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Prognosis of Metaplastic Breast Cancer: A Population-Based Matched Cohort Study.

Cancer medicine 2026 Vol.15(2) p. e71570

Bergman M, Schiza A, Boyaci C, Acs B, Matikas A, Hartman J, Valachis A

📝 환자 설명용 한 줄

[PURPOSE] Metaplastic breast cancer (metBC) is a rare subtype of breast cancer known for its challenging management.

🔬 핵심 임상 통계 (초록에서 자동 추출 — 원문 검증 권장)
  • 95% CI 0.83-1.82
  • HR 1.23
  • 추적기간 54 months

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BibTeX ↓ RIS ↓
APA Bergman M, Schiza A, et al. (2026). Prognosis of Metaplastic Breast Cancer: A Population-Based Matched Cohort Study.. Cancer medicine, 15(2), e71570. https://doi.org/10.1002/cam4.71570
MLA Bergman M, et al.. "Prognosis of Metaplastic Breast Cancer: A Population-Based Matched Cohort Study.." Cancer medicine, vol. 15, no. 2, 2026, pp. e71570.
PMID 41603205
DOI 10.1002/cam4.71570

Abstract

[PURPOSE] Metaplastic breast cancer (metBC) is a rare subtype of breast cancer known for its challenging management. The impact of this histological subtype on prognosis remains unclear.

[METHODS] Data were collected from the Swedish Cancer Registry between 2008 and 2018. Patients with metBC were matched 2:1 with breast cancer cases of no special type (NST). Survival outcomes were analyzed using cause-specific hazard models for breast cancer specific survival (BCSS) and Cox proportional-hazards models for overall survival (OS).

[RESULTS] In total, 127 metBC patients were matched 2:1 with 245 NST patients, with a median follow-up period of 54 months. When adjusted for matching variables and treatment-related characteristics, metBC was not significantly associated with either BCSS (cause-specific Hazard Ratio (HR): 1.13; 95% Confidence Interval (CI): 0.66-1.92) or OS (HR: 1.23; 95% CI: 0.83-1.82).

[CONCLUSION] With appropriate treatment, metBC may have survival outcomes comparable to NST. Larger studies with longer follow-up are needed to provide further insights.

MeSH Terms

Humans; Female; Breast Neoplasms; Prognosis; Middle Aged; Aged; Sweden; Registries; Metaplasia; Adult; Cohort Studies; Aged, 80 and over; Proportional Hazards Models