Validation of a breast cancer risk assessment model in women with a positive family history.
BACKGROUND
Gail et al. developed a statistical model for estimating the risk of developing breast cancer in white women screened annually with mammography. This model is used for counseling and for admission to clinical trials.


OBJECTIVE
We evaluated the model prospectively in a cohort of women with a family history of breast cancer.


METHODS
We followed women who participated in the American Cancer Society 1987 Texas Breast Screening Project. The model was evaluated by comparing the observed (O) and expected (E) numbers of breast cancers using composite background rates from both the Breast Cancer Detection and Demonstration Project and the Surveillance, Epidemiology, and End Results program of the National Cancer Institute. Data were partitioned by adherence to American Cancer Society screening guidelines.


RESULTS
The Gail et al. model predicted the risk well among women who adhered to the American Cancer Society guidelines (O/E = 1.12; 95% confidence interval = 0.75-1.61) but overpredicted risk for women who did not adhere to the guidelines. There was an indication that the model overpredicted risk for women younger than 60 years old and underpredicted risk in women aged 60 years and older.


CONCLUSIONS
Overall, the Gail et al. model accurately predicts risk in women with a family history of breast cancer and who adhere to American Cancer Society screening guidelines. Thus, the model should be used as it was intended, for women who receive annual mammograms.
Bondy
M L
ML
Department of Epidemology, University of Texas M. D. Anderson Cancer Center, Houston 77030.
Lustbader
E D
ED
Halabi
S
S
Ross
E
E
Vogel
V G
VG
D000328:Adult; D000368:Aged; D000570:American Cancer Society; D001943:Breast Neoplasms / Q000453:epidemiology* / Q000235:genetics* / Q000517:prevention & control; D016022:Case-Control Studies; D005260:Female; D006801:Humans; D008327:Mammography; D008403:Mass Screening; D008875:Middle Aged; D015233:Models, Statistical; D009316:National Institutes of Health (U.S.); D010349:Patient Compliance; D011237:Predictive Value of Tests; D011446:Prospective Studies; D012307:Risk Factors; D013781:Texas / Q000453:epidemiology; D014481:United States