
In total, 233,686 breast cancer patients were finally enrolled in our research, including 2806 IBC and 230,880 non-IBC patients. The detailed baseline clinical characteristics are described in Table 1. Parameters including molecular subtype, age, marital status, race, grade, tumor size, and regional lymph node invasion showed significant differences between the two groups. Compared with the non-IBC group, the IBC group tended to have a higher incidence of the human epidermal growth factor receptor 2 positive (HER2+) and triple-negative breast cancer (TNBC) subtypes, older age, a higher rate of unmarried status, a lower incidence of black race, poorer tumor differentiation, larger tumor sizes, and a higher frequency of regional lymph node invasion. Regarding therapies, fewer IBC patients underwent surgery and more IBC patients received chemotherapy and radiation therapy than non-IBC patients.
Table 1.
Baseline clinical characteristics of IBC and non-IBC patients in the SEER database.
| Characteristics | IBC (n = 2806) |
Non-IBC (n = 230,880) |
p |
|---|---|---|---|
| Molecular subtype | <0.001 | ||
| HR+/HER2– | 1118 (39.8%) | 169,803 (73.5%) | |
| HR+/HER2+ | 521 (18.6%) | 24,599 (10.7%) | |
| HR–/HER2+ | 482 (17.2%) | 10,457 (4.5%) | |
| TNBC | 685 (24.4%) | 26,021 (11.3%) | |
| Age | <0.001 | ||
| <50 | 831 (29.6%) | 51,616 (22.3%) | |
| 51–65 | 1178 (42.0%) | 89,982 (39.0%) | |
| ⩾65 | 797 (28.4%) | 89,282(38.7%) | |
| Marital status | <0.001 | ||
| Married | 1291 (46.0%) | 127,478 (55.2%) | |
| Unmarried | 1379 (49.1%) | 91,183 (39.5%) | |
| Unknown | 136 (4.9%) | 12,219 (5.3%) | |
| Race | <0.001 | ||
| White | 2130 (75.9%) | 182,143 (78.9%) | |
| Black | 474 (16.9%) | 23,017 (10.0%) | |
| Others∆ | 202 (7.2%) | 25,720 (11.1%) | |
| Grade | <0.001 | ||
| I | 73 (2.6%) | 50,591 (21.9%) | |
| II | 709 (25.2%) | 97,249 (42.1%) | |
| III | 1637 (58.3%) | 72,869 (31.6%) | |
| Unknown | 387 (13.8%) | 10,171 (4.4%) | |
| Size (cm) | <0.001 | ||
| <2.0 | 244 (8.7%) | 125,928 (54.6%) | |
| 2.0–4.9 | 659 (23.5%) | 80,215 (34.7%) | |
| ⩾5.0 | 1114 (39.7%) | 19,857 (8.6%) | |
| Unknown | 789 (28.1%) | 4880 (2.1%) | |
| Regional lymph node invasion | <0.001 | ||
| N0 | 344 (12.2%) | 154,765 (67.0%) | |
| N1 | 1279 (45.6%) | 54,595 (23.7%) | |
| N2 | 506 (18.0%) | 12,298 (5.3%) | |
| N3 | 611 (21.8%) | 7516 (3.3%) | |
| NX | 66 (2.4%) | 1706 (0.7%) | |
| Surgery | <0.001 | ||
| Yes | 1809 (64.5%) | 214,167 (92.8%) | |
| No | 997 (35.5%) | 16,713 (7.2%) | |
| Chemotherapy | <0.001 | ||
| Yes | 2395 (85.4%) | 95,740 (41.5%) | |
| No | 411 (14.6%) | 135,140 (58.5%) | |
| Radiation therapy | 0.384 | ||
| Yes | 1599 (57.0%) | 129,672 (56.2%) | |
| No | 1207 (43.0%) | 101,208 (43.8%) |
∆Others include American Indian, AK Native, Asian, and Pacific Islander.
HER2, human epidermal growth factor receptor 2; HR, hormone receptor; IBC, inflammatory breast cancer; non-IBC, non-inflammatory breast cancer; SEER, Surveillance, Epidemiology and End Results; TNBC, triple-negative breast cancer.
Among all the included patients, 11,439 patients (4.9%) were recorded as having distant metastasis at the time of diagnosis. Based on metastasis data extracted from the SEER database, the five metastatic lesions (bone, brain, liver, lung, and DL) accounted for 94.4% (10,804/11,439) of all metastatic cases. Bone, which accounted for 65.9% (7543/11,439) of all metastatic cases, was the most frequent metastatic lesion. The brain was the least frequent lesion, accounting for 7.1% (816/11,439).
Metastatic patterns
The frequencies of different sites were compared between IBC and non-IBC. The metastatic rates of all sites in IBC were much higher than those in non-IBC (Figure 2). To further validate this finding, multivariate analysis was performed to adjust for confounding variables including age, race, marital status, molecular subtype, grade, tumor size, regional lymph node invasion, and therapies. The results demonstrated that the IBC group tended to have more bone metastasis [odds ratio (OR) 2.082, 95% confidence interval (CI) 1.846–2.348, p < 0.001], lung metastasis (OR 1.802, 95% CI 1.567–2.073, p < 0.001), liver metastasis (OR 1.531, 95% CI 1.319–1.777, p < 0.001), brain metastasis (OR 1.321, 95% CI 1.012–1.725, p = 0.041), and DL metastasis (OR 2.868, 95% CI 2.500–3.290, p < 0.001) than the non-IBC group (Table 2). Regarding metastatic distribution, both IBC and non-IBC shared similar trends, indicating that bone was the most common lesion in both IBC (21.1%) and non-IBC (3.0%) patients (followed by DL, lung, liver, and brain).
Figure 2.

Comparison of the frequencies of different sites between IBC and non-IBC.
*p < 0.05, **p < 0.01, ***p < 0.001
DL, distant lymph node; IBC, inflammatory breast cancer; non-IBC, non-inflammatory breast cancer.
Table 2.
Multivariate analyses of the impact of IBC on different metastatic sites.
| Variable | Metastatic site | OR | 95% CI | p |
|---|---|---|---|---|
| IBC versus non-IBC | Bone | 2.082 | 1.846–2.348 | <0.001 |
| Lung | 1.802 | 1.567–2.073 | <0.001 | |
| Liver | 1.531 | 1.319–1.777 | <0.001 | |
| Brain | 1.321 | 1.012–1.725 | 0.041 | |
| DL | 2.868 | 2.500–3.290 | <0.001 |
Adjusted for age, race, marital status, molecular subtype, grade, tumor size, regional lymph node invasion, and therapies.
CI, confidence interval; DL, distant lymph node; IBC, inflammatory breast cancer; non-IBC, non-inflammatory breast cancer; OR, odds ratio.
We further explored the impact of molecular subtypes on metastatic sites in IBC and non-IBC cases (Figure 3A,B). For all patients with metastasis, the percentage of hormone receptor positive (HR+)/human epidermal growth factor receptor 2 negative (HER2–) was much lower in IBC patients (42.6%) than in non-IBC patients (61.6%). The percentage of the HR+/HER2– subtype gradually decreased in patients with lung (42.5%), DL (41.5%), liver (31.3%) and brain (30.6%) metastases compared with bone (50.8%) metastasis in the IBC cohort. The same trend of the HR+/HER2– subtype was found in the non-IBC cohort. Compared with the whole cohort, the percentage of HR+/HER2+ and hormone receptor negative (HR–)/HER2+ subtypes increased most in patients with liver metastasis in both the IBC (HR+/HER2+: 24.4%, HR–/HER2+: 21.5%) and non-IBC (HR+/HER2+: 23.9%, HR–/HER2+: 15.1%) groups. We also found that, in both IBC and non-IBC cases, the proportion of visceral metastases increased in the TNBC subtype, especially brain metastasis (IBC: 26.4%, non-IBC: 21.2%), which had the largest increase.
Figure 3.

Distribution of molecular subtypes in IBC (A) and non-IBC (B).
DL, distant lymph node; HR, hormone receptor; HER2, human epidermal growth factor receptor 2; IBC, inflammatory breast cancer; MET, metastasis; non-IBC, non-inflammatory breast cancer; TNBC, triple negative breast cancer.
Combination of metastases
A large number of patients show multiorgan metastasis at the time of diagnosis. Pie charts illustrating the relative rates of single-organ and multi-organ metastases are shown in Figure 4. In the IBC cohort, bone, and DL were the two leading sites for single-site metastasis (Figure 4A). However, in the non-IBC group, only bone was the leading lesion for single-site metastasis (Figure 4B). For co-metastases, the bi-organ pattern (IBC: 28.4%, non-IBC: 24.4%) showed predominance over the tri-organ (IBC: 10.9%, non-IBC: 7.6%), tetra-organ (IBC: 4.2%, non-IBC: 3.2%), and penta-organ (IBC: 0.2%, non-IBC: 0.6%) patterns.
Figure 4.

Relative rates of single-organ and multi-organ metastatic sites in IBC (A) and non-IBC (B).
DL, distant lymph node; IBC, inflammatory breast cancer; non-IBC, non-inflammatory breast cancer.
The frequencies of all possible combinations of the five metastatic lesions were compared between the IBC and non-IBC cohorts (Table 3). The most frequent bi-site metastasis was the bone and liver (IBC: 2.5%, non-IBC: 0.3%). The most frequent tri-site combination was the bone, lung, and liver (IBC: 1.1%, non-IBC: 0.2%). Significant differences existed between the two groups in the frequencies of most of the metastatic combinations.
Table 3.
Frequencies of combined de novo metastases.
| Features | IBC (n = 2806) |
non-IBC (n = 230,880) |
p | ||
|---|---|---|---|---|---|
| Number | (%) | Number | (%) | ||
| One site | |||||
| Only bone | 238 | 8.482 | 3616 | 1.566 | <0.001 |
| Only lung | 79 | 2.815 | 759 | 0.329 | <0.001 |
| Only liver | 48 | 1.711 | 715 | 0.310 | <0.001 |
| Only brain | 8 | 0.285 | 122 | 0.053 | <0.001 |
| Only DL | 139 | 4.954 | 655 | 0.284 | <0.001 |
| Two sites | |||||
| Bone and lung | 62 | 2.210 | 736 | 0.319 | <0.001 |
| Bone and liver | 69 | 2.459 | 702 | 0.304 | <0.001 |
| Bone and brain | 17 | 0.606 | 151 | 0.065 | <0.001 |
| Bone and DL | 65 | 2.316 | 384 | 0.166 | <0.001 |
| Lung and liver | 23 | 0.820 | 168 | 0.073 | <0.001 |
| Lung and brain | 5 | 0.178 | 47 | 0.020 | <0.001 |
| Lung and DL | 31 | 1.105 | 236 | 0.102 | <0.001 |
| Liver and brain | 3 | 0.107 | 18 | 0.008 | 0.002 |
| Liver and DL | 11 | 0.392 | 82 | 0.036 | <0.001 |
| Brain and DL | 1 | 0.036 | 16 | 0.007 | 0.186 |
| Three sites | |||||
| Bone and lung and liver | 32 | 1.140 | 351 | 0.152 | <0.001 |
| Bone and lung and brain | 7 | 0.249 | 71 | 0.031 | <0.001 |
| Bone and lung and DL | 26 | 0.927 | 16 | 0.007 | <0.001 |
| Bone and liver and brain | 4 | 0.143 | 53 | 0.023 | 0.005 |
| Bone and liver and DL | 26 | 0.927 | 172 | 0.074 | <0.001 |
| Bone and brain and DL | 4 | 0.143 | 28 | 0.012 | 0.001 |
| Lung and liver and brain | 2 | 0.071 | 17 | 0.007 | 0.022 |
| Lung and liver and DL | 8 | 0.285 | 73 | 0.032 | <0.001 |
| Liver and brain and DL | 1 | 0.036 | 6 | 0.003 | 0.081 |
| Four sites | |||||
| Bone and lung and liver and brain | 10 | 0.356 | 77 | 0.033 | <0.001 |
| Bone and lung and liver and DL | 27 | 0.962 | 189 | 0.082 | <0.001 |
| Bone and lung and brain and DL | 1 | 0.036 | 41 | 0.018 | 0.398 |
| Bone and liver and brain and DL | 2 | 0.071 | 15 | 0.006 | 0.017 |
| Lung and liver and brain and DL | 2 | 0.071 | 8 | 0.003 | 0.006 |
| Five sites | |||||
| Bone and Lung and liver and brain and DL | 2 | 0.071 | 58 | 0.025 | 0.162 |
DL, distant lymph node; IBC, inflammatory breast cancer; non-IBC, non-inflammatory breast cancer.
In addition, the interactions among these metastatic lesions were further analyzed (Figure 5A–E). IBC patients with bone metastasis had a higher rate of metastasis to the liver (6.1%) than DL (6.0%), lung (5.5%) and brain (1.7%). However, non-IBC patients with bone metastasis had a higher incidence rate of lung metastasis (0.8%) than metastasis to the liver (0.7%), DL (0.5%) and brain (0.2%). Patients with liver, lung, brain or DL metastasis all had a higher incidence rate of bone metastasis than other lesions. We also noticed that the liver preferentially co-metastasized with bone in the IBC and non-IBC cohort. Brain metastasis was specifically associated with bone and lung metastases.
Figure 5.
Comparisons of co-metastatic rates in IBC and non-IBC. (A) Bone metastasis with other sites; (B) Lung metastasis with other sites; (C) Liver metastasis with other sites; (D) Brain metastasis with other sites; (E) DL metastasis with other sites.
*p < 0.05, **p < 0.01, ***p < 0.001.
DL, distant lymph node; IBC, inflammatory breast cancer; MET, metastasis; non-IBC, non-inflammatory breast cancer.
Survival
In our research, 974 deaths in the IBC cohort (34.7%) and 16,829 deaths in the non-IBC cohort (7.3%) were observed. The Kaplan–Meier curves suggested that the IBC cohort had poorer OS and BCSS than the non-IBC group (Figure 6A,B). The multivariate analyses further confirmed IBC as an independent prognostic factor for OS [hazard ratio (HR) 1.602, 95% CI 1.496–1.716, p < 0.001] and BCSS (HR 1.511, 95% CI 1.402–1.628, p < 0.001) (Table 4, Supplemental Table S1). We assessed the impact of IBC on patient survival according to different molecular subtypes. The IBC cohort showed poorer OS and BCSS than the non-IBC cohort in all molecular subtypes, including HR+/HER2–, HR+/HER2+, HR–/HER2+ and TNBC (Supplemental Figure 1A,B).
Figure 6.
Kaplan–Meier curves of the impact of IBC on overall survival (A) and breast cancer-specific survival (B).
IBC, inflammatory breast cancer; non-IBC, non-inflammatory breast cancer.
Table 4.
Univariate and multivariate analyses for OS.
| Clinicopathological characteristics | Univariable analysis p | Multivariable analysis | |
|---|---|---|---|
| Hazard ratio (95% CI) | p | ||
| IBC/non-IBC | <0.001 | <0.001 | |
| non-IBC | Reference | ||
| IBC | 1.602 (1.496–1.716) | <0.001 | |
| Age | <0.001 | <0.001 | |
| <50 | Reference | ||
| 50–64 | 1.256 (1.198–1.317) | <0.001 | |
| ⩾65 | 2.557 (2.443–2.675) | <0.001 | |
| Marital status | <0.001 | <0.001 | |
| Married | Reference | ||
| Unmarried | 1.468 (1.422–1.516) | <0.001 | |
| Unknown | 1.213 (1.136–1.295) | <0.001 | |
| Race | <0.001 | <0.001 | |
| White | Reference | ||
| Black | 0.616 (0.575–0.660) | <0.001 | |
| Others∆ | 0.849 (0.815–0.884) | <0.001 | |
| Molecular subtype | <0.001 | <0.001 | |
| HR+/HER2– | Reference | ||
| HR+/HER2+ | 0.908 (0.862–0.958) | <0.001 | |
| HR–/HER2+ | 1.255 (1.177–1.337) | <0.001 | |
| TNBC | 2.430 (2.332–2.532) | <0.001 | |
| Grade | <0.001 | <0.001 | |
| I | Reference | ||
| II | 1.173 (1.113–1.237) | <0.001 | |
| III | 1.836 (1.737–1.941) | <0.001 | |
| Unknown | 1.464 (1.366–1.569) | <0.001 | |
| Size (cm) | <0.001 | <0.001 | |
| <2.0 | Reference | ||
| 2.0–4.9 | 1.829 (1.758–1.904) | <0.001 | |
| ⩾5.0 | 2.711 (2.582–2.847) | <0.001 | |
| Unknown | 2.227 (2.087–2.376) | <0.001 | |
| Regional lymph node invasion | <0.001 | <0.001 | |
| N0 | Reference | ||
| N1 | 1.483 (1.428–1.541) | <0.001 | |
| N2 | 2.186 (2.071–2.307) | <0.001 | |
| N3 | 2.775(2.625–2.933) | <0.001 | |
| NX | 1.927(1.773–2.094) | <0.001 | |
| Bone metastasis | <0.001 | <0.001 | |
| No | Reference | ||
| Yes | 1.791 (1.703–1.884) | <0.001 | |
| Brain metastasis | <0.001 | <0.001 | |
| No | Reference | ||
| Yes | 2.370 (2.160–2.601) | <0.001 | |
| Liver metastasis | <0.001 | <0.001 | |
| No | Reference | ||
| Yes | 2.208 (2.078–2.346) | <0.001 | |
| Lung metastasis | <0.001 | <0.001 | |
| No | Reference | ||
| Yes | 1.421 (1.340–1.508) | <0.001 | |
| DL metastasis | <0.001 | 0.171 | |
| No | Reference | ||
| Yes | 1.048 (0.980–1.121) | 0.171 | |
| Surgery | <0.001 | <0.001 | |
| No | Reference | ||
| Yes | 0.303 (0.291–0.316) | <0.001 | |
| Chemotherapy | <0.001 | <0.001 | |
| No | Reference | ||
| Yes | 0.610 (0.588–0.632) | <0.001 | |
| Radiation therapy | <0.001 | <0.001 | |
| No | Reference | ||
| Yes | 0.650 (0.630–0.672) | <0.001 | |
∆Others include American Indian, AK Native, Asian, and Pacific Islander.
HER2, human epidermal growth factor receptor 2; HR, hormone receptor; IBC, inflammatory breast cancer; non-IBC, non-inflammatory breast cancer; OS, overall survival; TNBC, triple-negative breast cancer.
Moreover, univariate and multivariate analyses were performed to assess the impact of IBC on the prognosis of patients with different metastatic sites. The Kaplan–Meier curves indicated that the IBC group had poorer OS and BCSS than the non-IBC group at different metastatic sites, including bone, lung, liver, and DL (Supplemental Figure S2A,B). The multivariate analysis further indicated that IBC was an independent prognostic factor for OS in different metastatic sites, including bone (HR 1.366, 95% CI 1.213–1.539, p < 0.001), lung (HR 1.178, 95% CI 1.010–1.374, p = 0.037), liver (HR 1.349, 95% CI 1.144–1.591, p < 0.001), and DL node (HR 1.236, 95% CI 1.044–1.463, p = 0.014) (Table 5). For BCSS, IBC was also an independent predictive factor in patients with bone metastasis (HR 1.363, 95% CI 1.202–1.546, p < 0.001), lung metastasis (HR 1.228, 95% CI 1.047–1.441, p = 0.012), liver metastasis (HR 1.358, 95% CI 1.143–1.612, p < 0.001), and distant lymph node metastasis (HR 1.214, 95% CI 1.015–1.452, p = 0.034) (Supplemental Table S2).
Table 5.
Multivariate analyses of the impact of IBC on overall survival inpatients with different metastatic sites.
| Variable | Metastatic site | OS | |
|---|---|---|---|
| HR (95% CI) | p | ||
| IBC versus non-IBC | Bone | 1.366 (1.213–1.539) | <0.001 |
| Lung | 1.178 (1.010–1.374) | 0.037 | |
| Liver | 1.349 (1.144–1.591) | <0.001 | |
| Brain | 1.143 (0.845–1.545) | 0.386 | |
| DL | 1.236 (1.044–1.463) | 0.014 | |
Adjusted for age, race, marital status, molecular subtype, grade, tumor size, regional lymph node invasion and therapies. CI, confidence interval; DL, distant lymph node; HR, hazard ratio; IBC, inflammatory breast cancer; non-IBC, non-inflammatory breast cancer; OS, overall survival.
Discussion
Distant metastasis remains a vital problem in breast cancer, contributing to the majority of cancer-related deaths. Among all types of breast cancer, IBC is a fatal subtype with a high frequency of early distant metastasis. Therefore, it is important to compare the metastatic patterns between IBC and non-IBC. In the present research, we mainly achieved the following: (a) elaborated the distribution of single-site metastases; (b) clarified the impact of molecular subtypes on metastatic sites; (c) identified the patterns of co-metastases; and (d) compared prognostic outcomes and clinicopathological features between IBC and non-IBC. To the best of our knowledge, our research is the first comprehensive, population-based study comparing metastatic profiles between IBC and non-IBC. Thus, we hope that our research could be helpful in future clinical and translational studies in breast cancer.
By comparing the metastatic frequencies between IBC and non-IBC, we suggested that the metastatic rates of all sites in IBC were extraordinarily higher than those of non-IBC. Adjusting for confounding clinical variables, multivariate analyses further demonstrated that the inflammatory nature of IBC increased the metastatic frequency in all sites. Consistent with the results reported in previous publications, the bone and brain were the most and least frequent lesions, respectively, in the whole breast cancer cohort.17 We further studied the relationship between molecular subtype and metastasis. In both groups, the percentage of the HR+/HER2– subtype decreased in patients with lung, DL, liver, and brain metastases compared with bone metastasis. Previous studies have suggested that TNBC has a relatively high rate of brain metastasis,18,19 and our study also indicated that the proportion of visceral metastases increased in the TNBC subtype, especially brain metastasis, which showed the largest increase.
Of note, approximately 30% of patients with distant metastasis developed more than one metastatic lesion. Therefore, we analyzed the patterns of combined metastases in the IBC and non-IBC groups. It was suggested that DL was the leading site of single-site metastasis in IBC but not in non-IBC, which could be attributed to the clinical characteristics of tumor infiltration in lymphatics and regional lymph node invasion. Consistent with the findings in other solid tumors, the bi-organ pattern was far more common than the tri-organ, tetra-organ and penta-organ patterns in both inflammatory and non-inflammatory breast cancer.20,21 Among all combined metastases, the most frequent bi-organ metastatic pattern was the bone and liver, and the most frequent tri-organ metastasis was the bone, lung, and liver. Moreover, brain metastasis was preferentially correlated with bone and lung metastasis. The above results indicated that clinical physicians need to be aware of the possibility of combined metastases in different sites and make more accurate diagnoses and treatments for multiorgan metastasis.
We further focused on clinicopathological parameters and their prognostic significance in the two cohorts. Several clinical features including molecular subtype, age, marital status, race, and grade varied between the two groups. Compared with the non-IBC cohort, the IBC cohort had a higher incidence of the HER2+ and TNBC subtypes, older age, a higher rate of unmarried status, a lower incidence of black race, poorer tumor differentiation, larger tumor sizes, and a higher frequency of regional lymph node invasion. Notably, the IBC cohort tended to have a higher incidence of unmarried status, which could have several reasons. A possible explanation for this result may be the psychosocial perspective. Lacking support from spouses, unmarried patients may suffer from psychological stress, which alters neuroendocrine mediators, metabolic status, and immune system, thus facilitating tumor initiation and progression.22–24 Distressed psychological status may lead to bad habits, such as smoking and excessive alcohol consumption, also resulting in the development of cancer.25–27 Another finding is that marriage could increase the possibility of early diagnosis. Adekolujo et al. and Hinyard et al. found that unmarried patients showed a higher risk for late-stage diagnosis of breast cancer compared with married patients.28,29 Moreover, marital status partially reflects financial status, which could affect routine clinical visits and the quality of medical care. Several previous studies have indicated that IBC contributes to a large proportion of breast cancer in low-income populations.30,31 Regarding therapies, fewer IBC patients undergo surgery and more IBC patients undergo chemotherapy than non-IBC patients, which is due mainly to the tumor biology and metastatic potential of IBC. Moreover, univariate and multivariate analyses suggested that the IBC group showed poorer prognosis than the non-IBC group. In addition, adjusting for clinical and treatment variables, we found that IBC was an independent prognostic factor for patients with different metastatic sites.
We believe that our research could be conducive to the clinical practice. First, clinical and molecular subtypes could help clinicians recognize patients at high risk for distant metastasis. Second, knowledge of the patterns of site-specific metastases would improve study designs for precision medicine. Third, patients with bone-only metastasis may benefit from primary tumor operation and show favorable prognostic outcomes.32
As far as we know, this is the first population-based study summarizing the metastatic patterns in IBC and non-IBC. However, several potential limitations may exist in this retrospective study. The first limitation may be the retrospective nature of this study. Second, the SEER database only includes metastatic data in five sites (bone, lung, liver, brain, and DL node). However, we found that these five lesions accounted for 94.4% of all metastatic patients, and few patients with metastasis in other lesions were missing. Third, since detailed information on metastasis and molecular subtype was provided by the SEER database from 2010, we enrolled patients only between 2010 and 2014. Furthermore, the majority of the included cases were Caucasian and black, so the results needed to be validated in external cohorts, especially in Asian cohorts. Additionally, some patients may develop metachronous metastasis, which was unknown from the SEER database. Thus, we suggest that further prospective studies be performed to validate our findings.
In summary, in this population-based retrospective study, we compared metastatic patterns between IBC and non-IBC cases. We found that IBC and non-IBC patients presented with different metastatic frequencies, clinical features, and prognostic outcomes. Our findings provide more information for therapeutic decision making and clinical study designs.
Supplemental Material
Supplemental material, Supplementary_Table_1_1 for A large-cohort retrospective study of metastatic patterns and prognostic outcomes between inflammatory and non-inflammatory breast cancer by Zheng Wang, Hui Wang, Xinyuan Ding, Xiaosong Chen and Kunwei Shen in Therapeutic Advances in Medical Oncology
Supplemental material, Supplementary_Table_2 for A large-cohort retrospective study of metastatic patterns and prognostic outcomes between inflammatory and non-inflammatory breast cancer by Zheng Wang, Hui Wang, Xinyuan Ding, Xiaosong Chen and Kunwei Shen in Therapeutic Advances in Medical Oncology
Footnotes
Conflict of interest statement: The authors declare that there is no conflict of interest.
Funding: The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This study was supported by the National Natural Science Foundation of China (81772797), Shanghai Municipal Education Commission—Gaofeng Clinical Medicine Grant Support (20172007), Ruijin Hospital, Shanghai Jiao Tong University School of Medicine-“Guangci Excellent Youth Training Program” (GCQN-2017-A18), China Postdoctoral Science Foundation (2019M651529), Shanghai Sailing Program (17YF1401600) and Ruijin Youth NSFC Cultivation Fund (2019QNPY01046).
Supplemental material: Supplemental material for this article is available online.
Contributor Information
Zheng Wang, Department of General Surgery, Comprehensive Breast Health Center, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, 197 Ruijin Er Road, Shanghai 200025, China.
Hui Wang, Department of General Surgery, Comprehensive Breast Health Center, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Xinyuan Ding, Department of Pharmacy, the Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou, China.
Xiaosong Chen, Department of General Surgery, Comprehensive Breast Health Center, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, 197 Ruijin Er Road, Shanghai 200025, China.
Kunwei Shen, Department of General Surgery, Comprehensive Breast Health Center, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, 197 Ruijin Er Road, Shanghai 200025, China.
References
- 1. Siegel RL, Miller KD, Jemal A. Cancer statistics, 2019. CA Cancer J Clin 2019; 69: 7–34. [DOI] [PubMed] [Google Scholar]
- 2. Kozlowski J, Kozlowska A, Kocki J. Breast cancer metastasis - insight into selected molecular mechanisms of the phenomenon. Postepy Hig Med Dosw (Online) 2015; 69: 447–451. [DOI] [PubMed] [Google Scholar]
- 3. Lee ES, Jung SY, Kim JY, et al. Identifying the potential long-term survivors among breast cancer patients with distant metastasis. Ann Oncol 2016; 27: 828–833. [DOI] [PubMed] [Google Scholar]
- 4. Valastyan S, Weinberg RA. Tumor metastasis: molecular insights and evolving paradigms. Cell 2011; 147: 275–292. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5. Akhtar M, Haider A, Rashid S, et al. Paget’s “seed and soil” theory of cancer metastasis: an idea whose time has come. Adv Anat Pathol 2019; 26: 69–74. [DOI] [PubMed] [Google Scholar]
- 6. de Groot AE, Roy S, Brown JS, et al. Revisiting seed and soil: examining the primary tumor and cancer cell foraging in metastasis. Mol Cancer Res 2017; 15: 361–370. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7. Psaila B, Lyden D. The metastatic niche: adapting the foreign soil. Nat Rev Cancer 2009; 9: 285–293. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8. Fidler IJ. The pathogenesis of cancer metastasis: the ‘seed and soil’ hypothesis revisited. Nat Rev Cancer 2003; 3: 453–458. [DOI] [PubMed] [Google Scholar]
- 9. Mamouch F, Berrada N, Aoullay Z, et al. Inflammatory breast cancer: a literature review. World J Oncol 2018; 9: 129–135. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10. Rueth NM, Lin HY, Bedrosian I, et al. Underuse of trimodality treatment affects survival for patients with inflammatory breast cancer: an analysis of treatment and survival trends from the National Cancer Database. J Clin Oncol 2014; 32: 2018–2024. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11. Walshe JM, Swain SM. Clinical aspects of inflammatory breast cancer. Breast Dis 2005; 22: 35–44. [DOI] [PubMed] [Google Scholar]
- 12. Coleman RE. Clinical features of metastatic bone disease and risk of skeletal morbidity. Clin Cancer Res 2006; 12: 6243s–6249s. [DOI] [PubMed] [Google Scholar]
- 13. Ahn SG, Lee HM, Cho SH, et al. Prognostic factors for patients with bone-only metastasis in breast cancer. Yonsei Med J 2013; 54: 1168–1177. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14. Kai M, Kogawa T, Liu DD, et al. Clinical characteristics and outcome of bone-only metastasis in inflammatory and noninflammatory breast cancers. Clin Breast Cancer 2015; 15: 37–42. [DOI] [PubMed] [Google Scholar]
- 15. Brufsky AM, Mayer M, Rugo HS, et al. Central nervous system metastases in patients with HER2-positive metastatic breast cancer: incidence, treatment, and survival in patients from registHER. Clin Cancer Res 2011; 17: 4834–4843. [DOI] [PubMed] [Google Scholar]
- 16. Solomayer EF, Diel IJ, Meyberg GC, et al. Metastatic breast cancer: clinical course, prognosis and therapy related to the first site of metastasis. Breast Cancer Res Treat 2000; 59: 271–278. [DOI] [PubMed] [Google Scholar]
- 17. Xiao W, Zheng S, Yang A, et al. Breast cancer subtypes and the risk of distant metastasis at initial diagnosis: a population-based study. Cancer Manag Res 2018; 10: 5329–5338. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18. Dawood S, Broglio K, Esteva FJ, et al. Survival among women with triple receptor-negative breast cancer and brain metastases. Ann Oncol 2009; 20: 621–627. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19. Miller KD, Weathers T, Haney LG, et al. Occult central nervous system involvement in patients with metastatic breast cancer: prevalence, predictive factors and impact on overall survival. Ann Oncol 2003; 14: 1072–1077. [DOI] [PubMed] [Google Scholar]
- 20. Wang X, Yu GY, Chen M, et al. Pattern of distant metastases in primary extrahepatic bile-duct cancer: a SEER-based study. Cancer Med 2018; 7: 5006–5014. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21. Wu W, He X, Andayani D, et al. Pattern of distant extrahepatic metastases in primary liver cancer: a SEER based study. J Cancer 2017; 8: 2312–2318. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22. Chida Y, Hamer M, Wardle J, et al. Do stress-related psychosocial factors contribute to cancer incidence and survival? Nat Clin Pract Oncol 2008; 5: 466–475. [DOI] [PubMed] [Google Scholar]
- 23. Moreno-Smith M, Lutgendorf SK, Sood AK. Impact of stress on cancer metastasis. Future Oncol 2010; 6: 1863–1881. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24. Liang X, Margolis KL, Hendryx M, et al. Effect of depression before breast cancer diagnosis on mortality among postmenopausal women. Cancer 2017; 123: 3107–3115. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25. Surman M, Janik ME. Stress and its molecular consequences in cancer progression. Postepy Hig Med Dosw (Online) 2017; 71: 485–499 [DOI] [PubMed] [Google Scholar]
- 26. Goldzweig G, Andritsch E, Hubert A, et al. Psychological distress among male patients and male spouses: what do oncologists need to know? Ann Oncol 2010; 21: 877–883. [DOI] [PubMed] [Google Scholar]
- 27. Goldzweig G, Andritsch E, Hubert A, et al. How relevant is marital status and gender variables in coping with colorectal cancer? A sample of middle-aged and older cancer survivors. Psycho-oncology 2009; 18: 866–874. [DOI] [PubMed] [Google Scholar]
- 28. Adekolujo OS, Tadisina S, Koduru U, et al. Impact of marital status on tumor stage at diagnosis and on survival in male breast cancer. Am J Mens Health. 2017; 11: 1190–1199. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29. Hinyard L, Wirth LS, Clancy JM, et al. The effect of marital status on breast cancer-related outcomes in women under 65: a SEER database analysis. Breast 2017; 32: 13–17. [DOI] [PubMed] [Google Scholar]
- 30. Soliman AS, Kleer CG, Mrad K, et al. Inflammatory breast cancer in North Africa: comparison of clinical and molecular epidemiologic characteristics of patients from Egypt, Tunisia, and Morocco. Breast Dis 2011; 33: 159–169. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31. Soliman AS, Schairer C. Considerations in setting up and conducting epidemiologic studies of cancer in middle- and low-income countries: the experience of a case-control study of inflammatory breast cancer in North Africa in the past 10 years. Cancer Med 2012; 1: 338–349. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 32. Harris E, Barry M, Kell MR. Meta-analysis to determine if surgical resection of the primary tumour in the setting of stage IV breast cancer impacts on survival. Ann Surg Oncol 2013; 20: 2828–2834. [DOI] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Supplemental material, Supplementary_Table_1_1 for A large-cohort retrospective study of metastatic patterns and prognostic outcomes between inflammatory and non-inflammatory breast cancer by Zheng Wang, Hui Wang, Xinyuan Ding, Xiaosong Chen and Kunwei Shen in Therapeutic Advances in Medical Oncology
Supplemental material, Supplementary_Table_2 for A large-cohort retrospective study of metastatic patterns and prognostic outcomes between inflammatory and non-inflammatory breast cancer by Zheng Wang, Hui Wang, Xinyuan Ding, Xiaosong Chen and Kunwei Shen in Therapeutic Advances in Medical Oncology


