Measuring Hormone Levels Could Improve Risk Assessment for Breast Cancer
The inclusion of multiple hormones—rather than just adding one or two individually—in breast cancer risk prediction models may improve prediction of the disease and could help better identify women who would benefit from chemoprevention, according to a study by Shelley S. Tworoger, PhD, Associate Professor in the Channing Division of Network Medicine at Brigham and Women’s Hospital and Harvard Medical School, and colleagues. The results were presented at the 12th Annual AACR International Conference on Frontiers in Cancer Prevention (Abstract C21).
The researchers identified 473 postmenopausal women with invasive breast cancers and 770 matching controls, none of whom were using postmenopausal hormones at the time of blood draw, and analyzed their levels of estradiol, estrone, estrone sulfate, testosterone, prolactin, and sex hormone–binding globulin (SHBG) in blood samples drawn 1 to 20 years before diagnosis. The researchers used two breast cancer prediction models, Gail and Rosner-Colditz, which take into account factors such as number of pregnancies and age at menarche but not levels of hormones in a woman’s blood, and added these hormones to evaluate how much risk prediction improved.
Study Methods and Results
After measuring the area under the curve (AUC)—where an AUC of 1 indicates that a perfect prediction can be made of which women will get breast cancer over the next 5 years—the researchers found that adding individual hormones improved the AUC of the Gail score by 0.02 to 0.076 units and the AUC of the Rosner-Colditz score by 0.002 to 0.039 units.
When the researchers divided the data into a training set and a test set, the simultaneous inclusion of estrone sulfate, testosterone, and prolactin levels improved prediction of invasive breast cancer using the Gail model by 0.086 units in the training set. The inclusion of estrone sulfate, testosterone, prolactin, and SHBG improved the prediction of estrogen receptor–positive breast cancer by 0.125 units and 0.083 units in the two prediction models, respectively, in the test set.
“Our results strongly support that endogenous hormones can improve risk prediction for invasive breast cancer and may help identify women who would benefit from chemoprevention,” wrote the study authors. “The improvement in the AUC observed when adding circulating hormone levels was similar or better than prior studies that considered adding genetic risk factors or mammographic density, and since hormone levels are not strongly correlated with these other risk factors, future studies should consider simultaneous inclusion of all these factors.”
Dr. Tworoger declared no potential conflicts of interest.
The study was funded by the National Institutes of Health.
The content in this post has not been reviewed by the American Society of Clinical Oncology, Inc. (ASCO®) and does not necessarily reflect the ideas and opinions of ASCO®.
