Breast Tumor Prognostic Characteristics and Biennial vs Annual Mammography, Age, and Menopausal Status.
OBJECTIVE
Screening mammography intervals remain under debate in the United States.


OBJECTIVE
To compare the proportion of breast cancers with less vs more favorable prognostic characteristics in women screening annually vs biennially by age, menopausal status, and postmenopausal hormone therapy (HT) use.


METHODS
This was a study of a prospective cohort from 1996 to 2012 at Breast Cancer Surveillance Consortium facilities. A total of 15,440 women ages 40 to 85 years with breast cancer diagnosed within 1 year of an annual or within 2 years of a biennial screening mammogram.


METHODS
We updated previous analyses by using narrower intervals for defining annual (11-14 months) and biennial (23-26 months) screening.


METHODS
We defined less favorable prognostic characteristics as tumors that were stage IIB or higher, size greater than 15 mm, positive nodes, and any 1 or more of these characteristics. We used log-binomial regression to model the proportion of breast cancers with less favorable characteristics following a biennial vs annual screen by 10-year age groups and by menopausal status and current postmenopausal HT use.


RESULTS
Among 15,440 women with breast cancer, most were 50 years or older (13,182 [85.4%]), white (12,063 [78.1%]), and postmenopausal (9823 [63.6%]). Among 2027 premenopausal women (13.1%), biennial screeners had higher proportions of tumors that were stage IIB or higher (relative risk [RR], 1.28 [95% CI, 1.01-1.63]; P=.04), size greater than 15 mm (RR, 1.21 [95% CI, 1.07-1.37]; P=.002), and with any less favorable prognostic characteristic (RR, 1.11 [95% CI, 1.00-1.22]; P=.047) compared with annual screeners. Among women currently taking postmenopausal HT, biennial screeners tended to have tumors with less favorable prognostic characteristics compared with annual screeners; however, 95% CIs were wide, and differences were not statistically significant (for stage 2B+, RR, 1.14 [95% CI, 0.89-1.47], P=.29; size>15 mm, RR, 1.13 [95% CI, 0.98-1.31], P=.09; node positive, RR, 1.18 [95% CI, 0.98-1.42], P=.09; any less favorable characteristic, RR, 1.12 [95% CI, 1.00-1.25], P=.053). The proportions of tumors with less favorable prognostic characteristics were not significantly larger for biennial vs annual screeners among postmenopausal women not taking HT (eg, any characteristic: RR, 1.03 [95% CI, 0.95-1.12]; P=.45), postmenopausal HT users after subdividing by type of hormone use (eg, any characteristic: estrogen+progestogen users, RR, 1.16 [95% CI, 0.91-1.47]; P=.22; estrogen-only users, RR, 1.14 [95% CI, 0.94-1.37]; P=.18), or any 10-year age group (eg, any characteristic: ages 40-49 years, RR, .1.04 [95% CI, 0.94-1.14]; P=.48; ages 50-59 years, RR, 1.03 [95% CI, 0.94-1.12]; P=.58; ages 60-69 years, RR, 1.07 [95% CI, 0.97-1.19]; P=.18; ages 70-85 years, RR, 1.05 [95% CI, 0.94-1.18]; P=.35).


CONCLUSIONS
Premenopausal women diagnosed as having breast cancer following biennial vs annual screening mammography are more likely to have tumors with less favorable prognostic characteristics. Postmenopausal women not using HT who are diagnosed as having breast cancer following a biennial or annual screen have similar proportions of tumors with less favorable prognostic characteristics.
Division of Biostatistics, Department of Public Health Sciences, University of California Davis School of Medicine, Davis2Group Health Research Institute, Group Health Cooperative, Seattle, Washington.
Diana L
DL
Miglioretti
Group Health Research Institute, Group Health Cooperative, Seattle, Washington.
Weiwei
W
Zhu
Departments of Medicine and Epidemiology and Biostatistics, University of California-San Francisco, San Francisco,4General Internal Medicine Section, Department of Veterans Affairs, University of California-San Francisco, San Francisco.
Karla
K
Kerlikowske
Department of Surgery, Office of Health Promotion Research, University of Vermont College of Medicine, Burlington6University of Vermont Cancer Center, University of Vermont College of Medicine, Burlington.
Brian L
BL
Sprague
Department of Biomedical Data Science, Geisel School of Medicine at Dartmouth, Lebanon, New Hampshire8Department of Epidemiology, Geisel School of Medicine at Dartmouth, Lebanon, New Hampshire.
Tracy
T
Onega
Group Health Research Institute, Group Health Cooperative, Seattle, Washington.
Diana S M
DS
Buist
Department of Radiology, The University of North Carolina, Chapel Hill.
Louise M
LM
Henderson
Cancer Control Science Department, American Cancer Society, Atlanta, Georgia.
Robert A
RA
Smith
D000328:Adult; D000367:Age Factors; D000368:Aged; D000369:Aged, 80 and over; D001943:Breast Neoplasms / Q000000981:diagnostic imaging* / Q000453:epidemiology / Q000473:pathology; D018270:Carcinoma, Ductal, Breast / Q000000981:diagnostic imaging* / Q000453:epidemiology / Q000473:pathology; D002285:Carcinoma, Intraductal, Noninfiltrating / Q000000981:diagnostic imaging* / Q000453:epidemiology / Q000473:pathology; D055088:Early Detection of Cancer / Q000379:methods*; D005260:Female; D020249:Hormone Replacement Therapy / Q000009:adverse effects; D006801:Humans; D008207:Lymphatic Metastasis; D008327:Mammography / Q000379:methods*; D008875:Middle Aged; D009367:Neoplasm Staging; D016017:Odds Ratio; D017698:Postmenopause; D011237:Predictive Value of Tests; D017697:Premenopause; D011446:Prospective Studies; D012042:Registries; D018570:Risk Assessment; D012307:Risk Factors; D013997:Time Factors; D047368:Tumor Burden