Diana L Miglioretti1, Weiwei Zhu2, Karla Kerlikowske3, Brian L Sprague4, Tracy Onega5, Diana S M Buist2, Louise M Henderson6, Robert A Smith7. 1. Division of Biostatistics, Department of Public Health Sciences, University of California Davis School of Medicine, Davis2Group Health Research Institute, Group Health Cooperative, Seattle, Washington. 2. Group Health Research Institute, Group Health Cooperative, Seattle, Washington. 3. 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. 4. 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. 5. 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. 6. Department of Radiology, The University of North Carolina, Chapel Hill. 7. Cancer Control Science Department, American Cancer Society, Atlanta, Georgia.
Abstract
IMPORTANCE: 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. DESIGN, SETTING, AND PARTICIPANTS: 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. EXPOSURES: We updated previous analyses by using narrower intervals for defining annual (11-14 months) and biennial (23-26 months) screening. MAIN OUTCOMES AND MEASURES: 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 AND RELEVANCE: 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.
IMPORTANCE: 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. DESIGN, SETTING, AND PARTICIPANTS: 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. EXPOSURES: We updated previous analyses by using narrower intervals for defining annual (11-14 months) and biennial (23-26 months) screening. MAIN OUTCOMES AND MEASURES: 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 AND RELEVANCE: 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.
Authors: Laura E Ichikawa; William E Barlow; Melissa L Anderson; Stephen H Taplin; Berta M Geller; R James Brenner Journal: Radiology Date: 2010-05-26 Impact factor: 11.105
Authors: Karla Kerlikowske; Rebecca A Hubbard; Diana L Miglioretti; Berta M Geller; Bonnie C Yankaskas; Constance D Lehman; Stephen H Taplin; Edward A Sickles Journal: Ann Intern Med Date: 2011-10-18 Impact factor: 25.391
Authors: Rebecca A Hubbard; Karla Kerlikowske; Chris I Flowers; Bonnie C Yankaskas; Weiwei Zhu; Diana L Miglioretti Journal: Ann Intern Med Date: 2011-10-18 Impact factor: 25.391
Authors: Therese B Bevers; Benjamin O Anderson; Ermelinda Bonaccio; Saundra Buys; Sandra Buys; Mary B Daly; Peter J Dempsey; William B Farrar; Irving Fleming; Judy E Garber; Randall E Harris; Alexandra S Heerdt; Mark Helvie; John G Huff; Nazanin Khakpour; Seema A Khan; Helen Krontiras; Gary Lyman; Elizabeth Rafferty; Sara Shaw; Mary Lou Smith; Theodore N Tsangaris; Cheryl Williams; Thomas Yankeelov; Thomas Yaneeklov Journal: J Natl Compr Canc Netw Date: 2009-11 Impact factor: 11.908
Authors: Amanda I Phipps; Laura Ichikawa; Erin J A Bowles; Patricia A Carney; Karla Kerlikowske; Diana L Miglioretti; Diana S M Buist Journal: Maturitas Date: 2010-05-21 Impact factor: 4.342
Authors: Carol H Lee; D David Dershaw; Daniel Kopans; Phil Evans; Barbara Monsees; Debra Monticciolo; R James Brenner; Lawrence Bassett; Wendie Berg; Stephen Feig; Edward Hendrick; Ellen Mendelson; Carl D'Orsi; Edward Sickles; Linda Warren Burhenne Journal: J Am Coll Radiol Date: 2010-01 Impact factor: 5.532
Authors: Jeanne S Mandelblatt; Kathleen A Cronin; Stephanie Bailey; Donald A Berry; Harry J de Koning; Gerrit Draisma; Hui Huang; Sandra J Lee; Mark Munsell; Sylvia K Plevritis; Peter Ravdin; Clyde B Schechter; Bronislava Sigal; Michael A Stoto; Natasha K Stout; Nicolien T van Ravesteyn; John Venier; Marvin Zelen; Eric J Feuer Journal: Ann Intern Med Date: 2009-11-17 Impact factor: 25.391
Authors: Anna M Chiarelli; Kristina M Blackmore; Lucia Mirea; Susan J Done; Vicky Majpruz; Ashini Weerasinghe; Linda Rabeneck; Derek Muradali Journal: J Natl Cancer Inst Date: 2020-04-01 Impact factor: 13.506
Authors: Amy Trentham-Dietz; Mehmet Ali Ergun; Oguzhan Alagoz; Natasha K Stout; Ronald E Gangnon; John M Hampton; Kim Dittus; Ted A James; Pamela M Vacek; Sally D Herschorn; Elizabeth S Burnside; Anna N A Tosteson; Donald L Weaver; Brian L Sprague Journal: Breast Cancer Res Treat Date: 2017-11-28 Impact factor: 4.872
Authors: Matthew W Conklin; Ronald E Gangnon; Brian L Sprague; Lisa Van Gemert; John M Hampton; Kevin W Eliceiri; Jeremy S Bredfeldt; Yuming Liu; Nuntida Surachaicharn; Polly A Newcomb; Andreas Friedl; Patricia J Keely; Amy Trentham-Dietz Journal: Cancer Epidemiol Biomarkers Prev Date: 2017-11-15 Impact factor: 4.254
Authors: Karla Kerlikowske; Shuai Chen; Marzieh K Golmakani; Brian L Sprague; Jeffrey A Tice; Anna N A Tosteson; Garth H Rauscher; Louise M Henderson; Diana S M Buist; Janie M Lee; Charlotte C Gard; Diana L Miglioretti Journal: J Natl Cancer Inst Date: 2022-05-09 Impact factor: 11.816
Authors: Karla Kerlikowske; Michael C S Bissell; Brian L Sprague; Diana S M Buist; Louise M Henderson; Janie M Lee; Diana L Miglioretti Journal: J Natl Cancer Inst Date: 2021-07-01 Impact factor: 13.506
Authors: Michela Franchini; Stefania Pieroni; Edgardo Montrucchio; Jacopo Nori Cucchiari; Cosimo Di Maggio; Enrico Cassano; Brunella Di Nubila; Gian Marco Giuseppetti; Alberto Nicolucci; Gianfranco Scaperrotta; Paolo Belli; Sonia Santicchia; Sabrina Molinaro Journal: Int J Environ Res Public Health Date: 2021-03-02 Impact factor: 3.390
Authors: Donald L Weaver; Matthew W Conklin; Brian L Sprague; Pamela M Vacek; Sophie E Mulrow; Mark F Evans; Amy Trentham-Dietz; Sally D Herschorn; Ted A James; Nuntida Surachaicharn; Adib Keikhosravi; Kevin W Eliceiri Journal: Cancer Epidemiol Biomarkers Prev Date: 2020-10-20 Impact factor: 4.090