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Mammographic Density Reduction is Associated to the Prognosis in Asian Breast Cancer Patients Receiving Hormone Therapy

INTRODUCTION: Using mammographic density as a significant biomarker for predicting prognosis in adjuvant hormone therapy patients is controversial due to the conflicting results of recent studies. This study aimed to evaluate hormone therapy-induced mammographic density reduction and its association...

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Detalles Bibliográficos
Autores principales: Shia, Wei-Chung, Lin, Li-Sheng, Wu, Hwa-Koon, Chen, Chih-Jung, Chen, Dar-Ren
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9989438/
https://www.ncbi.nlm.nih.gov/pubmed/36866691
http://dx.doi.org/10.1177/10732748231160991
Descripción
Sumario:INTRODUCTION: Using mammographic density as a significant biomarker for predicting prognosis in adjuvant hormone therapy patients is controversial due to the conflicting results of recent studies. This study aimed to evaluate hormone therapy-induced mammographic density reduction and its association with prognosis in Taiwanese patients. METHODS: In this retrospective study, 1941 patients with breast cancer were screened, and 399 patients with estrogen receptor-positive breast cancer who received adjuvant hormone therapy were enrolled. The mammographic density was measured using a fully automatic estimation procedure based on full-field digital mammography. The prognosis included relapse and metastasis during treatment follow-up. The Kaplan-Meier method and Cox proportional hazards model were used for disease-free survival analysis. RESULTS: A mammographic density reduction rate >20.8%, measured preoperatively and after receiving hormone therapy from 12-18 months, was a significant threshold for predicting prognosis in patients with breast cancer. The disease-free survival rate was significantly higher in patients whose mammographic density reduction rate was >20.8% (P = .048). CONCLUSION: This study’s findings could help estimate the prognosis for patients with breast cancer and may improve the quality of adjuvant hormone therapy after enlarging the study cohort in the future.