Adenosquamous carcinoma of the breast: a population-based study

Abstract

Background: To summarize the clinicopathological characteristics, prognosis, and management of breast adenosquamous carcinoma (ASC).

Methods: A population-based study was performed using retrospectively extracted data from the Surveillance, Epidemiology, and End Results database for breast cancer patients with histological diagnoses of ASC, infiltrating duct carcinoma (IDC) and squamous cell carcinoma (SCC) from 2004 to 2016.

Results: ASC presented similar tumor size but low histological grade and less lymph node metastasis compared to IDC. ASC expressed less positive rate of hormone receptors and barely HER2, which was similar with SCC. ASC patients underwent the similar surgical and systematic treatment as IDC, only with less radiotherapy. Median follow-up data of 78 months showed that the prognosis of IDC patients was better than that of ASC patients (all p < 0.05 for BCSM and OS). ASC was not an independent prognosis factor of breast cancer. After propensity score matching (PSM), no significant difference in BCSM nor OS was observed between ASC and IDC groups. In HR-negative patients, the prognosis of ASC was similar with that of IDC, and both were superior to SCC. In HR-positive patients, the 5-year survival rate of ASC was 63.5%, which was far less than that in ASC of HR-negative (81.0%). Multivariate analysis showed that older age (age > 60) and advanced AJCC-stage were independent factors of poor prognosis in ASC, breast-conserving surgery was also ideally suited for ASC.

Conclusions: ASC has unique clinicopathological characteristics and prognosis. It is imperative to focus on a more precise and personalized treatment management of ASC patients.

Keywords: Adenosquamous; Breast; Breast neoplasms; Carcinoma; Ductal; Prognosis; Squamous cell.

Fig. 1

Kaplan–Meier curve illustrates BCSM and OS for IDC, ASC, and SCC in original and matched samples. a Kaplan–Meier curve illustrates BCSM for IDC, ASC, and SCC patients in original samples (IDC vs. ASC p = 0.002; ASC vs SCC p = 0.008, log-rank test); b Kaplan–Meier curve illustrates OS for IDC, ASC, and SCC patients in original samples (IDC vs. ASC p = 0.001; ASC vs. SCC p = 0.001, log-rank test); c Kernel Density of IDC and ASC groups before PS matching; d Kernel Density of IDC and ASC groups after PS matching. e Kaplan–Meier curve illustrates BCSM for IDC, ASC, and SCC patients in matched samples (IDC vs. ASC p = 0.540; ASC vs. SCC p = 0.005, log-rank test); f Kaplan–Meier curve illustrates OS for IDC, ASC and SCC patients in matched samples (IDC vs. ASC p = 0.865; ASC vs. SCC p = 0.001, log-rank test)

Fig. 2

Kaplan–Meier curve illustrates BCSM and OS for IDC, ASC, and SCC in different HR subgroup. a Kaplan–Meier curve illustrates BCSM for IDC, ASC, and SCC in HR-negative subgroup (IDC vs. ASC p = 0.288; ASC vs. SCC p = 0.013, log-rank test); b Kaplan–Meier curve illustrates BCSM for IDC, ASC, and SCC in HR-positive subgroup (IDC vs. ASC p = 0.001; ASC vs. SCC p = 0.710, log-rank test); c Kaplan–Meier curve illustrates OS for IDC, ASC, and SCC in HR-negative subgroup (IDC vs. ASC p = 0.686; ASC vs. SCC p = 0.004, log-rank test); d Kaplan–Meier curve illustrates OS for IDC, ASC, and SCC in HR-positive subgroup (IDC vs. ASC p = 0.001; ASC vs. SCC p = 0.391, log-rank test)