Radiotherapy after mastectomy has significant survival benefits for inflammatory breast cancer: a SEER population-based retrospective study

Ethics statement

The National Cancer Institute’s SEER program, initiated from 1973 and annually updated, uses population-based data to develop comprehensive sources (Duggan et al., 2016). It covers approximately 30% of the US population throughout several geographic regions (Cronin, Ries & Edwards, 2014). The SEER Research Data Agreement was signed for accessing SEER information with the use of reference number 16462-Nov2016. Additionally, the research methods were performed to obtain data following approved guidelines. The data analysis was considered by the Office for Human Research Protection to be non-human subjects who were researched by the United States Department of Health and Human Services, as they were publicly available and de-identified. Thus, no approval was required by the institutional review board.

Study population

Patient data were acquired using the SEER database (Submission, November 2016). The SEER*State v8.3.5 tool, released on March 6, 2018, was used to determine and select eligible patients. Additionally, the study duration ranged from 2010 to December 2013. The inclusion criteria were as follows: (1) only primary female IBC patients undergoing mastectomy were selected; (2) IBC was diagnosed in line with the International Classification of Disease for Oncology, Third Edition (ICD-O-3; coded as 8530/3). The exclusion criteria were listed in the following: (1) patients were burdened with multiple primary tumors; (2) patients were only clinically diagnosed; (3) patients without mastectomy; (4) patients with preoperative radiotherapy or unknown sequence of radiotherapy; (5) patients with incomplete important clinicopathological information, including age at diagnosis, race, 7th AJCC tumor stage, and surgical style; (6) patients died within 3 months after surgery; (7) patients withoutprognostic information. The remaining patients were enrolled as SEER primary cohort.

Covariates and endpoints

Patients’ characteristics were analyzed according to the following 9 factors: age (<40, 40–60, or >60 years), race (white, black, or other), marital status (married, unmarried, unknown), tumor grade (Grade I/II, Grade III/IV, unknown), AJCC stage (IIIA, IIIB, IV), breast Subtype (Her2-/hormone receptor (HoR)+, Her2+/HoR-, Her2+/HoR+, Triple Negative, unknown); surgery (simple mastectomy, radical mastectomy), chemotherapy (no/unknown, yes), PMRT (no/unknown, yes). The widowed or single (having a domestic partner or never married) or separated or divorced were classified as unmarried. Age was further transformed into a categorical variable according to recognized cut-off values. Race was divided into white, black and other (including Asian/Pacific Islander, American Indian/Alaska native, and unknown). A simple mastectomy removes all breast tissue, the nipple, and areolar complex. An axillary dissection is not done. A radical mastectomy removes all breast tissue, the nipple, the areolar complex, and variable amounts of breast skin, which includes axillary lymph node dissection. In addition, all eligible subjects were restaged in accordance with the 8th AJCC TNM staging system. The HoR status of tumor was stratified into HoR-positive [ER+/PR+, ER-/PR+, and ER+/PR-] and HoR-negative (ER-/PR-). The definition of ER/PR+ disease was ofor over 1% cells stained positive (Howlader et al., 2014). Our research was limited to between 2010 and2013 because breast subtype was published from 2010 in the SEER database.

The primary endpoints in this research were overall survival (OS) as well as cancer-specific survival (CSS). CSS was defined as the interval from diagnosis to the last follow-up or death caused by IBC.OS was defined as the duration from diagnosis to the last follow-up or death. There was a predetermined cut-off date based on the SEER 2016 submission database, containing death information until 2014. Therefore, a cut-off date of December 31, 2014 was utilized in our study.

Propensity score matching (PSM)

In observational research, selection bias is unavoidable, leading to unevenly distributed confounding factors between two groups. A PSM is defined as the conditional possibility of assignment to a certain treatment given a vector of observed covariates (Little & Rubin, 2000). Thus, in order to decrease selection bias as well as unevenly distributed confounding factors, the PSM method was employed in this research (Pattanayak, Rubin & Zell, 2011). The logistic regression model was used to estimate propensity scores of all patients by enrolling all covariates potentially affecting patient survival, followed by the PSM plug-in of the SPSS software to estimate the propensity score of every case. PSM was performed afterward using 1:1 nearest-neighbor matching with a caliper of0.05 to obtain a matched pair. PSM was conducted between the PMRT group and the No-PMRT group of each subgroup.

Statistical analyses

Pearson’s χ2 or Fisher’s exact tests were utilized for comparison of clinicopathologic characteristics before and after PSM. Kaplan–Meier (K-M) method was utilized for estimation of the univariate analysis, along with the log-rank test to assess the differences of CSS and OS. Moreover, the risk of mortality was assessed by multivariate Cox proportional hazards regression models, which were also used for subgroup analyses. Variables with potential significance in the univariate analysis (P < 0.05) or clinically regarded as prognostic factors were further enrolled in multivariate analysis. All statistical analyses were conducted using SPSS software (SPSS Inc., Chicago, USA, version 19.0). Graph Pad Prism 5 was employed to generate the survival curve and forest plots. A two-sided P < 0.05 was considered as statistically significant.

Patient characteristics before and after PSM

In total, 293 cases were enrolled in this research. According to whether the patients received PMRT, two groups were defined: No-PMRT group (n = 108) and PMRT group (n = 185).The specific screening process was shown in Fig. 1. Patient characteristics in both cohorts were presented in Table 1. Only two patients had bilateral breast cancer. The median follow-up duration of all subjects was 27 months (5–59 months).The following variables, age, tumor grade, race, marital status, AJCC stage, breast subtype; surgery style and chemotherapy were included in PSM. The plot of the propensity distribution score was shown in File S1. Specifically, the PMRT group had a higher proportion of married and received chemotherapy before PSM. After PSM at a 1:1 ratio, there were 94 patients in each group, and all the baseline characteristics of the two groups were balanced.

CSS and OS of patients before and after PSM

Before PSM, patients in the PMRT group showed significantly higher 1- and 3-year OS rates than those in the No-PMRT group (97.8%, 70.2%, respectively vs. 87.8% and 56.0%, respectively; P = 0.034) (Fig. 2B). However, there was no difference of1-and 3-year CSS between the two groups (97.8%, 70.1%, respectively vs. 89.5%, 60.1%, respectively; P = 0.13) (Fig. 2A). After PSM, patients in the PMRT group harbored significantly higher 1- and 3-year CSS and OS rates [CSS (99.0%, 81.8% vs. 89.1% and 59.7%, respectively, P = 0.013); OS (99.0%, 81.8% vs. 88.2% and 58.2%, respectively, P = 0.0063)] (Fig. 3).

Prognostic factors for survival after PSM

Multivariate analysis of CSS and OS revealed that black ethnicity[CSS (HR:2.251, 95% CI [1.186–4.271], P = 0.029); OS (HR:2.076, 95% CI [1.102–3.912], P = 0.024)], AJCC stage IV [CSS (HR:4.837, 95% CI [2.548–9.180], P < 0.001); OS (HR:4.475, 95% CI [2.387–8.389])] and triple negative subtype [CSS (HR:3.387, 95% CI [1.697–6.762], P = 0.001); OS (HR:3.188, 95% CI [1.630–6.235], P = 0.001)] were independent unfavorable prognostic factors, and Her2+/HR+ subtype [CSS (HR:0.244, 95% CI [0.070–0.857], P = 0.028); OS (HR:0.225, 95% CI [0.065–0.785], P = 0.019)] and PMRT [CSS (HR:0.519, 95% CI [0.287–0.939], P = 0.030); OS (HR:0.480, 95% CI [0.269–0.859], P = 0.013)] were independent favorable prognostic factors (Table 2).

Subgroup analysis for OS and CSS after PSM

Subgroup analysis of CSS and OS demonstrated that nearly all study population could benefit survival from PMRT except those with stage IV (Figs. 4 and 5). Married patients could obtain significant benefit from PMRT in terms of CSS (HR: 0.32, 95% CI [0.11–0.89], P = 0.029). In addition, patients who aged 40–60 (HR: 0.39, 95% CI [0.17–0.90], P = 0.027), married (HR: 0.32, 95% CI [0.11–0.89], P = 0.029), and chemotherapy (HR: 0.50, 95% CI [0.26–0.95], P = 0.035) also acquired significant benefit from PMRT, in terms of OS.