18: Reassessing Estrogen Receptor Expression Thresholds for Prognosis Using Shape Restricted Modeling
Takeo Fujii
Co-Author
Center for Cancer Research, National Cancer Institute
Jing Ning
Co-Author
University of Texas, MD Anderson Cancer Center
Jing Qin
Co-Author
National Institute of Allergy and Infectious Diseases, NIH
Naoto Ueno
Co-Author
University of Hawaiʻi Cancer Center
Yu Shen
Co-Author
UT M.D. Anderson Cancer Center
Wenli Dong
First Author
UT MD Anderson Cancer Center
Wenli Dong
Presenting Author
UT MD Anderson Cancer Center
Tuesday, Aug 5: 10:30 AM - 12:20 PM
1293
Contributed Posters
Music City Center
We used a novel shape-restricted Cox model to determine the desirable ER expression cutoff to predict breast cancer prognoses. Our model treats ER as a continuous variable using a flexible monotone-shaped Cox regression to assess its association with survival outcomes holistically. The study included 3055 patients with stage II/III HER2-negative breast cancer. The primary outcomes were time to recurrence or death (TTR) and overall survival (OS). The shape-restricted Cox model identified 10% ER as the preferred cutoff to predict TTR. The finding was confirmed by the log-rank test and standard Cox model that patients with ER ≥ 10% had TTR benefit over ER < 10% (log-rank p < 0.001). No OS or TTR benefit of adjuvant endocrine therapy was observed in patients with 1% ≤ ER < 10% (HR 0.877, 95% CI 0.481 – 1.600, p = 0.668 for TTR and HR 0.698, 95% CI 0.337 – 1.446, p = 0.333 for OS). Using the shape-restricted Cox model, this study suggests a potential preferred threshold of 10% for predicting TTR, assisting physicians in effectively weighing the benefits and risks of adjuvant endocrine therapy for patients with ER < 10% disease, particularly in cases with severe adverse events.
Estrogen receptor
Threshold
Survival
Modelling
Endocrine therapy
Breast cancer
Main Sponsor
Section on Nonparametric Statistics
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