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Figure.
Overview of Study Design
Overview of Study Design

This study captured 2 mechanisms by which a longer vs shorter screening interval might lead to breast cancers (BrCa) with less favorable characteristics: (1) more time for tumor growth between the index screening mammogram m′ and the previous screen m; and (2) more time for a tumor to become symptomatic and clinically detected after a negative screening mammogram m′. Follow-up indicates the follow-up period for cancer ascertainment.

Table 1.  
Population Characteristics by Screening Interval for Women With Breast Cancer Who Underwent Screening Mammography, 1996 to 2011
Population Characteristics by Screening Interval for Women With Breast Cancer Who Underwent Screening Mammography, 1996 to 2011
Table 2.  
Distribution of Tumor Characteristics by Age and Screening Interval
Distribution of Tumor Characteristics by Age and Screening Interval
Table 3.  
Distribution of Tumor Characteristics by Annual (A) or Biennial (B) Screening Interval,a Menopausal Status, and Postmenopausal HT Use
Distribution of Tumor Characteristics by Annual (A) or Biennial (B) Screening Interval,a Menopausal Status, and Postmenopausal HT Use
Table 4.  
Less Favorable Invasive Cancer Characteristics for Biennial vs Annual Screenersa
Less Favorable Invasive Cancer Characteristics for Biennial vs Annual Screenersa
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Buist  DS, Porter  PL, Lehman  C, Taplin  SH, White  E.  Factors contributing to mammography failure in women aged 40-49 years.  J Natl Cancer Inst. 2004;96(19):1432-1440.PubMedGoogle ScholarCrossref
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Anderson  TJ, Waller  M, Ellis  IO, Bobrow  L, Moss  S.  Influence of annual mammography from age 40 on breast cancer pathology.  Hum Pathol. 2004;35(10):1252-1259.PubMedGoogle ScholarCrossref
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White  E, Miglioretti  DL, Yankaskas  BC,  et al.  Biennial versus annual mammography and the risk of late-stage breast cancer.  J Natl Cancer Inst. 2004;96(24):1832-1839.PubMedGoogle ScholarCrossref
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Hubbard  RA, Kerlikowske  K, Flowers  CI, Yankaskas  BC, Zhu  W, Miglioretti  DL.  Cumulative probability of false-positive recall or biopsy recommendation after 10 years of screening mammography: a cohort study.  Ann Intern Med. 2011;155(8):481-492.PubMedGoogle ScholarCrossref
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Kerlikowske  K, Zhu  W, Hubbard  RA,  et al; Breast Cancer Surveillance Consortium.  Outcomes of screening mammography by frequency, breast density, and postmenopausal hormone therapy.  JAMA Intern Med. 2013;173(9):807-816.PubMedGoogle ScholarCrossref
23.
Dittus  K, Geller  B, Weaver  DL,  et al; Breast Cancer Surveillance Consortium.  Impact of mammography screening interval on breast cancer diagnosis by menopausal status and BMI.  J Gen Intern Med. 2013;28(11):1454-1462.PubMedGoogle ScholarCrossref
24.
Braithwaite  D, Zhu  W, Hubbard  RA,  et al; Breast Cancer Surveillance Consortium.  Screening outcomes in older US women undergoing multiple mammograms in community practice: does interval, age, or comorbidity score affect tumor characteristics or false positive rates?  J Natl Cancer Inst. 2013;105(5):334-341.PubMedGoogle ScholarCrossref
25.
O’Meara  ES, Zhu  W, Hubbard  RA,  et al.  Mammographic screening interval in relation to tumor characteristics and false-positive risk by race/ethnicity and age.  Cancer. 2013;119(22):3959-3967.PubMedGoogle ScholarCrossref
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Coldman  A, Phillips  N, Warren  L, Kan  L.  Breast cancer mortality after screening mammography in British Columbia women.  Int J Cancer. 2007;120(5):1076-1080.PubMedGoogle ScholarCrossref
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Randall  D, Morrell  S, Taylor  R, Hung  WT.  Annual or biennial mammography screening for women at a higher risk with a family history of breast cancer: prognostic indicators of screen-detected cancers in New South Wales, Australia.  Cancer Causes Control. 2009;20(5):559-566.PubMedGoogle ScholarCrossref
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Goel  A, Littenberg  B, Burack  RC.  The association between the pre-diagnosis mammography screening interval and advanced breast cancer.  Breast Cancer Res Treat. 2007;102(3):339-345.PubMedGoogle ScholarCrossref
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41.
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Original Investigation
November 2015

Breast Tumor Prognostic Characteristics and Biennial vs Annual Mammography, Age, and Menopausal Status

Author Affiliations
  • 1Division of Biostatistics, Department of Public Health Sciences, University of California Davis School of Medicine, Davis
  • 2Group Health Research Institute, Group Health Cooperative, Seattle, Washington
  • 3Departments 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
  • 5Department of Surgery, Office of Health Promotion Research, University of Vermont College of Medicine, Burlington
  • 6University of Vermont Cancer Center, University of Vermont College of Medicine, Burlington
  • 7Department of Biomedical Data Science, Geisel School of Medicine at Dartmouth, Lebanon, New Hampshire
  • 8Department of Epidemiology, Geisel School of Medicine at Dartmouth, Lebanon, New Hampshire
  • 9Department of Radiology, The University of North Carolina, Chapel Hill
  • 10Cancer Control Science Department, American Cancer Society, Atlanta, Georgia
 

Copyright 2015 American Medical Association. All Rights Reserved. Applicable FARS/DFARS Restrictions Apply to Government Use.

JAMA Oncol. 2015;1(8):1069-1077. doi:10.1001/jamaoncol.2015.3084
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.

Introduction

The frequency at which women should receive screening mammography remains controversial in the United States. In 2009, the US Preventive Services Task Force (USPSTF) updated their breast cancer screening guidelines to recommend routine biennial mammography for women ages 50 to 74 years, based on modeling evidence suggesting that the harms of more frequent screening outweigh the small estimated added benefit of annual screening.1,2 In contrast, some organizations, such as the American Cancer Society3 and other groups,4-6 have for decades recommended annual screening starting at age 40 years. However, during this time, mammography accuracy has improved,7,8 new breast cancer treatments have been developed, and interest in tailoring screening recommendations to individual risk to maximize the balance of benefits vs harms has increased.9-13

No head-to-head randomized controlled trials (RCTs) have compared annual with biennial screening. Thus, recommended screening intervals have mainly been influenced by interval cancer rates14 and inferential evidence on tumor growth rates observed in trials.15 Based on tumor biology, some have argued that screening intervals should be shorter for younger women, whereas less frequent screening may be sufficient for women 50 years or older.16-19 New RCTs comparing screening mammography intervals with mortality end points are impractical; thus, today screening interval guidelines must rely on observational data20-28 and modeling.2,13,29-31

The Breast Cancer Surveillance Consortium (BCSC) has published several large empirical studies comparing the benefits and harms of different screening intervals.20-25 These observational data suggest no difference in the proportion of advanced-stage invasive cancers with annual compared with biennial screening overall or for women 50 years or older. These analyses classified all women with 2 screening mammograms 9 to 30 months apart as annual screeners (median, 13 months [range, 9-18 months]) vs biennial screeners (median 24 months [range, 19-30 months]). Given the broad ranges used, these prior studies may not address subgroups of women who closely adhere to screening guidelines or evaluate whether screening at intervals more closely approximating 12 vs 24 months influences tumor characteristics in subgroups of women undergoing screening. To more specifically determine if annual vs biennial screening is associated with more favorable prognostic characteristics in younger or older women, we updated our prior analyses using more recent data and narrower definitions for annual (11-14 months) and biennial (23-26 months) screening. We evaluated whether proportions of tumors with less favorable vs more favorable prognostic characteristics differed by annual vs biennial screening in subgroups of women identified by age, menopausal status, and postmenopausal hormone therapy (HT) use.

Box Section Ref ID

At a Glance

  • Premenopausal women diagnosed as having breast cancer following biennial vs annual screening mammography were more likely to have tumors with less favorable prognostic characteristics (relative risks, 1.11-1.28; P < .05).

  • Postmenopausal women not using hormone therapy who are diagnosed as having breast cancer following a biennial or annual screen had similar proportions of tumors with less favorable prognostic characteristics.

  • Menopausal status may be more important than age when considering breast cancer screening intervals.

Methods
Study Setting and Data Sources

We used data from the BCSC (http://breastscreening.cancer.gov).32 The BCSC registries collect patient and clinical information from community radiology facilities with populations similar to that of the US population.33 Breast cancer diagnoses and tumor characteristics are obtained by linking with pathology databases; regional Surveillance, Epidemiology, and End Results (SEER) programs; and state tumor registries, with estimated completeness of reporting greater than 94.3%.34 The BCSC registries and the Statistical Coordinating Center received institutional review board approval for active or passive consenting processes or a waiver of consent to enroll participants, link and pool data, and perform analysis. All procedures were Health Insurance Portability and Accountability Act compliant, and registries and the Coordinating Center received a Federal Certificate of Confidentiality and other protections for the identities of women, physicians, and facilities.

Participants and Study Design

Women ages 40 to 85 years were included if diagnosed from 1996 to 2012 with an incident invasive breast cancer or ductal carcinoma in situ (DCIS), either as a screen-detected or interval cancer, and who had had at least 2 screening mammography examinations 11 to 14 or 23 to 26 months apart before diagnosis. The time between the 2 screening examinations was used to classify women as annual (11-14 months) or biennial (23-26 months) screeners.

We aimed to capture 2 mechanisms by which breast cancers with less favorable characteristics might result from a longer vs a shorter screening interval: (1) more tumor growth between 2 screening mammograms, leading to more advanced disease at screen detection, and (2) more time for a tumor to become symptomatic and clinically detected, and therefore more likely to be advanced, after a negative screening mammogram (Figure). Thus, we included both screen-detected and interval breast cancers diagnosed within 1 year of an annual screening mammogram or 2 years of a biennial screening mammogram, as would be done in the analysis of an RCT. Breast cancers following a positive screening mammogram were considered screen detected, and those following a negative screening mammogram were considered interval cancers using standard BCSC definitions for classifying mammography results.35 Only mammograms that occurred at least 1 year before the end of complete capture of cancers by the BCSC for annual mammograms and at least 2 years for biennial mammograms were included.

Measures and Definitions

Screening mammograms were defined using the indication reported by the radiologist or technologist. To minimize misclassification of diagnostic mammography as screening, we excluded examinations that were unilateral or were preceded by mammography or breast ultrasonography within 9 months.

Women completed a questionnaire at each mammography examination to collect information on race and ethnicity, history of first-degree relatives (mother, sister, or daughter) with breast cancer, menopausal status, current postmenopausal HT use, and history of hysterectomy. If self-reported race/ethnicity was missing, we used information from cancer registries. Women were considered postmenopausal if they reported removal of both ovaries, periods that stopped naturally or no period for more than 365 days, current HT use, or age 55 years or older.36 Women were considered premenopausal if they reported currently having periods or using oral contraceptives.36 Women were considered to have missing menopausal status if they were younger than 55 years and reported having had a hysterectomy without bilateral oophorectomy and were not using HT, or if menopausal status could not be determined based on available information. Postmenopausal women were classified by HT use. Women using HT with nonmissing hysterectomy information (53%) were included in subanalysis by HT type. Women with a uterus using HT were classified as using estrogen plus progestogen; women without a uterus using HT were classified as using estrogen only, based on clinical practice, as previously described.22,37

Four outcomes measured less favorable prognostic characteristics: American Joint Committee on Cancer (AJCC)38 stage IIB or higher; tumor size greater than 15 mm; positive nodes; and a measure of any 1 or more of these characteristics. For 262 women missing AJCC stage (3% of invasive cancers), stage IIB or higher was imputed based on tumor size or extension, nodal status, metastasis, or SEER summary stage, as previously described.22 In sensitivity analyses to evaluate our choices for stage and size thresholds, we classified tumors as stage IIA or higher and size greater than 20 mm.

Statistical Analysis

We described the participant population by screening interval. We estimated the proportion of women with invasive cancer vs DCIS. Among women with invasive cancer, we estimated the distribution of tumor characteristics (stage, size, lymph node status) at diagnosis by screening interval, and separately by age group and by menopausal status and HT use. Among women with invasive breast cancer, we used log-binomial regression39 to estimate relative risks (RRs) and 95% CIs of less favorable vs more favorable invasive tumor characteristics associated with screening interval by age group and by menopausal status and postmenopausal HT use, adjusting for race/ethnicity, first-degree family history of breast cancer, and BCSC registry. In one case for which the log-binomial model could not be estimated, we used Poisson regression with robust error variances. This approach gave results very similar to those of log-binomial regression in cases that could be estimated using both methods. Based on the observed numbers of women with invasive breast cancer, we had 80% power with a 2-sided α of .05 to detect RRs within age and menopausal status groups of approximately 1.25 to 1.35 for stage IIB or higher, 1.20 to 1.30 for positive nodes, and 1.10 to 1.20 for tumors greater than 15 mm and the measure of any 1 or more characteristics. For analyses subdivided by HT type, we had 80% power to detect an RR of 1.25-1.55. We performed analyses with SAS statistical software (version 9.2; SAS Institute Inc).

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%]) (Table 1). Biennial screeners were more likely to be in the youngest (40-49 years) or oldest (70-85 years) age groups and less likely than annual screeners to have a family history of breast cancer. Among annual screeners, 77.8% of cancers were screen detected compared with 72.8% for biennial screeners.

The proportion of DCIS vs invasive cancers and the proportion of invasive tumors associated with less favorable vs more favorable prognostic characteristics decreased with age (Table 2). For example, 21.3% to 24.2% of women ages 40 to 49 years diagnosed as having an invasive cancer after an annual or biennial screen had tumors that were stage IIB or higher, compared with 16.4% or less among women 60 years or older. Within age groups, the proportions of invasive tumors vs DCIS were similar among annual vs biennial screeners. Only small and inconsistent differences were seen in the proportions of invasive tumors with more favorable vs less favorable characteristics for annual vs biennial screeners.

Premenopausal women (2027 [13.1%]) had higher proportions of DCIS vs invasive cancers and invasive tumors with less favorable prognostic characteristics than postmenopausal women (Table 3). For example, 19.8% to 25.7% of premenopausal women diagnosed as having an invasive cancer after an annual or biennial screen had tumors that were stage IIB or higher compared with 13.2% to 15.8% of postmenopausal women not using HT and 16.1% to 18.4% of HT users. Within most groups, the proportions of invasive tumors vs DCIS were similar among annual vs biennial screeners; however, postmenopausal women not using HT had a higher proportion of invasive cancers if they were screened biennially compared with annually. Among premenopausal women, women screened biennially vs annually had a higher proportion of stage IIB or higher tumors (25.7% vs 19.8%), tumors greater than 15 mm (65.3% vs 54.6%), and node-positive disease (36.6% vs 31.3%). Differences in these tumor characteristics among postmenopausal women were small and inconsistent, regardless of HT use.

We calculated the RRs of less favorable tumor characteristics for women with invasive breast cancer following a biennial vs annual screen, adjusting for race/ethnicity, family history of breast cancer, and BCSC registry (Table 4). Within age groups, RR estimates were close to 1 with no significant differences between biennial vs annual screeners. However, among premenopausal women, compared with annual screeners, biennial screeners were at increased risk of stage IIB or higher tumors (RR, 1.28 [95% CI, 1.01-1.63]; P = .04), tumors greater than 15 mm (RR, 1.21 [95% CI, 1.07-1.37]; P = .002), and tumors with any less favorable prognostic characteristic (RR, 1.11 [95% CI, 1.00-1.22]; P = .047). Among postmenopausal women not using HT at the time of the mammogram, RR estimates were close to 1 with no significant differences between biennial vs annual screeners except for a modest increased risk of tumors greater than 15 mm (RR, 1.11 [95% CI, 1.00-1.22]; P = .045). Among postmenopausal women using HT at the time of the mammogram, RR estimates for biennial vs annual screeners were consistently higher than 1, with nonsignificant increases in risk of tumors greater than 15 mm (RR, 1.13 [95% CI, 0.98-1.31]; P = .09), positive lymph nodes (RR, 1.18 [95% CI, 0.98-1.42]; P = .09), and tumors with less favorable prognosis (RR, 1.12 [95% CI, 1.00-1.25]; P = .05). Subdividing HT users with known hysterectomy status by the likely type of HT used did not change most results, which remained statistically nonsignificant except for increased risk of tumors greater than 15 mm among biennial vs annual screeners using estrogen plus progestogen (RR, 1.38 [95% CI, 1.04-1.82]; P = .02). Sensitivity analyses that classified tumors as IIA or higher or size greater than 20 mm did not substantially change results (data not shown).

Discussion

Premenopausal women diagnosed as having invasive breast cancer following a biennial screening mammogram were more likely to have tumors with less favorable prognostic characteristics than women diagnosed following an annual screening mammogram. In contrast, postmenopausal women diagnosed as having invasive breast cancer after biennial vs annual screening showed no statistically significant differences in the likelihood of less favorable prognostic characteristics, with the exception of small but non–statistically significant differences among women currently taking postmenopausal HT. We found no statistically significant differences in breast tumor prognostic characteristics for biennial vs annual screeners within 10-year age groups.

Our findings suggest that menopausal status may be more important than age when considering breast cancer screening intervals, which is biologically plausible. Tumors exposed to estrogen may grow faster, decreasing the detectable preclinical phase and resulting in a higher proportion of interval cancers with poorer tumor characteristics.14,15,18 In addition, breast density decreases after menopause, making it easier to diagnose breast cancers when they are smaller.8,40,41 In our sample of premenopausal women with breast cancer, 70% were ages 40 to 49 years, and 30% were ages 50 to 54 years. In a study of all women in the BCSC, only 10% of women ages 40 to 49 years were postmenopausal, and 25% of women ages 50 to 54 years were premenopausal.36 Thus, if screening guidelines were based on menopausal status rather than age, some women ages 40 to 54 years might be recommended for more frequent screening and others, less frequent screening.

Our study refines prior BCSC studies20-25 that used wider screening intervals to classify women as annual or biennial screeners. Similar to our study, these prior studies found no difference in the proportion of invasive cancers with less favorable prognostic characteristics with biennial vs annual screening for women 50 years or older.20-22 In contrast to our study, White et al20 found that women ages 40 to 49 years were less likely to have late- vs early-stage invasive cancer if screened annually compared with biennially; however, an updated analysis with more recent data that included digital mammography found no difference by screening interval in the proportions of late-stage disease for women ages 40 to 49 years, consistent with our findings.21 Kerlikowske et al22 found a significantly higher proportion of less favorable tumors with biennial vs annual screening in women ages 40 to 49 years but only among women with extremely dense breasts; however, 95% CIs were wide within density groups. Buist et al18 showed the higher interval cancer rates in women ages 40 to 49 years compared with those of older women observed in RCTs were still evident in modern (film-screen–based) service screening, which they attributed to younger women having faster-growing tumors and greater mammographic breast density.

In other prior BCSC analyses, O’Meara and colleagues25 compared intervals within racial and ethnic groups. Biennial vs annual screening was not associated with overall increased risk of less favorable tumor characteristics among women who were white, black, or Hispanic and ages 40 to 49 years, or among Asian women ages 50 to 74 years; however, Hispanic women ages 50 to 74 years who were screened biennially vs annually had an increased risk of late-stage disease and larger tumors, and Asian women ages 40 to 49 years who were screened biennially were at high risk of a node-positive diagnosis. Dittus et al23 observed that premenopausal obese women undergoing biennial screening had a non–statistically significantly increased risk of diagnosis with a tumor greater than 20 mm relative to annual screeners. In contrast, across all body mass index categories, postmenopausal women undergoing biennial screening vs annual screening did not present with more advanced stage or larger tumor sizes. Braithwaite et al24 examined tumor characteristics among women ages 66 to 89 years and found no statistically significant difference in adverse tumor characteristics by screening interval within age-by-comorbidity subgroups. Kerlikowske et al22 found that women ages 50 to 74 years undergoing biennial screening mammography had a risk of advanced-stage disease similar to that of women undergoing annual mammography within subgroups defined by HT use and breast density.

These findings add to the body of evidence that is providing greater confidence in the potential for advising women and their clinicians about screening frequency based on personal risk factors. When considering recommendations regarding screening intervals, the potential benefit of diagnosing cancers at an earlier stage must be weighed against the increased potential for harms associated with more frequent screening, such as false-positive recalls and biopsies, which are 1.5 to 2 times higher in annual vs biennial screeners.2,21-25,29,30 Future studies should focus on strategies to reduce these harms. We also need studies that will improve our understanding of tumor growth rates and aggressiveness among premenopausal and postmenopausal women, the duration of the transition from shorter to longer sojourn times, and the degree to which risk factors may change the association among menopausal status, screening interval, and tumor characteristics observed herein.

Our study has several limitations. First, the potential for confounding is always a concern in observational studies. For example, women who know they have breast cancer risk factors might undergo more frequent screening than women without these factors. We adjusted for family history, race, and ethnicity in our analyses to minimize bias but did not adjust for other risk factors, such as benign breast disease or reproductive factors. Second, some of our comparisons might be significant by chance alone, so the magnitude and consistency of differences and 95% CIs should be considered. Another limitation is that we maximized sample sizes within subgroups by including data back to 1996, which included film-screen mammograms. Overall, the sensitivities of digital and film-screen mammography are similar, but sensitivity may be higher for digital mammography in some subgroups, especially women with dense breasts and premenopausal women.8,42,43 We did not collect HT type, relying instead on a surrogate based on hysterectomy status, which was available for only 53% of HT users. Results within HT-type subgroups were inconsistent and had wide 95% CIs, limiting our ability to make inferences in this group. Finally, we did not measure breast cancer mortality. Thus, we do not know if the observed increases in the proportions of less favorable tumors with biennial vs annual screening would result in differences in breast cancer mortality.

Conclusions

Premenopausal women diagnosed as having breast cancer following a biennial mammogram are more likely to have tumors with less favorable prognostic characteristics than women with breast cancers diagnosed after annual screening. 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. Results are less clear for women using postmenopausal HT. Our findings of a lower proportion of less favorable tumors with more frequent screening in premenopausal women, and no statistically significant difference in the proportion of less favorable tumors in postmenopausal women by screening interval, add to evidence about the potential benefits and harms of screening that policymakers can use to set guidelines about screening intervals and women can use when making personal screening decisions with their clinicians.

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Article Information

Corresponding Author: Diana L. Miglioretti, PhD, Department of Public Health Sciences, University of California–Davis School of Medicine, One Shields Ave, Med-Sci 1C, Room 145, Davis, CA 95616 (dmiglioretti@ucdavis.edu).

Accepted for Publication: July 6, 2015.

Published Online: October 20, 2015. doi:10.1001/jamaoncol.2015.3084.

Author Contributions: Ms Zhu had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Study concept and design: Miglioretti, Kerlikowske, Sprague, Buist, Smith.

Acquisition, analysis, or interpretation of data: All authors.

Drafting of the manuscript: Miglioretti, Kerlikowske, Smith.

Critical revision of the manuscript for important intellectual content: Zhu, Kerlikowske, Sprague, Onega, Buist, Henderson, Smith.

Statistical analysis: Miglioretti, Zhu.

Obtained funding: Miglioretti, Kerlikowske, Sprague, Onega, Buist, Henderson, Smith.

Study supervision: Miglioretti.

Conflict of Interest Disclosures: Dr Smith served as an unpaid advisor on General Electric Health Care’s Breast Medical Advisory Board. No other disclosures are reported.

Funding/Support: This research was supported the American Cancer Society. Collection of mammography performance data was supported by the National Cancer Institute’s Breast Cancer Surveillance Consortium (P01CA154292 and HHSN261201100031C) and U54CA163303. The collection of cancer data used in this study was supported in part by several state public health departments and cancer registries throughout the United States (for a full description of these sources, please see http://breastscreening.cancer.gov/work/acknowledgement.html).

Role of the Funder/Sponsor: The American Cancer Society Inc requested the study to inform their screening guidelines but had no role in the conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication. The National Cancer Institute had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, and approval of the manuscript; or decision to submit the manuscript for publication.

Group Information: Breast Cancer Surveillance Consortium members are as follows: Linn Abraham, MS, Group Health Cooperative; Andrew Avins, MD, Kaiser Permanente Division of Research; Rob Arao, MS, Group Health Cooperative; Steve Balch, MS, MBA, Group Health Cooperative; Thad Benefield, MS, University of North Carolina, Chapel Hill; Erin Aiello Bowles, MPH, Group Health Cooperative; Mark Bowman, University of Vermont; Susan Brandzel, MPH, Group Health Cooperative; Diana Buist, PhD, MPH, Group Health Cooperative; David Burian, BA, University of California, San Francisco; Elyse Chiapello, BASc, University of California, San Francisco; Rachael Chicoine, BS, University of Vermont; Firas Dabbous, MS, University of Illinois at Chicago; Tammy Dodd, Group Health Cooperative; Therese Dolecek, PhD, MS, University of Illinois at Chicago; Scottie Eliassen, MS, Dartmouth College; Kevin Filocamo, Group Health Cooperative; Pete Frawley, Group Health Cooperative; Hongyuan Gao, MS, Group Health Cooperative; Charlotte Gard, PhD, MS, Consultant New Mexico State University; Berta Geller, PhD, University of Vermont; Martha Goodrich, MS, Dartmouth College; Mikael Anne Greenwood-Hickman, MPH, University of North Carolina, Chapel Hill; Cindy Groseclose, University of Vermont; Henderson, Louise, PhD, MSPH, University of North Carolina, Chapel Hill; Deirdre Hill, PhD, University of New Mexico; Michael Hofmann, MS, University of California, San Francisco; Rebecca Hubbard, PhD, University of Pennsylvania; Erika Holden, Group Health Cooperative; Tiffany Hoots, University of North Carolina, Chapel Hill; Kathleen Howe, AA, University of Vermont; Laura Ichikawa, MS, Group Health Cooperative; Doug Kane, MS, Group Health Cooperative; Karla Kerlikowske, MD, University of California, San Francisco; Jenna Khan, MPH, University of Illinois at Chicago; Gabe Knop, University of North Carolina, Chapel Hill; Casey Luce, MSPH, Group Health Cooperative; Lin Ma, MS University of California, San Francisco; Terry Macarol, Advocate Health Care; John Mace, PhD, University of Vermont; Jennifer Maeser, MS, University of Washington; Kathy Malvin, BA, University of California, San Francisco; Katie Marsh, MPH, University of North Carolina, Chapel Hill; Diana Miglioretti, PhD, University of California, Davis; Anne Marie Murphy, PhD, Metropolitan Chicago Breast Cancer Task Force; Ellen O’Meara, PhD, Group Health Cooperative; Tracy Onega, PhD, MA, MS, Dartmouth College; Tiffany Pelkey, BA, University of Vermont; Dusty Quick, University of Vermont; Garth Rauscher, PhD, University of Illinois at Chicago; KatieRose Richmire, Group Health Cooperative; Scott Savioli, MA, Dartmouth College; Deborah Seger, Group Health Cooperative; Jennette Sison, MPH, University of California, San Francisco; Brian Sprague, PhD, University of Vermont; Wm. Thomas Summerfelt, PhD, Advocate Health Care; Katherine Tossas-Milligan, MS, University of Illinois at Chicago; Anna Tosteson, ScD, Dartmouth College; Rod Walker, MS, Group Health Cooperative; Julie Weiss, MS, Dartmouth College; Rob Wellman, MS, Group Health Cooperative; Karen Wernli, PhD, Group Health Cooperative; Heidi Whiting, MS Group Health Cooperative; Bonnie Yankaskas, PhD, University of North Carolina, Chapel Hill; Weiwei Zhu, MS, Group Health Cooperative.

Additional Information: The procedures for requesting BCSC data for research purposes are provided at http://breastscreening.cancer.gov/.

Additional Contributions: We thank the participating women, mammography facilities, and radiologists for the data they have provided for this study. Chris Tachibana, PhD, from Group Health Research Institute provided scientific editing as part of her position there. She did not receive additional compensation besides her salary.

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