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Journal of the National Cancer Institute Advance Access originally published online on November 13, 2007
JNCI Journal of the National Cancer Institute 2007 99(22):1657-1659; doi:10.1093/jnci/djm228
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Published by Oxford University Press 2007.

EDITORIALS

Absolute Risk Models for Subtypes of Breast Cancer

Mitchell H. Gail, William F. Anderson, Montserrat Garcia-Closas, Mark E. Sherman

Affiliations of authors: Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD

Correspondence to: Mitchell H. Gail, MD, PhD, Biostatistics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, 6120 Executive Plaza South, Room 8032, Bethesda, MD 20892-7244 (e-mail: gailm@mail.nih.gov).

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Statistical models developed to predict the absolute risks of breast cancer subtypes may help identify women who could benefit from specific preventive interventions and improve estimates of total breast cancer risk. Chlebowski et al. (1) present data from the observational study and clinical trial cohorts of the Women's Health Initiative (WHI) to evaluate and improve absolute risk prediction models for estrogen receptor (ER)–positive and –negative invasive breast cancer among women aged 50–79 years. They evaluate how well the Gail model [model 2 in Costantino et al. (2)] predicts the numbers of breast cancers in the combined observational study and clinical trial cohorts (i.e., calibration) and the Gail model's discriminatory accuracy, expressed as the area under the receiver operating curve (AUC), in the clinical trial . . . [Full Text of this Article]


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