Non-participation in breast screening in Denmark: Sociodemographic determinants.

BACKGROUND: Internationally, non-participation in breast screening increased with decreasing level of education indicating importance of information campaigns to enhance awareness of screening. However, in Denmark in the 1990s the association between education and non-participation was U-shaped. We therefore analyzed recent Danish data. METHODS: Data derived from the Capital Region of Denmark, biennial, organized breast screening program 2008-2020, where women aged 50-69 were personally invited to screening. Non-participation was measured as number of women with no participation out of women eligible for at least three invitations. Sociodemographic determinants were identified by linkage to public registers. Results were reported as age adjusted odds ratios (OR) of non-participation including 95% confidence intervals (CI). RESULTS: Among 196,085 women, 86% participated. Using women with low education as baseline, the OR for professional bachelors was 0.64; and for academics 0.75. The strongest determinants of non-participation were being non-married OR 2.03; born outside Denmark OR 2.04; being self-employed OR 1.67; retired OR 3.12; on public support OR 3.66; or having co-morbidity OR 1.56. CONCLUSION: The U-shaped association between education and non-participation in breast screening prevailed. The data further indicated that screening participation was low in women with pertinent health and social problems.

Introduction of one-view tomosynthesis in population-based mammography screening: Impact on detection rate, interval cancer rate and false-positive rate.

OBJECTIVE: To assess performance endpoints of a combination of digital breast tomosynthesis (DBT) and full-field digital mammography (FFDM) compared with FFDM only in breast cancer screening. MATERIALS AND METHODS: This was a prospective population-based screening study, including eligible (50-69 years) women attending the Capital Region Mammography Screening Program in Denmark. All attending women were offered FFDM. A subgroup was consecutively allocated to a screening room with DBT. All FFDM and DBT underwent independent double reading, and all women were followed up for 2 years after screening date or until next screening date, whichever came first. RESULTS: 6353 DBT + FFDM and 395 835 FFDM were included in the analysis and were undertaken in 196 267 women in the period from 1 November 2012 to 12 December 2018. Addition of DBT increased sensitivity: 89.9% (95% confidence interval (CI): 81.0-95.5) for DBT + FFDM and 70.1% (95% CI: 68.6-71.6) for FFDM only, p < 0.001. Specificity remained similar: 98.2% (95% CI: 97.9-98.5) for DBT + FFDM and 98.3% (95% CI: 98.2-98.3) for FFDM only, p = 0.9. Screen-detected cancer rate increased statistically significantly: 11.18/1000 for DBT + FFDM and 6.49/1000 for FFDM only, p < 0.001. False-positive rate was unchanged: 1.75% for DBT + FFDM and 1.73% for FFDM only, p = 0.9. Positive predictive value for recall was 39.0% (95% CI: 31.9-46.5) for DBT + FFDM and 27.3% (95% CI: 26.4-28.2), for FFDM only, p < 0.0005. The interval cancer rate decreased: 1.26/1000 for DBT + FFDM and 2.76/1000 for FFDM only, p = 0.02. CONCLUSION: DBT + FFDM yielded a statistically significant increase in cancer detection and program sensitivity.

Early Indicators of the Impact of Using AI in Mammography Screening for Breast Cancer.

Background Retrospective studies have suggested that using artificial intelligence (AI) may decrease the workload of radiologists while preserving mammography screening performance. Purpose To compare workload and screening performance for two cohorts of women who underwent screening before and after AI system implementation. Materials and Methods This retrospective study included 50-69-year-old women who underwent biennial mammography screening in the Capital Region of Denmark. Before AI system implementation (October 1, 2020, to November 17, 2021), all screenings involved double reading. For screenings conducted after AI system implementation (November 18, 2021, to October 17, 2022), likely normal screenings (AI examination score ≤5 before May 3, 2022, or ≤7 on or after May 3, 2022) were single read by one of 19 senior full-time breast radiologists. The remaining screenings were read by two radiologists with AI-assisted decision support. Biopsy and surgical outcomes were retrieved between October 1, 2020, and April 15, 2023, ensuring at least 180 days of follow-up. Screening metrics were compared using the χ2 test. Reading workload reduction was measured as saved screening reads. Results In total, 60 751 and 58 246 women were screened before and after AI system implementation, respectively (median age, 58 years [IQR, 54-64 years] for both cohorts), with a median screening interval before AI of 845 days (IQR, 820-878 days) and with AI of 993 days (IQR, 968-1013 days; P < .001). After AI system implementation, the recall rate decreased by 20.5% (3.09% before AI [1875 of 60 751] vs 2.46% with AI [1430 of 58 246]; P < .001), the cancer detection rate increased (0.70% [423 of 60 751] vs 0.82% [480 of 58 246]; P = .01), the false-positive rate decreased (2.39% [1452 of 60 751] vs 1.63% [950 of 58 246]; P < .001), the positive predictive value increased (22.6% [423 of 1875] vs 33.6% [480 of 1430]; P < .001), the rate of small cancers (≤1 cm) increased (36.6% [127 of 347] vs 44.9% [164 of 365]; P = .02), the rate of node-negative cancers was unchanged (76.7% [253 of 330] vs 77.8% [273 of 351]; P = .73), and the rate of invasive cancers decreased (84.9% [359 of 423] vs 79.6% [382 of 480]; P = .04). The reading workload was reduced by 33.5% (38 977 of 116 492 reads). Conclusion In a population-based mammography screening program, using AI reduced the overall workload of breast radiologists while improving screening performance. Published under a CC BY 4.0 license. Supplemental material is available for this article. See also the editorial by Lee and Friedewald in this issue.

Residual Axillary Metastases in Node-Positive Breast Cancer Patients After Neoadjuvant Treatment: A Register-Based Study.

BACKGROUND: Lymph node (LN) metastasis after neoadjuvant chemotherapy (NACT) generally warrants axillary lymph node dissection, which opposes guidelines of upfront surgery in many cases. We investigated the risk of having additional metastases in the axilla when the LNs removed by targeted axillary dissection (TAD) harbored metastases after NACT. We aimed to identify subgroups suitable for de-escalated axillary treatment. METHODS: This register-based study used data from the Danish Breast Cancer Cooperative Group database. Data were analyzed with logistic regression models. The primary outcome was the metastatic burden in non-TAD LNs in patients with positive TAD LNs after NACT. RESULTS: Among 383 patients, < 66.6% positive TAD LNs (adjusted odds ratio [OR] 0.34, 95% confidence interval [CI] 0.17-0.62), only isolated tumor cells (ITCs) [OR 0.11, 95% CI < 0.01-0.82], and breast pathological complete response (pCR) [OR 0.07, 95% CI < 0.01-0.56] were associated with a low risk of having more than three positive non-TAD LNs. In 315 patients with fewer than three positive non-TAD LNs, the proportion of positive TAD LNs (OR 0.45, 95% CI 0.27-0.76 for 33.3-66.6% vs. > 66.6%), size of the TAD LN metastasis (OR 0.14, 95% CI 0.04-0.54 for ITC vs. macrometastasis), tumor size at diagnosis (OR 0.30, 95% CI 0.15-0.64 for 20-49 mm vs. ≥ 50 mm) and breast pCR (OR 0.38, 95% CI 0.15-0.96) were associated with residual LN metastases in the axilla. CONCLUSIONS: Breast pCR or ITC only in TAD LNs can, with reasonable certainty, preclude more than three positive non-TAD LNs. Additionally, patients with only ITCs in the TAD LN had a low risk of having any non-TAD LN metastases after NACT. De-escalated axillary treatment may be considered in both subgroups.

Differences in mammography screening attendance among non-Western immigrants in Denmark, Finland, Iceland and Norway.

Several studies have shown that attendance rates are lower among non-Western immigrants than among natives. As the Nordic countries have quite similar health systems and populations but also differences in the organisation of their organised mammography screening programmes, differences in attendance rates could highlight organisational factors that might increase the attendance rates. Mammography screening is offered free of charge in Denmark and Finland, but not in Iceland and Norway. Contrarily to the other countries, Iceland do not send out pre-booked appointment. The study population included natives and non-Western immigrants aged 50-69 years, who had at least one invitation to the national mammography screening programmes in Denmark (2008-2017), Finland (2001-2017), Iceland (2001-2020) or Norway (2001-2015). Relative risks (RRs) of attendance were estimated and adjusted for age group and calendar period. The study population included 116.033 non-Western immigrants and more than 2 million natives. The attendance rates were significantly lower among non-Western immigrants than among natives, with an adjusted relative risk of 0.81/0.80 in Denmark and Finland, 0.62 in Norway, and 0.40 in Iceland. The lower attendance rates among immigrants in Norway and Iceland did not seem to be due to differences in birth country, immigration age, or educational level, but might be explained by organisational factors. Offering free-of-charge mammography screening in Norway and Iceland and/or including a pre-booked appointment in the invitation letters in Iceland might increase the attendance rate among non-Western immigrants.

Robust cross-vendor mammographic texture models using augmentation-based domain adaptation for long-term breast cancer risk.

Purpose: Risk-stratified breast cancer screening might improve early detection and efficiency without comprising quality. However, modern mammography-based risk models do not ensure adaptation across vendor-domains and rely on cancer precursors, associated with short-term risk, which might limit long-term risk assessment. We report a cross-vendor mammographic texture model for long-term risk. Approach: The texture model was robustly trained using two systematically designed case-control datasets. Textural features, indicative of future breast cancer, were learned by excluding samples with diagnosed/potential malignancies from training. An augmentation-based domain adaption technique, based on flavorization of mammographic views, ensured generalization across vendor-domains. The model was validated in 66,607 consecutively screened Danish women with flavorized Siemens views and 25,706 Dutch women with Hologic-processed views. Performances were evaluated for interval cancers (IC) within 2 years from screening and long-term cancers (LTC) from 2 years after screening. The texture model was combined with established risk factors to flag 10% of women with the highest risk. Results: In Danish women, the texture model achieved an area under the receiver operating characteristic curve (AUC) of 0.71 and 0.65 for ICs and LTCs, respectively. In Dutch women with Hologic-processed views, the AUCs were not different from AUCs in Danish women with flavorized views. The AUC for texture combined with established risk factors increased to 0.68 for LTCs. The 10% of women flagged as high-risk accounted for 25.5% of ICs and 24.8% of LTCs. Conclusions: The texture model robustly estimated long-term breast cancer risk while adapting to an unseen processed vendor-domain and identified a clinically relevant high-risk subgroup.

Assessing Breast Cancer Risk by Combining AI for Lesion Detection and Mammographic Texture.

Background Recent mammography-based risk models can estimate short-term or long-term breast cancer risk, but whether risk assessment may improve by combining these models has not been evaluated. Purpose To determine whether breast cancer risk assessment improves when combining a diagnostic artificial intelligence (AI) system for lesion detection and a mammographic texture model. Materials and Methods This retrospective study included Danish women consecutively screened for breast cancer at mammography from November 2012 to December 2015 who had at least 5 years of follow-up data. Examinations were evaluated for short-term risk using a commercially available diagnostic AI system for lesion detection, which produced a score to indicate the probability of cancer. A mammographic texture model, trained on a separate data set, assessed textures associated with long-term cancer risk. Area under the receiver operating characteristic curve (AUC) analysis was used to evaluate both the individual and combined performance of the AI and texture models for the prediction of future cancers in women with a negative screening mammogram, including those with interval cancers diagnosed within 2 years of screening and long-term cancers diagnosed 2 years or more after screening. AUCs were compared using the DeLong test. Results The Danish screening cohort included 119 650 women (median age, 59 years [IQR, 53-64 years]), of whom 320 developed interval cancers and 1401 developed long-term cancers. The combination model achieved a higher AUC for interval and long-term cancers grouped together than either the diagnostic AI (AUC, 0.73 vs 0.70; P < .001) or the texture risk (AUC, 0.73 vs 0.66; P < .001) models. The 10% of women with the highest combined risk identified by the combination model accounted for 44.1% (141 of 320) of interval cancers and 33.7% (472 of 1401) of long-term cancers. Conclusion Combining a diagnostic AI system and mammographic texture model resulted in improved risk assessment for interval cancers and long-term cancers and enabled identification of women at high risk. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Poynton and Slanetz in this issue.

Nationwide mammography screening participation in Denmark during the COVID-19 pandemic: An observational study.

Background: In most of the world, the mammography screening programmes were paused at the start of the pandemic, whilst mammography screening continued in Denmark. We examined the mammography screening participation during the COVID-19 pandemic in Denmark. Methods: The study population comprised all women aged 50-69 years old invited to participate in mammography screening from 2016 to 2021 in Denmark based on data from the Danish Quality Database for Mammography Screening in combination with population-based registries. Using a generalised linear model, we estimated prevalence ratios (PRs) and 95% confidence intervals (CIs) of mammography screening participation within 90, 180, and 365 d since invitation during the pandemic in comparison with the previous years adjusting for age, year and month of invitation. Results: The study comprised 1,828,791 invitations among 847,766 women. Before the pandemic, 80.2% of invitations resulted in participation in mammography screening within 90 d, 82.7% within 180 d, and 83.1% within 365 d. At the start of the pandemic, the participation in screening within 90 d was reduced to 69.9% for those invited in pre-lockdown and to 76.5% for those invited in first lockdown. Extending the length of follow-up time to 365 d only a minor overall reduction was observed (PR = 0.94; 95% CI: 0.93-0.95 in pre-lockdown and PR = 0.97; 95% CI: 0.96-0.97 in first lockdown). A lower participation was, however, seen among immigrants and among women with a low income. Conclusions: The short-term participation in mammography screening was reduced at the start of the pandemic, whilst only a minor reduction in the overall participation was observed with longer follow-up time, indicating that women postponed screening. Some groups of women, nonetheless, had a lower participation, indicating that the social inequity in screening participation was exacerbated during the pandemic. Funding: The study was funded by the Danish Cancer Society Scientific Committee (grant number R321-A17417) and the Danish regions.

Cutaneous vascular calcifications in patients with chronic kidney disease and calcific uremic arteriolopathy: a cross-sectional study.

INTRODUCTION: Calcific uremic arteriolopathy is a life-threatening cutaneous condition in patients with chronic kidney disease. Often, clinical diagnosis is accompanied by histopathologic evaluations demonstrating vascular calcium deposits. We aimed to investigate the presence of cutaneous calcifications in non-lesional tissue in patients with chronic kidney disease, and the relation to systemic vascular calcification. METHODS: We investigated the presence of cutaneous vascular calcifications in non-lesional skin biopsies from patients with current or previous calcific uremic arteriolopathy and patients with different stages of chronic kidney disease without calcific uremic arteriolopathy, and explored their association with vascular calcification in other vascular beds. Systemic vascular calcification was examined by mammography and lumbar X-ray. RESULTS: Thirty-nine adults were enrolled (current or previous calcific uremic arteriolopathy, n = 9; end-stage chronic kidney disease, n = 12; chronic kidney disease stage 3b-4, n = 12; healthy controls, n = 6). All calcific uremic arteriolopathy patients had end-stage kidney disease. Cutaneous vascular calcifications were not present in any of the non-lesional skin punch biopsies. Breast arterial calcification was demonstrated in patients with calcific uremic arteriolopathy (75%) and chronic kidney disease (end-stage 67% and stage 3b-4 25%, respectively), but in none of the controls. All chronic kidney disease patients had systemic calcification on lumbar X-ray (median score 21, 22, and 15 in patients with calcific uremic arteriolopathy, end-stage kidney disease and chronic kidney disease stage 3b-4). The serum calcification propensity was significantly different between groups. DISCUSSION: Despite a high burden of systemic vascular calcification, cutaneous calcium deposits in non-lesional tissue could not be demonstrated histopathologically in patients with chronic kidney disease (with or without current or previous calcific uremic arteriolopathy). Further studies to determine whether these findings are representative or attributed to other factors are warranted.

Comparing Methods for Targeted Axillary Dissection in Breast Cancer Patients: A Nationwide, Retrospective Study.

BACKGROUND: Several techniques exist for performing targeted axillary dissection (TAD) after neoadjuvant chemotherapy with the removal of the sentinel node and a marked metastatic lymph node (LN). Two-step methods include coil-marking of the metastatic LN at diagnosis and re-marking with an intraoperatively identifiable marker before surgery. Because nondetection of the marked lymph node (MLN) warrants axillary clearance and many patients achieve axillary pathological complete response (ax-pCR), the success of TAD is crucial. We compare various two-step TAD methods in a Danish national cohort. METHODS: We included patients who received two-step TAD between January 1, 2016 and August 31, 2021. Patients were identified from the Danish Breast Cancer Group database and cross-checked with locally accessible lists. Data were extracted from the patient's medical files. RESULTS: We included 543 patients. In 79.4%, preoperative, ultrasound-guided re-marking was possible. Nonidentification of the coil-marked LN was more likely in patients with ax-pCR. The second markers used were hook-wire, iodine seeds, or ink marking on the axillary skin. Of patients with successful secondary marking, the MLN identification rate (IR) was 91%, and the sentinel node (SN) IR was 95%. Marking with iodine seeds was significantly more successful than ink marking with an odds ratio of 5.34 (95% confidence interval 1.62-17.60). The success rate of the complete TAD with the removal of MLN and SN was 82.3%. CONCLUSIONS: With two-step TAD, nonidentification of the coiled LN before surgery is frequent, especially in patients with ax-pCR. Despite successful remarking, the IR of the MLN at surgery is inferior to one-step TAD.

A population-based cohort study on changes in breast, lung and colorectal cancer incidence and mortality among non-Western immigrant women.

BACKGROUND: Cancer risk varies geographically, and migrants are influenced by different risk factors before, during and after migration. Increased migration from non-Western countries to the Nordic countries calls for a better understanding of the migrants' cancer risk and the change in risk patterns over time. The aim of this study was to compare the incidence and mortality of breast, colorectal and lung cancer between non-Western immigrant and the native female population in Denmark, Finland, Iceland, and Norway. MATERIAL AND METHODS: Data from national registries were processed and pre-analysed in each country. Multivariate Poisson regression models were used to model the relative differences in incidence and mortality as rate ratios (RR). The country-specific estimates and summary statistics were pooled together using a random effects model. RESULTS: Non-Western immigrant women had significantly lower breast (RR 0.71, 0.65-0.78), colorectal (RR 0.72, 0.57-0.92) and lung (RR 0.55, 0.42-0.72) cancer incidence rates than native women, and the risk of these cancers among immigrant women increased with duration of residence. Differences were parallel in breast, colorectal and lung cancer mortality (RR 0.64, 0.55-0.74; RR 0.66, 0.48-0.92; RR 0.51, 0.34-0.79). Among immigrant women, higher education increased the risk for breast cancer and decreased it for lung cancer. CONCLUSION: The results significantly complement and add to the previous findings of cancer burden and cancer burden transition among migrants and provide evidence of a prolonged cancer risk advantage among non-Western immigrant women. However, the findings show an increasing risk of lifestyle-related cancers with increasing duration of residence in the host country. Further studies are needed to discover underlying reasons for this phenomenon.

Standalone AI for Breast Cancer Detection at Screening Digital Mammography and Digital Breast Tomosynthesis: A Systematic Review and Meta-Analysis.

Background There is considerable interest in the potential use of artificial intelligence (AI) systems in mammographic screening. However, it is essential to critically evaluate the performance of AI before it can become a modality used for independent mammographic interpretation. Purpose To evaluate the reported standalone performances of AI for interpretation of digital mammography and digital breast tomosynthesis (DBT). Materials and Methods A systematic search was conducted in PubMed, Google Scholar, Embase (Ovid), and Web of Science databases for studies published from January 2017 to June 2022. Sensitivity, specificity, and area under the receiver operating characteristic curve (AUC) values were reviewed. Study quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies 2 and Comparative (QUADAS-2 and QUADAS-C, respectively). A random effects meta-analysis and meta-regression analysis were performed for overall studies and for different study types (reader studies vs historic cohort studies) and imaging techniques (digital mammography vs DBT). Results In total, 16 studies that include 1 108 328 examinations in 497 091 women were analyzed (six reader studies, seven historic cohort studies on digital mammography, and four studies on DBT). Pooled AUCs were significantly higher for standalone AI than radiologists in the six reader studies on digital mammography (0.87 vs 0.81, P = .002), but not for historic cohort studies (0.89 vs 0.96, P = .152). Four studies on DBT showed significantly higher AUCs in AI compared with radiologists (0.90 vs 0.79, P < .001). Higher sensitivity and lower specificity were seen for standalone AI compared with radiologists. Conclusion Standalone AI for screening digital mammography performed as well as or better than radiologists. Compared with digital mammography, there is an insufficient number of studies to assess the performance of AI systems in the interpretation of DBT screening examinations. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Scaranelo in this issue.

Targeted Axillary Dissection with 125I Seed Placement Before Neoadjuvant Chemotherapy in a Danish Multicenter Cohort.

BACKGROUND: Targeted axillary dissection (TAD), with marking of the metastatic lymph node before neoadjuvant chemotherapy (NACT), is increasingly used for breast cancer axillary staging. In the case of axillary pathological complete response (ax-pCR), axillary lymph node clearance can be omitted. Several marking methods exist, most using re-marking before surgery. Feasibility, learning curve, and identification rate (IR) vary. Marking with 125I seed before NACT makes re-marking at surgery redundant, possibly increasing feasibility and IR. Here, TAD with 125I seed placed before NACT is evaluated in a Danish multicenter cohort. METHODS: Patients staged with 125I TAD in Denmark between 1 January 2016 and 31 August 2021 were included. Patients were identified in radioactivity-emitting implant registries at the radiology departments and from the Danish Breast Cancer Group database. Data were extracted from patients' medical records. Information on patient/tumor characteristics, 125I seed activity, marking period, TAD success, number of sentinel nodes (SNs), the histopathological status of excised nodes, and whether the marked lymph node (MLN) was an SN were registered. RESULTS: 142 patients were included. The IR of the MLN was 99.3%, and the IR of the SLNB was 91.5%. TAD success was 91.5%. Minor challenges in marking or removal of the MLN were noted in three patients. In 72.3% of the patients, the MLN was a sentinel node. Overall, 40.8% had axillary pCR. CONCLUSION: TAD with 125I seed marking before NACT is feasible without re-marking at surgery and with only minor surgical challenges. The IR is high. Staging with TAD spares 41% of breast cancer patients an axillary dissection.

Impact of COVID-19 pandemic on breast and cervical cancer screening in Denmark: A register-based study.

Background: Denmark was one of the few countries where it was politically decided to continue cancer screening during the COVID-19 pandemic. We assessed the actual population uptake of mammography and cervical screening during this period. Methods: The first COVID-19 lockdown in Denmark was announced on 11 March 2020. To investigate possible changes in cancer screening activity due to the COVID-19 pandemic, we analysed data from the beginning of 2017 until the end of 2021. A time series analysis was carried out to discover possible trends and outliers in the screening activities in the period 2017-2021. Data on mammography screening and cervical screening were retrieved from governmental pandemic-specific monitoring of health care activities. Results: A brief drop was seen in screening activity right after the first COVID-19 lockdown, but the activity quickly returned to its previous level. A short-term deficit of 43% [CI -49 to -37] was found for mammography screening. A short-term deficit of 62% [CI -65 to -58] was found for cervical screening. Furthermore, a slight, statistically significant downward trend in cervical screening from 2018 to 2021 was probably unrelated to the pandemic. Other changes, for example, a marked drop in mammography screening towards the end of 2021, also seem unrelated to the pandemic. Conclusions: Denmark continued cancer screening during the pandemic, but following the first lockdown a temporary drop was seen in breast and cervical screening activity. Funding: Region Zealand (R22-A597).

Breast Cancer Screening Among Women With Intellectual Disability in Denmark.

Importance: Breast cancer-specific mortality is increased among women with intellectual disability (ID), and knowledge about participation in breast cancer screening in this group is needed. Objective: To examine participation in the Danish national breast cancer screening program among women with ID compared with women without ID. Design, Setting, and Participants: This dynamic population-based cohort study assessed participation in the Danish national breast cancer screening program initiated in 2007, targeting women aged 50 to 69 years with a screening interval of 2 years. In all, 6357 women with ID born between 1941 and 1967 and eligible for the screening program were identified in national registers. Women entered the study between January 1, 2007, and December 31, 2017. Subsequently, 273 women were excluded due to a history of carcinoma in situ or breast cancer, and 489 due to registration errors in registers. Each woman was individually age-matched with 10 women without ID (reference group). All women were followed up until March 31, 2021, or censoring (due to death, carcinoma in situ, or breast cancer). Data were analyzed from December 1, 2021, to June 31, 2022. Exposures: Intellectual disability was defined as being registered with an ID diagnosis or a diagnosis most likely leading to ID or residing at an institution for persons with ID. Main Outcomes and Measures: Participation in breast cancer screening (fully, partly, and never). Results: A total of 5595 women with ID and 49 423 age-matched women in the reference group were included in the analysis. Of these, 2747 women with ID (49%) and 24 723 in the reference group (50%) were 50 years of age at study entry; for those older than 50 years, the median age was 51 years (IQR, 50-58 years) in both groups. In all, 1425 women with ID (25%) were fully screened according to guidelines for the Danish breast cancer screening program compared with 30 480 women in the reference group (62%). Women with ID had nearly 5 times higher odds of never being screened compared with the reference group (odds ratio, 4.90 [95% CI, 4.60-5.22]). In all, 2498 women with ID (45%) and 6573 in the reference group (13%) were never screened. The proportion of never-screened women increased with severity of ID, from 834 of 2287 (36%) among women with mild ID to 173 of 212 (82%) among women with profound ID. Conclusions and Relevance: The findings of this cohort study suggest that women with ID are markedly less likely to participate in breast cancer screening compared with women without ID. These findings further suggest a need for tailored guidelines and approaches for breast cancer screening in this group of women.

Breast density and risk of breast cancer.

Early studies reported a 4- to 6-fold risk of breast cancer between women with extremely dense and fatty breasts. As most early studies were case-control studies, we took advantage of a population-based screening program to study density and breast cancer incidence in a cohort design. In the Capital Region, Denmark, women aged 50 to 69 are invited to screening biennially. Women screened November 2012 to December 2017 were included, and classified by BI-RADS density code, version 4, at first screen after recruitment. Women were followed up for incident breast cancer, including ductal carcinoma in situ (DCIS), to 2020 in nationwide pathology data. Rate ratios (RRs) and 95% confidence intervals (CI) were compared across density groups using Poisson-regression. We included 189 609 women; 1 067 282 person-years; and 4110 incident breast cancers/DCIS. Thirty-three percent of women had BI-RADS density code 1; 38% code 2; 24% code 3; 4.7% code 4; and missing 0.3%. Using women with BI-RADS density code 1 as baseline; women with code 2 had RR 1.69 (95% CI 1.56-1.84); women with code 3, RR 2.06 (95% CI 1.89-2.25); and women with code 4, RR 2.37 (95% CI 1.05-2.74). Results differed between observations accumulated during screening and above screening age. Our results indicated less difference in breast cancer risk across level of breast density than normally stated. Translated into absolute risk of breast cancer after age 50, we found a 6.2% risk for the one-third of women with lowest density, and 14.7% for the 5% of women with highest density.

An Artificial Intelligence-based Mammography Screening Protocol for Breast Cancer: Outcome and Radiologist Workload.

Background Developments in artificial intelligence (AI) systems to assist radiologists in reading mammograms could improve breast cancer screening efficiency. Purpose To investigate whether an AI system could detect normal, moderate-risk, and suspicious mammograms in a screening sample to safely reduce radiologist workload and evaluate across Breast Imaging Reporting and Data System (BI-RADS) densities. Materials and Methods This retrospective simulation study analyzed mammographic examination data consecutively collected from January 2014 to December 2015 in the Danish Capital Region breast cancer screening program. All mammograms were scored from 0 to 10, representing the risk of malignancy, using an AI tool. During simulation, normal mammograms (score < 5) would be excluded from radiologist reading and suspicious mammograms (score > recall threshold [RT]) would be recalled. Two radiologists read the remaining mammograms. The RT was fitted using another independent cohort (same institution) by matching to the radiologist sensitivity. This protocol was further applied to each BI-RADS density. Screening outcomes were measured using the sensitivity, specificity, workload, and false-positive rate. The AI-based screening was tested for noninferiority sensitivity compared with radiologist screening using the Farrington-Manning test. Specificities were compared using the McNemar test. Results The study sample comprised 114 421 screenings for breast cancer in 114 421 women, resulting in 791 screen-detected, 327 interval, and 1473 long-term cancers and 2107 false-positive screenings. The mean age of the women was 59 years ± 6 (SD). The AI-based screening sensitivity was 69.7% (779 of 1118; 95% CI: 66.9, 72.4) and was noninferior (P = .02) to the radiologist screening sensitivity of 70.8% (791 of 1118; 95% CI: 68.0, 73.5). The AI-based screening specificity was 98.6% (111 725 of 113 303; 95% CI: 98.5, 98.7), which was higher (P < .001) than the radiologist specificity of 98.1% (111 196 of 113 303; 95% CI: 98.1, 98.2). The radiologist workload was reduced by 62.6% (71 585 of 114 421), and 25.1% (529 of 2107) of false-positive screenings were avoided. Screening results were consistent across BI-RADS densities, although not significantly so for sensitivity. Conclusion Artificial intelligence (AI)-based screening could detect normal, moderate-risk, and suspicious mammograms in a breast cancer screening program, which may reduce the radiologist workload. AI-based screening performed consistently across breast densities. © RSNA, 2022 Online supplemental material is available for this article.