Screen-detected Cancers Research Articles

Overdiagnosis for screen-detected prostate cancer incorporating patient comorbidities

Abstract Background Evidence regarding the likelihood of overdiagnosis in prostate cancer (CaP) screening with PSA are mainly based on clinical trials, which include younger population with fewer comorbidities than those receiving the test in clinical practice. We aimed to assess the likelihood of overdiagnosis and associated variables using real-world data. Methods Retrospective cohort of men >40 years with PCa, who had been diagnosed being asymptomatic and after a positive PSA test in the previous 12 months in two hospitals (2004-2022). The probability of overdiagnosis was estimated considering the life expectancy of the Spanish male in the year 2022 and the Charlson Comorbidity Index (lead time 10 years). PSA values and Gleason score were included as independent variables. Results Of the 2,331 patients in the cohort, 1,070 (46%) met the inclusion criteria for this analysis. The median follow-up time was 5.7 years (IQR 3.2-8.6). The median age was 71 years (IQR 65-78) and 37% had more than one comorbidity. At diagnosis, the median life expectancy was 12 years (IQR 4-18) and the probability of overdiagnosis was 30.8% (IQR 17.6-52.4). Patients with PSA levels >10 mg/dl tended to be older and with more comorbidities than those with PSA levels 4-10 mg/dl, and thus, with shorter life expectancy. The median probability of overdiagnosis was higher in patients with PSA levels >10 mg/dl (41.4%, IQR 21.5-73.9) than in those with PSA levels 4-10 mg/dl (20.1%, IQR 12.8-30.4), p < 0.001. Correspondingly, patients with Gleason score ≥8 were more likely to be overdiagnosed (median 42.6%, IQR 23.6-68.6) than those with Gleason score ≤6 (median 20.1%, IQR 12.8-30.4) (p < 0.001). Conclusions In clinical practice, older patients with comorbidities showed high PSA levels and Gleason score ≥8, presenting low life expectancy at diagnosis and, therefore, high probability of overdiagnosis. This highlights the importance of considering the patient’s comorbidities when ordering a new PSA test. Key messages • A detailed assessment of the prevalence of comorbidities among CaP patients in real-life settings has significant implications for patient management. • The decision to make an early diagnosis should be based on individual life expectancy, where comorbidity is at least as important as age.

Association between mammographic screening history and stage at diagnosis among women with screen-detected breast cancer.

145 Background: Although screening mammography is an effective means of detecting breast cancer at earlier stages, some women are still diagnosed with later stage disease despite screening mammography. We hypothesized that screening history prior to diagnosis may impact stage at diagnosis and breast cancer mortality among women with screen-detected breast cancer. Methods: Retrospective cohort study of women aged 70+ in the SEER-Medicare database, diagnosed with ER+/HER2- breast cancer from 2010-2017, and enrolled in fee-for service Medicare Parts A and B from 5-years prior to diagnosis through 1 year after. We used validated claims-based algorithms to identify cancers that were detected by screening mammogram. We quantified 5-year screening history by number of prior screens. Stage at diagnosis was dichotomized into very early (T1N0) vs. later stage (T2+ or N+) disease. Multivariable logistic regression was used to assess the association between screening history and stage at diagnosis and Cox proportional hazards used to examine breast cancer mortality. Models were adjusted for demographic and clinical covariates associated with later stage disease in bivariate analyses. Results: We included 13,029 women with screen-detected breast cancer; 3,813 (29.27%) women had later stage disease at diagnosis, and 10,095 (77.48%) had at least one prior negative screening mammogram within the past five years. During this time, 2,359 (18.11%) women had only one prior mammogram, 3,132 (24.03%) had two, and 4,604 (35.34%) had three or four. Having at least one prior mammogram was associated with 56% lower odds of being diagnosed with later stage disease (OR: 0.44, 95% CI=0.40-0.48). Sociodemographic factors associated with increased odds of later stage disease included living in an area with greater poverty (20-100% vs. 0-5% of residents, OR: 1.19, 1.00-1.40), non-Hispanic Black race (OR: 1.18, 1.00-1.38), and Medicare/Medicaid dual eligibility (OR: 1.20, 1.06-1.36). Factors associated with later stage disease included living in an area with a more people with a high-school education (30-40% vs. 0-30% of residents, OR: 0.87, 0.77-0.97). At total of 696 deaths from breast cancer were observed, including 273 deaths among 2,935 women with no prior screening (9.3%) and 423 deaths among 10,097 women who had undergone screening within the past five years (4.2%, P < 0.001). Receiving at least one negative screening prior to diagnosis was associated with decreased breast cancer-specific Mortality in adjusted analysis (HR: 0.48, 0.40-0.57). Conclusions: The use of prior routine screening mammography was associated with lower risk of being diagnosed with later stage disease and dying from breast cancer in elderly women with screen-detected breast cancer. Future research is warranted regarding the impact of routine vs. sporadic screening on potential morbidity and mortality in this age group.

Artificial Intelligence Algorithm for Subclinical Breast Cancer Detection

Early breast cancer detection is associated with lower morbidity and mortality. To examine whether a commercial artificial intelligence (AI) algorithm for breast cancer detection could estimate the development of future cancer. This retrospective cohort study of 116 495 women aged 50 to 69 years with no prior history of breast cancer before they underwent at least 3 consecutive biennial screening examinations used scores from an AI algorithm (INSIGHT MMG, version 1.1.7.2; Lunit Inc; used September 28, 2022, to April 5, 2023) for breast cancer detection and screening data from multiple, consecutive rounds of mammography performed from September 13, 2004, to December 21, 2018, at 9 breast centers in Norway. The statistical analyses were performed from September 2023 to August 2024. Artificial intelligence algorithm score indicating suspicion for the presence of breast cancer. The algorithm provided a continuous cancer detection score for each examination ranging from 0 to 100, with increasing values indicating a higher likelihood of cancer being present on the current mammogram. Maximum AI algorithm score for cancer detection and absolute difference in score among breasts of women developing screening-detected cancer, women with interval cancer, and women who screened negative. The mean (SD) age at the first study round was 58.5 (4.5) years for 1265 women with screening-detected cancer in the third round, 57.4 (4.6) years for 342 women with interval cancer after 3 negative screening rounds, and 56.4 (4.9) years for 116 495 women without breast cancer all 3 screening rounds. The mean (SD) absolute differences in AI scores among breasts of women developing screening-detected cancer were 21.3 (28.1) at the first study round, 30.7 (32.5) at the second study round, and 79.0 (28.9) at the third study round. The mean (SD) differences prior to interval cancer were 19.7 (27.0) at the first study round, 21.0 (27.7) at the second study round, and 34.0 (33.6) at the third study round. The mean (SD) differences among women who did not develop breast cancer were 9.9 (17.5) at the first study round, 9.6 (17.4) at the second study round, and 9.3 (17.3) at the third study round. Areas under the receiver operating characteristic curve for the absolute difference were 0.63 (95% CI, 0.61-0.65) at the first study round, 0.72 (95% CI, 0.71-0.74) at the second study round, and 0.96 (95% CI, 0.95-0.96) at the third study round for screening-detected cancer and 0.64 (95% CI, 0.61-0.67) at the first study round, 0.65 (95% CI, 0.62-0.68) at the second study round, and 0.77 (95% CI, 0.74-0.79) at the third study round for interval cancers. In this retrospective cohort study of women undergoing screening mammography, mean absolute AI scores were higher for breasts developing vs not developing cancer 4 to 6 years before their eventual detection. These findings suggest that commercial AI algorithms developed for breast cancer detection may identify women at high risk of a future breast cancer, offering a pathway for personalized screening approaches that can lead to earlier cancer diagnosis.

Large cell carcinoma of the lung: LDCT features and survival in screen-detected cases.

To investigate the early radiological features and survival of Large Cell Carcinoma (LCC) cases diagnosed in low-dose computed tomography (LDCT) screening trials. Two radiologists jointly reviewed the radiological features of screen-detected LCCs observed in NLST, ITALUNG, and LUSI trials between 2002 and 2016, comprising a total of 29,744 subjects who underwent 3-5 annual screening LDCT examinations. Survival or causes of death were established according to the mortality registries extending more than 12years since randomization. LCC was diagnosed in 30 (4%) of 750 subjects with screen-detected lung cancer (LC), including 15 prevalent and 15 incident cases. Three additional LCCs occurred as interval cancers during the screening period. LDCT images were available for 29 cases of screen-detected LCCs, and 28 showed a single, peripheral, and well-defined solid nodule or mass with regularly smooth (39%), lobulated (43%), or spiculated (18%) margins. One case presented as hilar mass. In 9 incident LCCs, smaller solid nodules were identified in prior LDCT examinations, allowing us to calculate a mean Volume Doubling Time (VDT) of 98.7±47.8 days. The overall five-year survival rate was 50%, with a significant (p=0.0001) difference between stages I-II (75% alive) and stages III-IV (10% alive). LCC is a fast-growing neoplasm that can escape detection by annual LDCT screening. LCC typically presents as a single solid peripheral nodule or mass, often with lobulated margins, and exhibits a short VDT. The 5-year survival reflects the stage at diagnosis.

P4.07G.01 Incidence of and Outcomes of Second Primary Lung Cancer after Resection for Screen-Detected Lung Cancer

P4.07G.01 Incidence of and Outcomes of Second Primary Lung Cancer after Resection for Screen-Detected Lung Cancer

MA04.04 Treatment Patterns and Survival of Screen-Detected Lung Cancer in the Real World Versus the National Lung Screening Trial

MA04.04 Treatment Patterns and Survival of Screen-Detected Lung Cancer in the Real World Versus the National Lung Screening Trial

Diagnostic Accuracy of Screening Contrast-enhanced Mammography for Women with Extremely Dense Breasts at Increased Risk of Breast Cancer.

Background Mammogram interpretation is challenging in female patients with extremely dense breasts (Breast Imaging Reporting and Data System [BI-RADS] category D), who have a higher breast cancer risk. Contrast-enhanced mammography (CEM) has recently emerged as a potential alternative; however, data regarding CEM utility in this subpopulation are limited. Purpose To evaluate the diagnostic performance of CEM for breast cancer screening in female patients with extremely dense breasts. Materials and Methods This retrospective single-institution study included consecutive CEM examinations in asymptomatic female patients with extremely dense breasts performed from December 2012 to March 2022. From CEM examinations, low-energy (LE) images were the equivalent of a two-dimensional full-field digital mammogram. Recombined images highlighting areas of contrast enhancement were constructed using a postprocessing algorithm. The sensitivity and specificity of LE images and CEM images (ie, including both LE and recombined images) were calculated and compared using the McNemar test. Results This study included 1299 screening CEM examinations (609 female patients; mean age, 50 years ± 9 [SD]). Sixteen screen-detected cancers were diagnosed, and two interval cancers occured. Five cancers were depicted at LE imaging and an additional 11 cancers were depicted at CEM (incremental cancer detection rate, 8.7 cancers per 1000 examinations). CEM sensitivity was 88.9% (16 of 18; 95% CI: 65.3, 98.6), which was higher than the LE examination sensitivity of 27.8% (five of 18; 95% CI: 9.7, 53.5) (P = .003). However, there was decreased CEM specificity (88.9%; 1108 of 1246; 95% CI: 87.0, 90.6) compared with LE imaging (specificity, 96.2%; 1199 of 1246; 95% CI: 95.0, 97.2) (P < .001). Compared with specificity at baseline, CEM specificity at follow-up improved to 90.7% (705 of 777; 95% CI: 88.5, 92.7; P = .01). Conclusion Compared with LE imaging, CEM showed higher sensitivity but lower specificity in female patients with extremely dense breasts, although specificity improved at follow-up. © RSNA, 2024 See also the editorial by Lobbes in this issue.

Clinicopathological and molecular differences between stage IV screen-detected and interval colorectal cancers in the Flemish screening program.

Interval cancer (IC) is an important quality indicator in colorectal cancer (CRC) screening. Previously, we found that fecal immunochemical test (FIT) ICs are more common in women, older age, right-sided tumors, and advanced stage. Here, we extended our existing stage IV patient cohort with clinicopathological and molecular characteristics, to identify factors associated with FIT-IC. Logistic regression models were fit to identify variables associated with the odds of having a stage IV FIT-IC. Multivariate models were corrected for gender, age, and location. A total of 292 screen-detected (SD) CRCs and 215 FIT-IC CRCs were included. FIT-IC CRC had 5 fold higher odds to be a neuroendocrine (NET) tumor and 2.5 fold higher odds to have lymphovascular invasion. Interestingly, some variables lost significance upon accounting for location. Thus, tumor location is a critical covariate that should always be included when evaluating factors related to FIT-IC. We identified NETs and lymphovascular invasion as factors associated with increased odds of having a stage IV FIT-IC. Moreover, we highlight the importance of tumor location as a covariate in evaluating FIT-IC related factors. More research across all stages is needed to clarify how these insights might help to optimize the Flemish CRC screening program.

Risk of Recurrence in Screen-Detected vs Non–Screen-Detected Colorectal Cancer Patients

Background & aimPatients with screen-detected colorectal cancer (CRC) have a better stage-specific overall survival than non-screen detected CRC. Currently, it is unknown if recurrence rates differ between screen- and non-screen detected CRCs, and whether this could explain the observed difference in overall survival. Therefore, we aimed to assess the disease-free survival (DFS) rates in screen-detected and non-screen detected CRCs and if recurrence affects overall survival. MethodsDutch CRC (stage I-III) patients, diagnosed by screening or not in the first six months of 2015, were included from the Netherlands Cancer Registry. DFS and survival data were retrieved and analyzed by Kaplan Meier method. The association between mode of detection and recurrence and overall survivall was evaluated with a Cox-regression model. ResultsA total of 3725 CRC patients were included, 2073 (55.7%) non-screen-detected and 1652 (44.3%) screen-detected CRCs. Three-year DFS was significantly higher in screen-detected CRC compared to non-screen-detected CRC (87.8% versus 77.2.%, p<0.001). Stage-specific DFS rates for screen-detected vs. non-screen-detected CRC were 94.7% vs. 92.3% for stage I (p=0.45), 84.3% vs. 81.4% for stage II (p=0.17) and 77.9% vs 66.7% for stage III (p<0.001), respectively. Detection by screening was independently associated with a lower risk of recurrence (HR 0.67; CI 0.55 – 0.81, p<0.001) when adjusted for age, gender, tumor location, stage and treatment. Recurrence independently predicted overall survival (HR 15.90; CI 13.28-19.04, p<0.001). ConclusionDisease-free survival was significantly better in screen-detected compared to non-screen-detected CRCs independent of age, gender, tumor location, stage and treatment, and was associated with an overall survival benefit.

Clinical Significance of Combined Density and Deep-Learning-Based Texture Analysis for Stratifying the Risk of Short-Term and Long-Term Breast Cancer in Screening.

Assessing a woman's risk of breast cancer is important for personalized screening. Mammographic density is a strong risk factor for breast cancer, but parenchymal texture patterns offer additional information which cannot be captured by density. We aimed to combine BI-RADS density score 4th Edition and a deep-learning-based texture score to stratify women in screening and compare rates among the combinations. This retrospective study cohort study included 216,564 women from a Danish populations-based screening program. Baseline mammograms were evaluated using BI-RADS density scores (1-4) and a deep-learning texture risk model, with scores categorized into four quartiles (1-4). The incidence rate ratio (IRR) for screen-detected, interval, and long-term cancer were adjusted for age, year of screening and screening clinic. Compared with subgroup B1-T1, the highest IRR for screen-detected cancer were within the T4 category (3.44 (95% CI: 2.43-4.82)-4.57 (95% CI: 3.66-5.76)). IRR for interval cancer was highest in the BI-RADS 4 category (95% CI: 5.36 (1.77-13.45)-16.94 (95% CI: 9.93-30.15)). IRR for long-term cancer increased both with increasing BI-RADS and increasing texture reaching 5.15 (4.31-6.16) for the combination of B4-T4 compared with B1-T1. Deep-learning-based texture analysis combined with BI-RADS density categories can reveal subgroups with increased rates beyond what density alone can ascertain, suggesting the potential of combining texture and density to improve risk stratification in breast cancer screening.

ASO Visual Abstract: Contrast-Enhanced Mammography inLocal Stagingof Screen-Detected Breast Cancer.

ASO Visual Abstract: Contrast-Enhanced Mammography inLocal Stagingof Screen-Detected Breast Cancer.

Initial interpretation scores of screening mammograms and cancer detection in BreastScreen Norway

PurposeTo explore the association between radiologists’ interpretation scores, early performance measures and cumulative reading volume in mammographic screening. MethodWe analyzed 1,689,731 screening examinations (3,379,462 breasts) from BreastScreen Norway 2012–2020, all breasts scored 1–5 by two independent radiologists. Score 1 was considered negative/benign and score ≥2 positive in this scoring system. We performed descriptive analyses of recall, screen-detected cancer, positive predictive value (PPV) 1, mammographic features and histopathological characteristics by breast-based interpretation scores, and cumulative reading volume by examination-based interpretation scores. ResultsCounting breasts and not women, 3.9 % (132,570/3,379,462) had a score of ≥2 by one or both radiologists. Of these, 84.8 % (112,440/132,570) were given a maximum score 2. Total recall rate was 1.6 % (53,735/3,379,462), 69.3 % (37,220/53,735) given maximum score 2. Among the 0.3 % (9733/3,379,462) diagnosed with screen-detected cancer, 34.6 % (3369/9733) had maximum score 3. The percentages of recall, screen-detected cancer and PPV-1 increased by increasing the sum of scores assigned by two radiologists (p < 0.001 for trend). Higher proportions of masses were observed among recalls and screen-detected cancers with low scores, and higher proportions of spiculated masses were observed for high scores (p < 0.001). Proportions of invasive carcinoma, histological grade 3 and lymph node positive tumors were higher for high versus low scores (p < 0.001). The proportion of examinations scored 1 increased by cumulative reading volume. ConclusionsWe observed higher rates of recall and screen-detected cancer and less favorable histopathological tumor characteristics for high versus low interpretation scores. However, a considerable number of recalls and screen-detected cancers had low interpretation scores.

Comparison of radiological and histopathological features between interval and screen-detected breast cancers: a retrospective case–control study

PurposeTo compare tumor features of interval breast cancers (IBCs) with those of screen-detected breast cancers (SDBCs), focusing on true interval breast cancers (TIBCs).MethodsA retrospective case–control study within the population-based Rimini breast screening program was performed. Between 2018 and 2023, 115 IBCs and 229 SDBCs were compared (matched 1:2) with multivariate analysis.Results47% of IBC were TIBCs. In IBCs and TIBCs, the following features were more frequent than in SDBCs: triple-negative phenotype (16.5, 22.2, 2.6% respectively), high histological grading (49.6, 53.7, 30.1%), multifocality (39.1, 35.2, 15.7%), lymph node involvement (33, 27.8, 8.7%), and high breast density (60.9, 61.1, 17%) with a p value ≤ 0.05 for each of them.ConclusionIn this cohort study, IBCs, especially TIBCs, were proved to be more aggressive than SDBCs in relation to invasiveness, advanced stage, histopathological features, and molecular phenotype (with the highest rates of high histological grading, triple-negative phenotype, and invasive lobular cancer).

Examining breast cancer screening recommendations in Canada: The projected resource impact of screening among women aged 40-49.

To quantify the resource use of revising breast cancer screening guidelines to include average-risk women aged 40-49 years across Canada from 2024 to 2043 using a validated microsimulation model. OncoSim-Breast microsimulation platform was used to simulate the entire Canadian population in 2015-2051. We compared resource use between current screening guidelines (biennial screening ages 50-74) and alternate screening scenarios, which included annual and biennial screening for ages 40-49 and ages 45-49, followed by biennial screening ages 50-74. We estimated absolute and relative differences in number of screens, abnormal screening recalls without cancer, total and negative biopsies, screen-detected cancers, stage of diagnosis, and breast cancer deaths averted. Compared with current guidelines in Canada, the most intensive screening scenario (annual screening ages 40-49) would result in 13.3% increases in the number of screens and abnormal screening recalls without cancer whereas the least intensive scenario (biennial screening ages 45-49) would result in a 3.4% increase in number of screens and 3.8% increase in number of abnormal screening recalls without cancer. More intensive screening would be associated with fewer stage II, III, and IV diagnoses, and more breast cancer deaths averted. Revising breast cancer screening in Canada to include average-risk women aged 40-49 would detect cancers earlier leading to fewer breast cancer deaths. To realize this potential clinical benefit, a considerable increase in screening resources would be required in terms of number of screens and screen follow-ups. Further economic analyses are required to fully understand cost and budget implications.

ASO Author Reflections: Contrast-Enhanced Mammography in Local Staging of Screen-Detected Breast Cancer.

ASO Author Reflections: Contrast-Enhanced Mammography in Local Staging of Screen-Detected Breast Cancer.

Prostate Cancer Screening in Young Men.

Background: Prostate cancer (PCa) screening strategies are being developed and evaluated in several countries. However, most of the evidence regarding PCa screening has been generated in study populations aged 50 and older. Aims: This study summarizes findings of a screening trial in younger men and discuss those findings in the context of other screening trials. Methods: Non-systematic review. Results: Screening of 45-year-old men resulted in a low PCa detection rate. Nonetheless, almost 70% of screen-detected PCa at this age was clinically significant. In young men ISUP GG 1 screen-detected cancers warrant rigorous follow-up. A baseline, midlife prostate-specific antigen (PSA) value at age 45 may safely exclude the vast majority of men from further screening investigations for at least 5 years. At age 45, a confirmatory PSA value reduces the number of subsequent tests almost by half. Sequential magnetic resonance imaging (MRI) as a reflex test subsequent to an elevated PSA ≥ 3 ng/mL needs further investigation in young men. Conclusions: Screening in young men needs to be carefully investigated in order to avoid overscreening and overdiagnosis.

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

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. 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. 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. DBT + FFDM yielded a statistically significant increase in cancer detection and program sensitivity.

Contrast-Enhanced Mammography in Local Staging of Screen-Detected Breast Cancer.

BreastScreen Australia, the population mammographic screening program for breast cancer, uses two-view digital screening mammography ± ultrasound followed by percutaneous biopsy to detect breast cancer. Secondary breast imaging for further local staging, not performed at BreastScreen, may identify additional clinically significant breast lesions. Staging options include further mammography, bilateral ultrasound, and/or contrast-based imaging (CBI) [magnetic resonance imaging (MRI) or contrast-enhanced mammography (CEM)]. CBI for local staging of screen-detected cancer was introduced at an academic hospital breast service in Melbourne, VIC, Australia. We report findings for otherwise occult disease and resulting treatment changes. Patients staged using CEM between November 2018 and April 2022 were identified from hospital records. Data were extracted from radiology, pathology, and breast unit databases. CEM-detected abnormalities were documented as true positive (TP) for invasive cancer or ductal carcinoma in situ (DCIS), or otherwise false positive (FP). The impact on surgical decisions was assessed. Of 202 patients aged 44-84 years, 60 (30%) had 74 additional findings [34 (46%) TP, 40 (54%) FP]. These were malignant in 29/202 (14%) patients (79% invasive cancers, 21% DCIS). CEM resulted in surgical changes in 43/202 (21%) patients: wider resection (24/43), conversion to mastectomy (6/43), contralateral breast surgery (6/43), additional ipsilateral excision (5/43), and bracketing (2/43). Additional findings were more common for patients with larger index lesions and for invasive cancer, but there was no significant variation by age, breast density, or index lesion grade. CEM for local staging of screen-detected breast cancers identified occult malignancy in 14% of patients. CEM improves local staging and may facilitate appropriate management of screen-detected breast cancers.

Breast density effect on the sensitivity of digital screening mammography in a UK cohort.

To assess the performance of breast cancer screening by category of breast density and age in a UK screening cohort. Raw full-field digital mammography data from a single site in the UK, forming a consecutive 3-year cohort of women aged 50 to 70 years from 2016 to 2018, were obtained retrospectively. Breast density was assessed using Volpara software. Examinations were grouped by density category and age group (50-60 and 61-70 years) to analyse screening performance. Statistical analysis was performed to determine the association between density categories and age groups. Volumetric breast density was assessed as a binary classifier of interval cancers (ICs) to find an optimal density threshold. Forty-nine thousand nine-hundred forty-eight screening examinations (409 screen-detected cancers (SDCs) and 205 ICs) were included in the analysis. Mammographic sensitivity, SDC/(SDC + IC), decreased with increasing breast density from 75.0% for density a (p = 0.839, comparisons made to category b), to 73.5%, 59.8% (p = 0.001), and 51.3% (p < 0.001) in categories b, c, and d, respectively. IC rates were highest in the densest categories with rates of 1.8 (p = 0.039), 3.2, 5.7 (p < 0.001), and 7.9 (p < 0.001) per thousand for categories a, b, c, and d, respectively. The recall rate increased with breast density, leading to more false positive recalls, especially in the younger age group. There was no significant difference between the optimal density threshold found, 6.85, and that Volpara defined as the b/c boundary, 7.5. The performance of screening is significantly reduced with increasing density with IC rates in the densest category four times higher than in women with fatty breasts. False positives are a particular issue for the younger subgroup without prior examinations. In women attending screening there is significant underdiagnosis of breast cancer in those with dense breasts, most marked in the highest density category but still three times higher than in women with fatty breasts in the second highest category. Breast density can mask cancers leading to underdiagnosis on mammography. Interval cancer rate increased with breast density categories 'a' to 'd'; 1.8 to 7.9 per thousand. Recall rates increased with increasing breast density, leading to more false positive recalls.

Age-specific differences in breast cancer treatment between screen-detected and non-screen-detected breast cancers in women aged 40-74 years at diagnosis in Sweden 2008-2017.

We have recently demonstrated that screen-detected invasive breast cancers had more favourable tumour characteristics than non-screen-detected. The objective of the study was to analyse differences in breast cancer treatment between screen-detected and non-screen-detected cases by age at diagnosis, with and without adjustment for tumour (T) and nodal (N) status, within a nationwide, population-based mammography screening programme utilising register data. Data spanning 2008-2017 were collected from the National Quality Register for Breast Cancer. Multivariable logistic regression analysis was used to estimate odds ratios and 95% confidence intervals for treatment disparities between screen-detected and non-screen-detected breast cancer. Among 46,481 women diagnosed with invasive breast cancer aged 40-74 and invited for mammography screening, significant differences in treatment were observed. Screen-detected cases showed higher likelihoods of partial mastectomy compared to mastectomy, endocrine therapy, and radiotherapy, whereas chemotherapy and antibody therapy were less likely compared to non-screen-detected cases. However, when adjusting for surgery type, screen-detected cases showed lower likelihoods of radiotherapy. Age at diagnosis significantly influenced treatment odds ratios, with interactions observed for all treatments except radiotherapy adjusted for surgery. Differences increased with age, except for endocrine therapy. Radiotherapy adjusted for surgery type showed no age-related interaction. Adjusting for T and N did not alter these patterns. In general, screen-detected cases received less aggressive treatment, such as mastectomy, chemotherapy, and antibody therapy, compared to non-screen-detected cases. Disparities increased with age, except for endocrine therapy and radiotherapy adjusted for surgery. Differences persisted after adjusting for T and N, suggesting that these factors cannot solely explain the results.