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. 2022 Jun 8;19(8):919–934. doi: 10.1016/j.jacr.2022.04.008

Impact of the COVID-19 Pandemic on Breast Imaging: An Analysis of the National Mammography Database

Lars J Grimm a,b,, Cindy Lee c, Robert D Rosenberg d,e, Judy Burleson f, Michael Simanowith g, Tom Fruscello Jr h, Casey E Pelzl i, Sarah M Friedewald j, Linda Moy c, Margarita L Zuley k,l
PMCID: PMC9174535  PMID: 35690079

Abstract

Purpose

The aim of this study was to quantify the initial decline and subsequent rebound in breast cancer screening metrics throughout the coronavirus disease 2019 (COVID-19) pandemic.

Methods

Screening and diagnostic mammographic examinations, biopsies performed, and cancer diagnoses were extracted from the ACR National Mammography Database from March 1, 2019, through May 31, 2021. Patient (race and age) and facility (regional location, community type, and facility type) demographics were collected. Three time periods were used for analysis: pre-COVID-19 (March 1, 2019, to May 31, 2019), peak COVID-19 (March 1, 2020, to May 31, 2020), and COVID-19 recovery (March 1, 2021, to May 31, 2021). Analysis was performed at the facility level and overall between time periods.

Results

In total, 5,633,783 screening mammographic studies, 1,282,374 diagnostic mammographic studies, 231,390 biopsies, and 69,657 cancer diagnoses were analyzed. All peak COVID-19 metrics were less than pre-COVID-19 volumes: 36.3% of pre-COVID-19 for screening mammography, 57.9% for diagnostic mammography, 47.3% for biopsies, and 48.7% for cancer diagnoses. There was some rebound during COVID-19 recovery as a percentage of pre-COVID-19 volumes: 85.3% of pre-COVID-19 for screening mammography, 97.8% for diagnostic mammography, 91.5% for biopsies, and 92.0% for cancer diagnoses. Across various metrics, there was a disproportionate negative impact on older women, Asian women, facilities in the Northeast, and facilities affiliated with academic medical centers.

Conclusions

COVID-19 had the greatest impact on screening mammography volumes, which have not returned to pre-COVID-19 levels. Cancer diagnoses declined significantly in the acute phase and have not fully rebounded, emphasizing the need to increase outreach efforts directed at specific patient population and facility types.

Key Words: COVID-19, screening mammography, diagnostic mammography, breast biopsies, breast cancer


Credits awarded for this enduring activity are designated “SA-CME” by the American Board of Radiology (ABR) and qualify toward fulfilling requirements for Maintenance of Certification (MOC) Part II: Lifelong Learning and Self-assessment. To access the SA-CME activity visit https://cortex.acr.org/Presenters/CaseScript/CaseView?Info=fTHuFtw7Oc%2fz5rY2qFnR7ROBl3P%2bhKo5leeSIT4Hk6E%253d. SA-CME credit for this article expires July 31, 2025. All SA-CME articles can be found on JACR.org by navigating to SA-CME on the dropdown menu.

Introduction

The coronavirus disease 2019 (COVID-19) pandemic had a profound impact on health care delivery in the United States due to mandatary stay-at-home orders and patient fears about visiting health care facilities [1]. During the peak of the pandemic in early 2020, CMS recommended that individuals “consider postponing service” for “preventive care visit/screening” [2]. This led to the near complete cessation of many cancer screening services, including screening mammography [3, 4, 5, 6, 7, 8, 9]. As the public and health care organizations began to adapt, guidelines on a safe return to imaging were released by the Society of Breast Imaging in May 2020, followed by the ACR in July 2020 [10,11]. These guidelines advocated for strategies to shift the risk/benefit ratio for patients to facilitate a safe return to screening practices. In response, practices adopted a wide variety of strategies to encourage patients to return, including expanding hours, switching to electronic intake forms, improved cleaning and sanitation practices, and rearranging the workflows of clinics [12]. Several publications using regional and limited national data sets reported that in the months after the pandemic peak, screening mammography volumes began to rebound, but rates had not yet returned to prepandemic baseline [2,5,6]. However, the intermediate-term impact of COVID-19 on the use of screening and diagnostic mammography, demonstrated on a larger scale that is more representative of the national population and includes subgroup analysis across pertinent patient demographics and analysis at a facility level, has not been well studied.

The purpose of this study was to quantify the decrease and subsequent rebound in breast cancer screening and diagnostic metrics during the COVID-19 pandemic using the National Mammography Database (NMD).

Methods

The NMD

The NMD was established by the ACR in 2008 to facilitate quality improvement and research efforts for screening mammography practices in the United States [13]. The NMD represents the broadest coverage of all national and regional breast imaging databases in the United States and allows subgroup analysis to assess for disproportionate impacts on specific patient and facility demographics. The NMD includes the results of more than 31 million mammographic examinations, representing 690 facilities in 45 states [14]. All NMD data are HIPAA compliant, anonymized, and deidentified before analysis by non-NMD investigators, who do not have access to any patient-, physician-, or facility-identifying information.

Study Population

The 377 distinct facilities that submitted data to the NMD from March 1, 2019, through May 31, 2021, were included for analysis. This duration was chosen to span 1 year before the peak of the COVID-19 pandemic in spring 2020 (March, April, and May) as well as 1 year after the peak. Patient demographics included age and race (Asian; black; Native American, Native Hawaiian, or Pacific Islander; white; or unknown). Facility demographics included regional location (Northeast, South, Midwest, or West), community type (metropolitan [>100,000 persons], suburban [50,000-100,000 persons], or rural [<50,000 persons]), and facility type (academic or university, community hospital, freestanding imaging center, or multispecialty clinic).

Outcomes Measures and Analysis

To assess for changes in the use of breast cancer screening services before, during, and after the height of the COVID-19 pandemic, we compared the number of occurrences per facility for screening mammography, diagnostic mammography, biopsies performed, and cancer diagnoses at all sites that contributed to the NMD across three time periods: pre-COVID-19 (March 1, 2019, to May 31, 2019), peak COVID-19 (March 1, 2020, to May 31, 2020), and COVID-19 recovery (March 1, 2021, to May 31, 2021). Because health care encounters tend to have “seasonality” (eg, patients often seek the bulk of their preventive care at the beginning or end of the year), we matched the date ranges in each of our three time periods [15]. Matched date ranges in each year help mitigate any skewness that would otherwise occur had we widened our ranges to entire calendar years for 2020 and portions of calendar years for 2019 and 2021.

Because the numbers of encounters per facility in each of the four encounter categories listed previously were not normally distributed, we assessed the median number of encounters and compared these medians between each possible pairing of time periods using nonparametric, one-sided Wilcoxon’s rank-sum tests, resulting in three separate measures (ie, pre-COVID-19 vs peak COVID-19, peak COVID-19 vs COVID-19 recovery, and pre-COVID-19 vs COVID-19 recovery). We anticipated seeing significantly fewer encounters from pre-COVID-19 to peak COVID-19 and significantly more encounters from peak COVID-19 to COVID-19 recovery with no statistically significant difference from pre-COVID-19 to COVID-19 recovery. To avoid potentially “artificial” or overstated statistically significant findings with such large encounter numbers, any comparison with more than 10,000 total encounters for both groups used a more conservative α value of 0.01 for statistical significance; comparisons with fewer than 10,000 encounters used an α value of 0.05. Alpha was not further adjusted to account for the number of comparisons. Results are presented as numbers, medians, and interquartile ranges.

Results

Overall Study Population and Metrics

There were 5,633,783 screening mammographic studies, 1,282,374 diagnostic mammographic studies, 231,390 biopsies, and 69,657 cancer diagnoses reported from March 1, 2019, through May 31, 2021. A breakdown by patient and facility demographics over the entire study period is reported in Table 1 . The greatest decrease in volume during the peak COVID-19 period was for screening mammography (36.3% of pre-COVID-19), and the smallest decrease in volumes was for diagnostic mammography (57.9% of pre-COVID-19), followed by biopsies (47.3% of pre-COVID-19) and cancer diagnoses (48.7% of pre-COVID-19). Similarly, the rebound during the COVID-19 recovery period was weakest for screening mammography (85.3% of pre-COVID-19) and greatest for diagnostic mammography (97.8% of pre-COVID-19), followed by biopsies (91.5% of pre-COVID-19) and cancer diagnoses (92.0% of pre-COVID-19). A graphical representation of the outcome metrics over time is shown in Figures 1 and 2 .

Table 1.

Total volume of screening mammographic examinations, diagnostic mammographic examinations, breast biopsies, and cancer diagnoses by patient and facility demographics from March 1, 2019, through May 31, 2021

Variable Screening Mammography
Diagnostic Mammography
Biopsies
Cancer Diagnoses
n % n % n % n %
Age
 <40 y 62,295 1.1 130,899 10.2 14,292 6.2 1,854 2.7
 40-49 y 1,175,114 20.9 323,706 25.2 57,021 24.6 8,980 12.9
 50-59 y 1,551,265 27.5 304,685 23.8 55,606 24.0 14,998 21.5
 60-69 y 1,631,623 29.0 286,704 22.4 57,257 24.7 21,662 31.1
 70-79 y 999,124 17.7 186,031 14.5 37,559 16.2 16,621 23.9
 ≥80 y 214,362 3.8 50,349 3.9 9,655 4.2 5,542 8.0
Race
 Asian 109,497 1.9 20,671 1.6 5,268 2.3 1,427 2.0
 Black 246,026 4.4 43,924 3.4 8,856 3.8 2,472 3.5
 Native American, Native Hawaiian, or Pacific Islander 38,932 0.7 6,046 0.5 1,260 0.5 363 0.5
 White 1,923,641 34.1 367,601 28.7 75,510 32.6 24,027 34.5
 Unknown 3,315,683 58.9 844,130 65.8 140,496 60.7 41,368 59.4
Community type
 Academic/university 599,772 11.0 169,674 13.5 33,856 15.0 10,251 15.0
 Community hospital 2,301,231 42.1 514,308 40.9 95,234 42.1 28,676 41.9
 Multispecialty clinic 391,185 7.2 52,402 4.2 12,306 5.4 3,793 5.5
 Freestanding imaging center 2,178,651 39.8 522,098 41.5 84,699 37.5 25,660 37.5
Facility type
 Metropolitan (>100,000 persons) 3,268,582 58.0 828,716 64.6 142,980 61.8 44,231 63.5
 Suburban/small (50,000-100,000 persons) 1,872,684 33.2 345,009 26.9 70,173 30.3 20,341 29.2
 Rural (<50,000 persons) 492,521 8.7 108,650 8.5 18,237 7.9 5,085 7.3
Region
 Northeast 1,348,398 23.9 286,831 22.4 53,606 23.2 14,932 21.4
 Midwest 1,391,629 24.7 257,868 20.1 51,927 22.4 17,816 25.6
 South 1,404,760 24.9 328,844 25.6 56,220 24.3 15,850 22.8
 West 1,489,000 26.4 408,832 31.9 69,637 30.1 21,059 30.2

Fig. 1.

Fig. 1

Monthly volume of screening and diagnostic mammographic examinations from the National Mammography Database from March 1, 2019, through May 31, 2021. The green, red, and yellow boxes refer to the 3-month-long pre-COVID-19, peak COVID-19, and COVID-19 recovery periods, respectively, used for analysis. COVID-19 = coronavirus disease 2019.

Fig. 2.

Fig. 2

Monthly volume of biopsies performed and cancer diagnoses from the National Mammography Database from March 1, 2019, through May 31, 2021. The green, red, and yellow boxes refer to the 3-month-long pre-COVID-19, peak COVID-19, and COVID-19 recovery periods, respectively, used for analysis. COVID-19 = coronavirus disease 2019.

Screening Mammography

The volume of screening mammographic examinations during the peak COVID-19 period (246,610 studies) was 36.3% of the pre-COVID-19 period (678,890 studies; Figure 1). During the nadir of the peak COVID-19 period in April 2020, screening mammography volume was 3.7% (8,403 studies) of the monthly average during the pre-COVID-19 period (226,297 studies). As shown in Table 2 , the greatest decreases were seen for women aged 80 years or older (32.2% of pre-COVID-19), Asian women (28.4% of pre-COVID-19), and facilities in suburban communities (34.3% of pre-COVID-19), with academic or university affiliations (30.4% of pre-COVID-19), and in the Northeast (31.0% of pre-COVID-19). At the facility level, there were statistically significant decreases (P < .01) for all demographics studied.

Table 2.

Changes in screening mammography quarterly volumes in the pre-COVID-19, peak COVID-19, and COVID-19 recovery periods by patient and facility demographics

Variable Pre-COVID-19
Peak COVID-19
COVID-19 Recovery
Pre-COVID-19 vs Peak COVID-19
Peak COVID-19 vs COVID-19 Recovery
Pre-COVID-19 vs COVID-19 Recovery
Facility Median (IQR) Total n Facility Median (IQR) Total n Facility Median (IQR) Total n Facility P Value Total Change % Facility P Value Total Change % Facility P Value Total Change %
Age group
 <40 y 14 (4-25) 7,922 5 (2-10) 2,936 11 (4-24) 7,055 <0.001 37.1 <0.001 240.3 0.172 89.1
 40-49 y 247 (110-468) 142,207 88 (39-181) 52,377 242 (110-409) 128,369 <0.001 36.8 <0.001 245.1 0.131 90.3
 50-59 y 329 (144-607) 189,226 119 (48-225) 68,741 272 (128-496) 158,123 <0.001 36.3 <0.001 230.0 0.017 83.6
 60-69 y 334 (149-642) 194,679 109 (53-237) 70,686 279 (135-537) 163,760 <0.001 36.3 <0.001 231.7 0.017 84.1
 70-79 y 192 (79-393) 117,886 67 (27-144) 43,181 164 (72-330) 101,003 <0.001 36.6 <0.001 233.9 0.021 85.7
 ≥80 y 43 (17-89) 26,969 11 (5-29) 8,689 30 (13-67) 20,526 <0.001 32.2 <0.001 236.2 0.001 76.1
Race
 Asian 0 (0-26) 14,705 0 (0-7) 4,181 0 (0-20) 10,664 0.002 28.4 0.018 255.1 0.2145 72.5
 Black 2 (0-58) 32,163 0 (0-18) 10,627 1 (0-43) 24,717 0.001 33.0 0.021 232.6 0.157 76.8
 Native American, Native Hawaiian or Pacific Islander 0 (0-4) 3,405 0 (0-1) 2,479 0 (0-4) 4,538 <0.001 72.8 <0.001 183.1 0.421 133.3
 White 152 (0-862) 243,520 44 (0-262) 83,897 76 (0-663) 191,245 <0.001 34.5 0.002 228.0 0.123 78.5
 Unknown 422 (84-1,209) 385,095 141 (23-478) 145,426 420 (71-1,079) 347,672 <0.001 37.8 <0.001 239.1 0.189 90.3
Community type
 Metropolitan (>100,000 persons) 1,839 (805-3,218) 397,037 646 (222-1,235) 144,170 1,539 (729-2,904) 347,318 <0.001 36.3 <0.001 240.9 0.124 87.5
 Suburban/small (50,000-100,000 persons) 1,213 (766-1,905) 226,200 432 (234-694) 77,598 990 (589-1,544) 180,933 <0.001 34.3 <0.001 233.2 0.010 80.0
 Rural (<50,000 persons) 391 (139-939) 55,653 167 (71-423) 24,842 323 (160-748) 50,585 <0.001 44.6 <0.001 203.6 0.454 90.9
Facility type
 Academic/university 1,475 (719-3,841) 73,164 510 (243-1,287) 22,231 1,221 (667-2,507) 58,027 <0.001 30.4 0.002 261.0 0.188 79.3
 Community hospital 1,290 (402-2,227) 286,548 410 (133-796) 102,767 820 (239-1,881) 231,914 <0.001 35.9 <0.001 225.7 0.028 80.9
 Multispecialty clinic 835 (450-2,022) 46,341 264 (135-657) 15,954 781 (492-1,504) 43,143 <0.001 34.4 <0.001 270.4 0.451 93.1
 Freestanding imaging center 1,183 (627-2,093) 252,863 457 (213-778) 97,591 1,148 (677-1,794) 224,701 <0.001 38.6 <0.001 230.2 0.233 88.9
Region
 Northeast 1,209 (516-1,780) 162,705 378 (167-601) 50,486 955 (446-1,575) 138,814 <0.001 31.0 <0.001 275.0 0.076 85.3
 Midwest 997 (584-2,185) 172,423 342 (175-691) 59,834 852 (465-1,769) 140,220 <0.001 34.7 <0.001 234.3 0.084 81.3
 South 1,260 (563-2,379) 160,976 602 (221-987) 67,588 1,193 (602-2,009) 137,475 <0.001 42.0 <0.001 203.4 0.254 85.4
 West 1,281 (462-2,888) 182,786 488 (151-1,192) 68,702 1,164 (324-2,271) 162,327 <0.001 37.6 <0.001 236.3 0.222 88.8

Note: Facility refers to the median and IQR for facilities. Total refers to the total reported at all facilities. Facility P value compares the metrics at the facility level. Statistical significance was defined as a P value of .01 for encounters greater than 10,000 and .05 for encounters less than 10,000. Statistically significant values are in boldface type. Total change refers to the second comparator group divided by the first comparator group as a percentage. COVID-19 = coronavirus disease 2019; IQR = interquartile range.

During the COVID-19 recovery period, screening mammography volume (578,836 studies) rebounded to 85.3% of the pre-COVID-19 level (678,890 studies; Figure 1). The smallest rebounds were for women aged 80 years or older (76.1% of pre-COVID-19, P = .001), Asian women (72.5% of pre-COVID-19), and facilities in suburban communities (80.0% of pre-COVID-19), with academic or university affiliations (79.3% of pre-COVID-19), and in the Midwest (81.3% of pre-COVID-19).

Diagnostic Mammography

The volume of diagnostic mammographic examinations during the peak COVID-19 period (83,915 studies) was 57.9% of the pre-COVID-19 period (144,855 studies, Figure 1). During the nadir of the peak COVID-19 period in April 2020, diagnostic mammography volume was 30.2% (14,586 studies) of the monthly average in the pre-COVID-19 period (48,285 studies). As shown in Table 3 , the greatest decreases were seen for women aged 80 years and older (50.9% of pre-COVID-19), Asian women (45.1% of pre-COVID-19), and facilities in metropolitan communities (53.2% of pre-COVID-19), with academic or university affiliations (55.1% of pre-COVID-19), and in the West (54.2% of pre-COVID-19). At the facility level, there were statistically significant decreases for all age groups 50 years and older (P < .01 for all); Native American, Native Hawaiian, or Pacific Islander women (P = .014); and facilities in metropolitan communities (P = .009), as shown in Table 2. There was a significant linear decrease in diagnostic mammographic examinations with increasing age decade (R 2 = 0.88, P = .005; Figure 3 ).

Table 3.

Changes in diagnostic mammography quarterly volumes in the pre-COVID-19, peak COVID-19, and COVID-19 recovery periods by patient and facility demographics

Variable Pre-COVID-19
Peak COVID-19
COVID-19 Recovery
Pre-COVID-19 vs Peak COVID-19
Peak COVID-19 vs COVID-19 Recovery
Pre-COVID-19 vs COVID-19 Recovery
Facility Median (IQR) Total n Facility Median (IQR) Total n Facility Median (IQR) Total n Facility P Value Total Change % Facility P Value Total Change % Facility P Value Total Change %
Age group
 <40 y 7 (0-44) 15,062 6 (0-34) 9,952 11 (0-45) 15,056 0.107 66.1 0.019 151.3 0.236 100.0
 40-49 y 30 (1-104) 35,981 20 (0-75) 21,434 35 (1-118) 37,240 0.023 59.6 0.002 173.7 0.214 103.5
 50-59 y 30 (1-95) 34,765 19 (0-60) 19,772 35 (1-96) 33,087 0.007 56.9 0.003 167.3 0.411 95.2
 60-69 y 28 (0-91) 32,216 17 (0-58) 18,145 32 (2-93) 30,647 0.009 56.3 0.001 168.9 0.296 95.1
 70-79 y 17 (0-64) 20,964 10 (0-38) 11,624 18 (1-57) 20,042 0.004 55.4 0.001 172.4 0.409 95.6
 ≥80 y 4 (0-17) 5,866 2 (0-9) 2,988 5 (0-16) 5,615 0.001 50.9 <0.001 187.9 0.339 95.7
Race
 Asian 0 (0-0) 2,563 0 (0-0) 1,155 0 (0-0) 2,176 0.265 45.1 0.411 188.4 0.342 84.9
 Black 0 (0-4) 5,241 0 (0-2) 2,848 0 (0-4) 4,496 0.202 54.3 0.141 157.9 0.406 85.8
 Native American, Native Hawaiian, or Pacific Islander 0 (0-0) 598 0 (0-0) 518 0 (0-0) 653 0.014 86.6 0.180 126.1 0.105 109.2
 White 0 (0-113) 43,546 0 (0-57) 24,621 0 (0-81) 36,543 0.125 56.5 0.325 148.4 0.246 83.9
 Unknown 35 (0-197) 92,907 21 (0-156) 54,773 40 (0-245) 97,818 0.041 59.0 0.008 178.6 0.233 105.3
Community type
 Metropolitan (>100,000 persons) 276 (9-874) 99,039 178 (4-526) 52,650 303 (58-864) 94,817 0.009 53.2 0.009 180.1 0.483 95.7
 Suburban/small (50,000-100,000 persons) 97 (0-256) 35,065 70 (0-180) 23,219 125 (0-285) 36,169 0.078 66.2 0.027 155.8 0.301 103.1
 Rural (<50,000 persons) 40 (15-171) 10,751 36 (13-138) 8,046 54 (11-167) 10,701 0.258 74.8 0.156 133.0 0.352 99.5
Facility type
 Academic/university 275 (0-1,267) 18,618 223 (0-660) 10,256 350 (0-988) 17,277 0.142 55.1 0.179 168.5 0.470 92.8
 Community hospital 150 (30-385) 56,929 97 (25-271) 34,632 155 (39-389) 57,305 0.049 60.8 0.007 165.5 0.248 100.7
 Multispecialty clinic 1 (0-182) 5,098 1 (0-153) 4,193 0 (0-117) 5,832 0.365 82.2 0.377 139.1 0.251 114.4
 Freestanding imaging center 155 (0-376) 60,146 90 (0-260) 33,950 176 (0-407) 59,554 0.050 56.4 0.024 175.4 0.389 99.0
Region
 Northeast 137 (0-368) 31,526 65 (0-181) 17,194 174 (20-399) 32,166 0.067 54.5 0.003 187.1 0.172 102.0
 Midwest 86 (0-255) 26,799 48 (0-178) 17,579 72 (0-254) 25,637 0.118 65.6 0.183 145.8 0.402 95.7
 South 172 (2-594) 38,841 157 (1-406) 23,280 213 (1-603) 34,729 0.122 59.9 0.108 149.2 0.472 89.4
 West 157 (24-590) 47,689 111 (28-431) 25,862 218 (37-606) 49,155 0.185 54.2 0.108 190.1 0.381 103.1

Note: Facility refers to the median and IQR for facilities. Total refers to the total reported at all facilities. Facility P value compares the metrics at the facility level. Statistical significance was defined as a P value of .01 for encounters greater than 10,000 and .05 for encounters less than 10,000. Statistically significant values are in boldface type. Total change refers to the second comparator group divided by the first comparator group as a percentage. COVID-19 = coronavirus disease 2019; IQR = interquartile range.

Fig. 3.

Fig. 3

Percentage of diagnostic mammographic examinations during the peak COVID-19 versus the pre-COVID-19 period by age decade with fitted trend line. COVID-19 = coronavirus disease 2019.

During the COVID-19 recovery, diagnostic mammography volume (141,687 studies) rebounded to 97.8% of the pre-COVID-19 level (144,855 studies; Figure 1). The smallest rebounds were for women aged 60 to 69 years (95.1% of pre-COVID-19), white women (83.9% of pre-COVID-19), and facilities in metropolitan communities (95.7% of pre-COVID-19), with academic or university affiliations (92.8% of pre-COVID-19), and in the South (89.4% of pre-COVID-19). There were no significant differences in the pre-COVID-19 versus COVID-19 recovery period diagnostic volumes for the demographics studied.

Biopsies

The volume of biopsies during the peak COVID-19 period (13,191 biopsies) was 47.3% of the pre-COVID-19 period (27,907 biopsies; Figure 2). During the nadir of the peak COVID-19 period in April 2020, the biopsy volume was 20.1% (1,876 biopsies) of the monthly average in the pre-COVID-19 period (9,302 biopsies). As shown in Table 4 , the largest declines were seen for women aged 50 to 59 and 60 to 69 years (45.2% of pre-COVID-19 for both), Asian women (43.2% of pre-COVID-19), and facilities in suburban communities (44.0% of pre-COVID-19), with academic or university affiliations (45.1% of pre-COVID-19), and in the Northeast (38.9% of pre-COVID-19). At the facility level, there were statistically significant decreases (P < .01) for all demographics except for facilities in rural communities (P = .122) and in the West (P = .095).

Table 4.

Changes in biopsy quarterly volumes in the pre-COVID-19, peak COVID-19, and COVID-19 recovery periods by patient and facility demographics

Variable Pre-COVID-19
Peak COVID-19
COVID-19 Recovery
Pre-COVID-19 vs Peak COVID-19
Peak COVID-19 vs COVID-19 Recovery
Pre-COVID-19 vs COVID-19 Recovery
Facility Median (IQR) Total n Facility Median (IQR) Total n Facility Median (IQR) Total n Facility P Value Total Change % Facility P Value Total Change % Facility P Value Total Change %
Age
 <40 y 1 (0-4) 1,676 0 (0-3) 1,148 1 (0-4) 1,611 0.024 68.5 0.021 140.3 0.469 96.1
 40-49 y 6 (1-20) 6,715 3 (0-11) 3,198 7 (1-19) 6,527 <0.001 47.6 <0.001 204.1 0.477 97.2
 50-59 y 6 (1-21) 6,950 3 (0-10) 3,143 6 (1-16) 6,061 <0.001 45.2 <0.001 192.8 0.158 87.2
 60-69 y 7 (2-23) 6,936 3 (0-10) 3,133 7 (2-18) 6,245 <0.001 45.2 <0.001 199.3 0.279 90.0
 70-79 y 4 (0-14) 4,462 2 (0-6) 2,021 4 (0-12) 4,056 <0.001 45.3 <0.001 200.7 0.143 90.9
 ≥80+ y 1 (0-4) 1,168 0 (0-2) 548 1 (0-3) 1,047 <0.001 46.9 <0.001 191.1 0.076 89.6
Race
 Asian 0 (0-0) 662 0 (0-0) 286 0 (0-0) 537 0.006 43.2 0.011 187.8 0.405 81.1
 Black 0 (0-1) 1,078 0 (0-0) 573 0 (0-1) 930 0.001 53.2 0.009 162.3 0.261 86.3
 Native American, Native Hawaiian, or Pacific Islander 0 (0-0) 122 0 (0-0) 84 0 (0-0) 143 0.003 68.9 0.002 170.2 0.439 117.2
 White 2 (0-28) 9,736 0 (0-10) 4,247 2 (0-18) 7,350 0.002 43.6 0.017 173.1 0.208 75.5
 Unknown 9 (1-37) 16,309 4 (0-20) 8,001 9 (0-41) 16,587 <0.001 49.1 <0.001 207.3 0.360 101.7
Community type
 Metropolitan (>100,000 persons) 54 (13-155) 17,393 24 (5-79) 8,262 48 (14-146) 16,382 <0.001 47.5 <0.001 198.3 0.362 94.2
 Suburban/small (50,000-100,000 persons) 29 (7-60) 8,414 11 (2-30) 3,698 26 (9-58) 7,446 <0.001 44.0 <0.001 201.4 0.426 88.5
 Rural (<50,000 persons) 5 (0-26) 2,100 4 (0-16) 1,231 6 (0-24) 1,719 0.122 58.6 0.218 139.6 0.340 81.9
Facility type
 Academic/university 91 (17-260) 4,095 43 (5-111) 1,847 56 (9-205) 3,231 0.012 45.1 0.094 174.9 0.147 78.9
 Community hospital 30 (4-73) 11,248 15 (2-39) 5,564 24 (4-68) 10,348 0.002 49.5 0.015 186.0 0.226 92.0
 Multispecialty clinic 10 (2-51) 1,344 1 (0-34) 676 10 (4-40) 1,554 0.030 50.3 0.021 229.9 0.356 115.6
Freestanding imaging center 26 (8-74) 10,396 11 (4-34) 4,853 26 (10-71) 9,830 <0.001 46.7 <0.001 202.6 0.375 94.6
 Region
 Northeast 24 (4-76) 6,809 9 (1-30) 2,649 24 (9-59) 5,550 0.003 38.9 <0.001 209.5 0.495 81.5
 Midwest 19 (7-71) 6,277 9 (1-27) 2,783 19 (6-51) 5,450 <0.001 44.3 <0.001 195.8 0.186 86.8
 South 28 (8-107) 6,860 11 (3-63) 3,444 32 (8-96) 6,192 0.008 50.2 0.014 179.8 0.458 90.3
 West 37 (8-116) 7,961 27 (7-66) 4,315 36 (7-118) 8,355 0.095 54.2 0.105 193.6 0.486 104.9

Note: Facility refers to the median and IQR for facilities. Total refers to the total reported at all facilities. Facility P value compares the metrics at the facility level. Statistical significance was defined as a P value of .01 for encounters greater than 10,000 and .05 for encounters less than 10,000. Statistically significant values are in boldface type. Total change refers to the second comparator group divided by the first comparator group as a percentage. COVID-19 = coronavirus disease 2019; IQR = interquartile range.

During the COVID-19 recovery, biopsy volume (25,547 biopsies) rebounded to 91.5% of the pre-COVID-19 level (27,907 biopsies; Figure 1). The smallest rebounds were for women aged 60 to 69 years (90.0% of pre-COVID-19), white women (75.5% of pre-COVID-19), and facilities in rural communities (81.9% of pre-COVID-19), with academic or university affiliations (78.9% of pre-COVID-19), and in the Northeast (81.5% of pre-COVID-19). There were no significant differences in the pre-COVID-19 versus COVID-19 recovery period diagnostic volumes for the demographics studied.

Cancer Diagnoses

The volume of cancer diagnoses during the peak COVID-19 period (4,101 cancers) was 48.7% of the pre-COVID-19 period (8,413 cancers; Figure 2). During the nadir of the peak COVID-19 period in April 2020, the cancer diagnosis volume was 20.5% (576 cancers) of the monthly average in the pre-COVID-19 period (2,804 cancers). As shown in Table 5 , the greatest decreases were seen for women aged 60 to 69 years (46.3% of pre-COVID-19), Asian women (35.5% of pre-COVID-19), and facilities in suburban communities (45.2% of pre-COVID-19), with academic or university affiliations (45.4% of pre-COVID-19), and in the Northeast (39.7% of pre-COVID-19). At the facility level, there were statistically significant decreases (P < .05) for all demographics except age < 40 years (P = .245); Asian race (P = .069); Native American, Native Hawaiian, or Pacific Islander race (P = .154); rural location (P = .054); and location in the West (P = .095).

Table 5.

Changes in cancer quarterly volumes in the pre-COVID-19, peak COVID-19, and COVID-19 recovery periods by patient and facility demographics

Variable Pre-COVID-19
Peak COVID-19
COVID-19 Recovery
Pre-COVID-19 vs Peak COVID-19
Peak COVID-19 vs COVID-19 Recovery
Pre-COVID-19 vs COVID-19 Recovery
Facility Median (IQR) Total n Facility Median (IQR) Total n Facility Median (IQR) Total n Facility P Value Total Change % Facility P Value Total Change % Facility P Value Total Change %
Age
 <40 y 0 (0-0) 199 0 (0-0) 189 0 (0-0) 200 0.245 95.0 0.424 105.8 0.315 100.5
 40-49 y 1 (0-3) 1,079 0 (0-2) 558 1 (0-3) 1,047 <0.001 51.7 <0.001 187.6 0.397 97.0
 50-59 y 2 (0-5) 1,888 1 (0-3) 894 1 (0-5) 1,614 <0.001 47.4 0.001 180.5 0.103 85.5
 60-69 y 3 (0-9) 2,633 1 (0-4) 1,219 2 (0-8) 2,428 <0.001 46.3 <0.001 199.2 0.193 92.2
 70-79 y 2 (0-6) 1,958 1 (0-3) 929 1 (0-5) 1,868 <0.001 47.4 <0.001 201.1 0.126 95.4
 ≥80 y 0 (0-2) 656 0 (0-1) 312 0 (0-2) 583 <0.001 47.6 0.001 186.9 0.118 88.9
Race
 Asian 0 (0-0) 211 0 (0-0) 75 0 (0-0) 152 0.069 35.5 0.344 202.7 0.144 72.0
 Black 0 (0-0) 303 0 (0-0) 176 0 (0-0) 257 0.018 58.1 0.098 146.0 0.211 84.8
 Native American, Native Hawaiian, or Pacific Islander 0 (0-0) 34 0 (0-0) 20 0 (0-0) 34 0.154 58.8 0.015 170.0 0.121 100.0
 White 0 (0-9) 3,103 0 (0-3) 1,354 0 (0-5) 2,496 <0.001 43.6 0.011 184.3 0.107 80.4
 Unknown 3 (0-12) 4,762 1 (0-6) 2,476 2 (0-12) 4,801 <0.001 52.0 <0.001 193.9 0.277 100.8
Community type
 Metropolitan (>100,000 persons) 17 (5-48) 5,277 8 (1-27) 2,653 12 (4-48) 5,011 <0.001 50.3 <0.001 188.9 0.297 95.0
 Suburban/small (50,000-100,000 persons) 9 (3-20) 2,503 3 (0-9) 1,131 9 (2-19) 2,228 <0.001 45.2 <0.001 197.0 0.270 89.0
 Rural (<50,000 persons) 2 (0-11) 633 1 (0-4) 317 1 (0-8) 501 0.054 50.1 0.243 158.0 0.205 79.1
Facility type
 Academic/university 22 (6-78) 1,256 13 (2-31) 570 16 (3-55) 1,035 0.032 45.4 0.147 181.6 0.248 82.4
 Community hospital 10 (1-27) 3,422 4 (0-14) 1,681 8 (1-25) 3,101 <0.001 49.1 0.019 184.5 0.158 90.6
 Multispecialty clinic 3 (0-17) 420 0 (0-8) 212 4 (1-11) 533 0.014 50.5 0.009 251.4 0.402 126.9
 Freestanding imaging center 8 (2-22) 3,110 3 (1-11) 1,565 9 (2-21) 2,970 <0.001 50.3 <0.001 189.8 0.334 95.5
Region
 Northeast 9 (1-20) 1,943 2 (0-9) 771 7 (1-16) 1,494 <0.001 39.7 0.004 193.8 0.228 76.9
 Midwest 8 (2-26) 2,217 3 (0-10) 988 6 (2-23) 1,969 <0.001 44.6 <0.001 199.3 0.192 88.8
 South 9 (2-25) 1,911 4 (1-20) 1,019 9 (1-35) 1,736 0.013 53.3 0.025 170.4 0.447 90.8
 West 8 (2-41) 2,342 5 (1-23) 1,323 11 (0-42) 2,541 0.095 56.5 0.149 192.1 0.437 108.5

Note: Facility refers to the median and IQR for facilities. Total refers to the total reported at all facilities. Facility P value compares the metrics at the facility level. Statistical significance was defined as a P value of .01 for encounters greater than 10,000 and .05 for encounters less than 10,000. Statistically significant values are in boldface type. Total change refers to the second comparator group divided by the first comparator group as a percentage. COVID-19 = coronavirus disease 2019; IQR = interquartile range.

During the COVID-19 recovery, cancer diagnoses (7,740 cancers) rebounded to 92.0% of the pre-COVID-19 level (8,413 cancers; Figure 2). The smallest rebounds were for women aged 50 to 59 years (85.5% of pre-COVID-19), Asian women (72.0% of pre-COVID-19), and facilities in rural communities (79.1% of pre-COVID-19), with academic or university affiliations (82.4% of pre-COVID-19), and in the Northeast (76.9% of pre-COVID-19). There were no significant differences in the pre-COVID-19 versus COVID-19 recovery period diagnostic volumes for the demographics studied. The monthly average of breast cancers diagnosed from March 2019 to February 2020 was 2,843 cancers. The cumulative cancer deficit (ie, monthly average from preceding year minus cancer diagnoses per month in current year) accumulated from the peak COVID-19 to the COVID-19 recovery period was 7,113 cancers, as shown in Figure 4 .

Fig. 4.

Fig. 4

Monthly and cumulative cancer deficits from March 2020 to May 2021 on the basis of the average monthly cancer diagnoses from March 2019 to February 2020.

Discussion

These results from the NMD provide the broadest and largest analysis in the United States of the impact of the COVID-19 pandemic on breast cancer screening outcomes both during the peak of the pandemic and in the subsequent (rebound) year. The COVID-19 pandemic resulted in acute and pronounced declines for all breast imaging metrics studied during the peak COVID-19 period, but the effect was greatest for screening mammography (36.3% of pre-COVID-19). The decrease in screening mammography followed federal guidelines to postpone screening services, and similar results have been reported using regional and smaller national data sets [2,5,6]. However, there is a paucity of longer follow-up data to document changes in patient behaviors and the seasonality associated with health maintenance examinations [5,6,16]. Our data collected 1 year after the acute phase of the pandemic, during the COVID-19 recovery period, demonstrate that screening mammography volumes (85.3% of pre-COVID-19) continued to lag behind all other breast imaging metrics studied (range, 91.5%-97.8% of pre-COVID-19), and this was exaggerated for women aged 80 years and older (76.1% of pre-COVID-19). The persistent failure to return to regular screening intervals has also been reproduced in colon and cervical cancer screening [16]. If volumes do not normalize, screening mammography will remain underused among asymptomatic women. Strategies to facilitate safe breast imaging have been developed, but radiologists will need to develop outreach efforts, especially at the local level, directed toward patients and ordering providers on the importance of screening mammography in order to improve utilization rates [10,11].

As expected, there was an acute decrease in breast cancer diagnoses during the peak COVID-19 period. But although cancer diagnoses largely rebounded (92.0% of pre-COVID-19). This is especially worrying as cancer diagnoses have not reached pre-COVID-19 levels, and the cumulative breast cancer deficit since the start of the pandemic continues to grow (Fig. 4). This rebound represents a mix of cancers not diagnosed during the peak COVID-19 period as well as the normal cancers detected through routine practice. There are major concerns that in the near future, depending on the lead time of breast cancer, there will be an increase in cancer diagnoses and that a larger proportion of breast cancers will be diagnosed at a higher stage and thus have a worse prognosis. Analysis of Breast Cancer Surveillance Consortium data demonstrates that decreases in cancer diagnoses were due largely to fewer screen-detected cancers [3]. The NMD unfortunately does not include tumor staging information to assess clinical outcomes and prognosis. To date, one study from Italy has demonstrated that a 2-month pause in mammographic screening resulted in an 11% increase in node-positive breast cancer and a 10% increase in stage III breast cancer [17]. Similarly, an increase in stage III breast cancer (8.4% pre-COVID-19 vs 23.8% post-COVID-19) and systemic first-line chemotherapy (23.0% pre-COVID-19 vs 36.5% post-COVID-19) have been reported in South Korea [18]. Longer term modeling studies all report an increase in poor outcomes, including life years lost, excess breast cancer deaths, and treatment morbidity [4,19,20]. Although there are differences in the modeling estimates on the basis of assumptions around screening practices (ie, annual vs biennial, screening utilization rates), a key unknown is how quickly screening practices will normalize. Our results indicate that screening practices may take much longer to normalize than previously hypothesized and that models will need to be adjusted for the persistent decline. Given the latency of breast cancer diagnosis and mortality as well as the persistent reduction in breast cancer screening practices currently, it may be several years before these results are fully realized.

There were notable differences in the reported breast cancer metrics on the basis of patient demographics. Compared with all other racial groups, Asian women had the largest decrease in screening mammography, diagnostic mammography, and cancer diagnoses during peak COVID-19 and experienced the smallest rebound in screening mammography and cancer diagnoses during COVID-19 recovery. Published literature examining the impact of the pandemic on breast cancer screening for different racial and ethnic groups is very mixed; however, there are examples of the disproportionate impact on Asian women, with studies demonstrating large decreases in screening mammography volumes [5,7,21] and fewer breast cancer diagnoses, similar to our findings [3]. Similar patterns for Asian women have been noted for other screening services, including cervical cancer [7]. Much of the focus on race/ethnicity in breast cancer screening outreach efforts unrelated to the pandemic has been directed toward black women because of their high rates of breast cancer and generally worse outcomes [22]. But our results suggest that outreach efforts directed toward the Asian community are important as well. These efforts could include engaging with local community organizations, disaggregating the impact of COVID-19 on specific Asian populations, especially immigrant groups, and identifying any underlying cultural barriers to returning for routine care [23]. Finally, there were greater decreases and more limited recovery across most breast cancer metrics for elderly women. COVID-19 had a disproportionate impact on elderly patients, especially minority elderly patients, with higher rates of death and severe infection from COVID-19 as well as an increased risk for neglect, loss of social support networks, and economic hardships [24, 25, 26]. Outreach efforts and reestablishing support networks are critical to meet the needs of this patient population, who are at the highest risk for developing breast cancer.

The early phase of the COVID-19 pandemic had an unequal geographic distribution, which is reflected in the outcome differences by facility demographics [27]. Facilities in the Northeast had the largest decrease in all metrics during the peak COVID-19 period and continued to have the smallest rebound in breast biopsies and cancer diagnoses during the COVID-19 recovery period. This may reflect the very large numbers of COVID-19 cases in metropolitan areas such as New York City [27]. The impact of breast imaging metrics on community type is mixed. Suburban and metropolitan facilities had larger decreases across all metrics during the peak COVID-19 period, which likely reflects the initial spread of disease in denser population centers. However, there were notably smaller rebounds in biopsies and cancer diagnoses in rural facilities during the COVID-19 recovery period, which likely reflects shifts in the spread of disease from urban to rural facilities [28,29]. Facilities affiliated with academic practices had the largest declines during peak COVID-19 and the smallest rebound during the COVID-19 recovery period for every breast cancer metric in our database. This may be due to a fear that academic centers were also treating many patients with COVID-19 and may be confounded by the higher concentration of academic facilities in metropolitan and suburban locations.

There were limitations to this study. Although the number of breast care encounters in the NMD is very large, which facilitates many subgroup analyses, some subgroups were still small. For example, measurements for women younger than 40 years and for Native American, Native Hawaiian, or Pacific Islander women have much wider confidence intervals. We compensated for this by adjusting our threshold for statistical significance on the basis of sample sizes. Additionally, a majority of patients have their race documented as “unknown” (58.9%), which is a limitation of NMD data entry. Data from the NMD are exported in aggregate, precluding multivariate analysis at the patient level, which would facilitate testing of confounding factors, especially for demographic subgroup analysis. Facilities have several months to report their metrics to the NMD, so data from late 2021 were not available for analysis. The NMD is also not linked with a tumor registry to allow assessment of tumor outcomes.

Take-Home Points

  • There were major decreases in screening mammography, diagnostic mammography, breast biopsies, and cancer diagnoses during the peak COVID-19 period, with a rapid rebound during the COVID-19 recovery period.

  • COVID-19 had the greatest impact on screening mammography, and utilization rates have not returned to baseline, which may have long-term implications for breast cancer staging and outcomes.

  • The acute deficits in breast cancer diagnoses during the peak COVID-19 period continued to increase in the following year.

  • COVID-19 had a disproportionate effect on older women and Asian women for multiple breast cancer screening metrics during the peak COVID-19 and COVID-19 recovery periods.

  • The impact of COVID-19 on facility demographics likely reflects differences in the temporal and geographic distribution of disease.

Acknowledgments

The authors thank ACR staff members for assistance in preparation of the NMD data and acknowledge guidance and input by the NMD Steering Committee for this analysis.

Footnotes

This research was supported by the ACR’s National Radiology Data Registry. The views expressed in this report represent those of the authors and do not necessarily represent the official views of the National Radiology Data Registry or the ACR. The authors state that they have no conflict of interest related to the material discussed in this article. The authors are non-partner/non-partnership track/employees.

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