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Contains fulltext : 292920.pdf (Publisher’s version ) (Open Access) Women tend to make a decision about participation in breast cancer screening and adhere to this for future invitations. Therefore, our study aimed to provide high-quality information on cumulative risks of false-positive (FP) recall and screen-detected breast cancer over multiple screening examinations. Individual Dutch screening registry data (2005-2018) were gathered on subsequent screening examinations of 92 902 women age 49 to 51 years in 2005. Survival analyses were used to calculate cumulative risks of a FP and a true-positive (TP) result after seven examinations. Data from 66 472 women age 58 to 59 years were used to extrapolate to 11 examinations. Participation, detection and additional FP rates were calculated for women who previously received FP results compared to women with true negative (TN) results. After 7 examinations, the cumulative risk of a TP result was 3.7% and the cumulative risk of a FP result was 9.1%. After 11 examinations, this increased to 7.1% and 13.5%, respectively. Following a FP result, participation was lower (71%-81%) than following a TN result (>90%). In women with a FP result, more TP results (factor 1.59 [95% CI: 1.44-1.72]), more interval cancers (factor 1.66 [95% CI: 1.41-1.91]) and more FP results (factor 1.96 [95% CI: 1.87-2.05]) were found than in women with TN results. In conclusion, due to a low recall rate in the Netherlands, the cumulative risk of a FP recall is relatively low, while the cumulative risk of a TP result is comparable. Breast cancer diagnoses and FP results were more common in women with FP results than in women with TN results, while participation was lower.

Item does not contain fulltext Background Digital breast tomosynthesis (DBT) followed by targeted US is commonly performed to evaluate women with localized breast complaints. However, the added value of DBT in addition to targeted US is unknown. Omitting DBT may be cost-effective and improve patient comfort but may miss potential breast cancer. Purpose To assess whether an imaging protocol consisting of targeted US alone may be feasible for the diagnostic work-up of women with localized symptoms and to assess the supplemental value of DBT in this reversed setting. Materials and Methods This prospective study enrolled consecutive women aged 30 years or older with focal breast complaints in three hospitals in the Netherlands between September 2017 and June 2019. In all participants, first, targeted US was evaluated, and if needed, biopsy was performed, followed by DBT. The primary outcome was the frequency of breast cancer detected with DBT when US was negative. Secondary outcomes were frequency of cancer detected with DBT elsewhere in the breast and combined overall sensitivity of US plus DBT. The reference standard was 1 year follow-up or histopathologic examination. Results There were 1961 women (mean age ± SD, 47 years ± 12) enrolled. Based on initial US alone, 1587 participants (81%) had normal or benign findings and 1759 (90%) had a definitive accurate diagnosis. In total, 204 breast cancers were detected during initial work-up. The frequency of malignancy was 10% (192 of 1961 participants) with US (US sensitivity, 98.5% [95% CI: 96, 100]; US specificity, 90.8% [95% CI: 89, 92]). DBT depicted three unobserved malignant lesions at the complaint site and 0.41% (eight of 1961 participants) of incidental malignant findings in participants without symptomatic cancer. Conclusion Compared with combined US and DBT, US was accurate as a stand-alone breast imaging modality in the assessment of focal breast complaints. The rate of cancer detection of cancers elsewhere in the breast with DBT is comparable to cancer detection rate of screening mammography. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Newell in this issue.

Contains fulltext : 244756.pdf (Publisher’s version ) (Open Access) In Western populations, the incidence of oesophageal squamous cell carcinoma (OSCC) has been declining, whereas the incidence of oesophageal adenocarcinoma (OAC) has been increasing. Our study examines temporal trends in the incidence of oesophageal cancer in the Netherlands between 1989 and 2016, in addition to predicting future trends through 2041. Data from the Netherlands Cancer Registry and Statistics Netherlands were collected to obtain incidence trends of OSCC and OAC for the period 1989 to 2016. Age-period-cohort (APC) modelling was used to estimate the contribution of age, calendar period and birth cohort on the observed incidence trends. To predict the future numbers of new cases of both OSCC and OAC from 2017 to 2041, log-linear APC models were fitted to the trends of 1989 to 2016. The age-standardised incidence rates of OSCC have decreased slightly for men and increased slightly for women. In contrast, a marked increase in the incidence of OAC was observed, ranging from 2.8 per 100 000 persons in 1989 to 10.1 in 2016. This increase in OAC incidence was more prominent in men, and it will result in an increased risk of OAC for successive generations. Future projections indicate that the incidence of OAC will further increase to 13.1 per 100 000 persons in 2037 to 2041, meaning that there will be 13 259 cases of OAC in 2037 to 2041, as compared to 9386 diagnoses in 2017 to 2021. The changing epidemiologic trends in oesophageal cancer in the Netherlands should be reflected in the development of prevention, early detection and treatment strategies.

Purpose Problem solving magnetic resonance imaging (MRI) is used to exclude malignancy in women with equivocal findings on conventional imaging. However, recommendations on its use for women recalled after screening are lacking. This study evaluates the impact of problem solving MRI on diagnostic workup among women recalled from the Dutch screening program, as well as time trends and inter-hospital variation in its use. Methods Women who were recalled at screening mammography in the South of the Netherlands (2008–2017) were included. Two-year follow-up data were collected. Diagnostic-workup and accuracy of problem solving MRI were evaluated and time trends and inter-hospital variation in its use were examined. Results In the study period 16,175 women were recalled, of whom 906 underwent problem solving MRI. Almost half of the women (45.4%) who underwent problem solving MRI were referred back to the screening program without further workup. The sensitivity, specificity, and positive and negative predictive values of problem solving MRI were 98.2%, 70.0%, 31.1%, and 99.6%, respectively. The percentage of recalled women receiving problem solving MRI fluctuated over time (4.7%–7.2%) and significantly varied among hospitals (2.2%–7.0%). Conclusion The use of problem solving MRI may exclude malignancy in recalled women. The use of problem solving MRI varied over time and among hospitals, which indicates the need for guidelines on problem solving MRI., Highlights • Problem solving MRI did correctly refer back women to the screening program. • The sensitivity and specificity of problem solving MRI were 98.2% and 70.0%. • Positive and negative predictive values of problem solving MRI were 31.1% and 99.6%. • By excluding malignancy, problem solving MRI may reduce invasive diagnostic workup.

Background The onset of the COVID-19 pandemic forced the Dutch national screening program to a halt and increased the burden on health care services, necessitating the introduction of specific breast cancer treatment recommendations from week 12 of 2020. We aimed to investigate the impact of COVID-19 on the diagnosis, stage and initial treatment of breast cancer. Methods Women included in the Netherlands Cancer Registry and diagnosed during four periods in weeks 2–17 of 2020 were compared with reference data from 2018/2019 (averaged). Weekly incidence was calculated by age group and tumor stage. The number of women receiving initial treatment within 3 months of diagnosis was calculated by period, initial treatment, age, and stage. Initial treatment, stratified by tumor behavior (ductal carcinoma in situ [DCIS] or invasive), was analyzed by logistic regression and adjusted for age, socioeconomic status, stage, subtype, and region. Factors influencing time to treatment were analyzed by Cox regression. Results Incidence declined across all age groups and tumor stages (except stage IV) from 2018/2019 to 2020, particularly for DCIS and stage I disease (p wks2–8: 2.04, ORwks9–11: 2.18). Invasive tumors were less likely to be treated initially by mastectomy with immediate reconstruction (ORwks12–13: 0.52) or by breast conserving surgery (ORwks14–17: 0.75). Chemotherapy was less likely for tumors diagnosed in the beginning of the study period (ORwks9–11: 0.59, ORwks12–13: 0.66), but more likely for those diagnosed at the end (ORwks14–17: 1.31). Primary hormonal treatment was more common (ORwks2–8: 1.23, ORwks9–11: 1.92, ORwks12–13: 3.01). Only women diagnosed in weeks 2–8 of 2020 experienced treatment delays. Conclusion The incidence of breast cancer fell in early 2020, and treatment approaches adapted rapidly. Clarification is needed on how this has affected stage migration and outcomes.

We aimed to compare (1) treatments and time intervals between treatments of breast cancer patients diagnosed during and before the COVID-19 pandemic, and (2) the number of treatments started during and before the pandemic.Women were selected from the Netherlands Cancer Registry. For aim one, odds ratios (OR) and 95% confidence intervals (95%CI) were calculated to compare the treatment of women diagnosed within four periods of 2020: pre-COVID (weeks 1-8), transition (weeks 9-12), lockdown (weeks 13-17), and care restart (weeks 18-26), with data from 2018/2019 as reference. Wilcoxon rank-sums test was used to compare treatment intervals, using a two-sided p-value 0.05. For aim two, number of treatments started per week in 2020 was compared with 2018/2019.We selected 34,097 women for aim one. Compared to 2018/2019, neo-adjuvant chemotherapy was less likely for stage I (OR 0.24, 95%CI 0.11-0.53), stage II (OR 0.63, 95%CI 0.47-0.86), and hormone receptor+/HER2- tumors (OR 0.55, 95%CI 0.41-0.75) diagnosed during transition. Time between diagnosis and first treatment decreased for patients diagnosed during lockdown with a stage I (p 0.01), II (p 0.01) or III tumor (p = 0.01). We selected 30,002 women for aim two. The number of neo-adjuvant endocrine therapies and surgeries starting in week 14, 2020, increased by 339% and 18%, respectively. The number of adjuvant chemotherapies decreased by 42% in week 15 and increased by 44% in week 22.The pandemic and subsequently altered treatment recommendations affected multiple aspects of the breast cancer treatment strategy and the number of treatments started per week.

Introduction The COVID-19 pandemic led to a significant drop in the incidence of cancer diagnoses in the Netherlands, partially due to the suspension of all national cancer screening programs on 16th March 2020 (week 12). Hospitals were forced to focus on care for COVID-19 patients resulting in limited capacity and down scaling of health care for non-COVID-19 patients. Specific recommendations for breast cancer treatment strategies, such as alterations in sequence, type, and/or frequency, were temporarily implemented from week 12 onwards. The aim of this study was to investigate the impact of the first outbreak on the initial treatment of breast cancer patients. Methods Women older than 18 years, treated within three months following their breast cancer diagnosis during weeks 2-17 2018-2019 (reference period) or weeks 2-17 2020 (COVID-19 period), were selected from the Netherlands Cancer Registry. Weeks 2-17 2020 were split up in four periods, based on the number of breast cancer diagnoses: weeks 2-8, weeks 9-11, weeks 12-13, and weeks 14-17. Average number of breast conserving surgeries (BCS), mastectomies with direct reconstruction (DR), mastectomies without DR, chemotherapy, endocrine therapy or other therapies, given as initial treatment per week, were calculated, stratified by period and by tumor stage. Treatments given to patients diagnosed in the reference period were compared with treatments given to patients diagnosed in the COVID-19 period, using a Mantel-Haenszel test, adjusting for age. Results A total of 16,553 patients were included in the current study. Of these patients 5,504 received their initial treatment in weeks 2-17 2018, 5,641 in weeks 2-17 2019 and 5,408 in weeks 2-17 2020. An increase in the use of endocrine therapy was seen in weeks 12-13 and 14-17 2020 compared to weeks 2-17 2018/2019, especially for patients with stage I cancer (12.3% and 7.7% vs 4.8%) and stage II cancer (25.4% and 17.4% vs 13.4%). In addition, a lower proportion of patients with stage II breast cancer received chemotherapy as first treatment in weeks 12-13 (21.1%) and 14-17 2020 (20.1%) compared to weeks 2-17 2018/2019 (29.8%) (Table). Discussion The COVID-19 pandemic led to a major increase in the use of endocrine therapy following the recommendations, which was mainly used to enable postponing surgery. The lower use of chemotherapy was probably related to the thought to limit hospital visits and the expected higher risk of developing COVID-19 complications due to chemotherapy. Possible long-term effects of changes in initial treatments will be monitored. Foodnote by table: Weeks 2-17 2020 (the COVID-19 period) were compared to the same weeks in 2018-2019, adjusted for age (74). A statistically significant: ↑ higher proportion of patients received this therapy, corrected for age; ↓ lower proportion of patients received this therapy, corrected for age; a: lower proportion of patients aged between 50 and 64 years received BCS; b: higher proportion of patients aged 39 or younger received mastectomy without DR; c: higher proportion of patients aged 39 or younger, or aged between 50 and 75 years received endocrine therapy; d: higher proportion of patients aged between 40 and 74 years received endocrine therapy; e: higher proportion of patients aged 74 or younger received endocrine therapy; f: higher proportion of patients aged 39 or younger received chemotherapy; g: higher proportion of patients aged 75 years or older received BCS Average number (percentage) initial treatments per week, stratified by stage and periodTotalBreast conserving surgeryMastectomy with direct reconstructionMastectomy without direct reconstructionChemotherapyEndocrine therapyTotalDCISWeek 2-17 2018/201940.629.5 (72.7)4.9 (12.0)5.7 (13.9)0.1 (0.2)0.3 (0.8)0.1 (0.2)Week 2-8 202043.730.9 (70.6)5.0 (11.4)7.3 (16.7)0.4 (1.0)0.1 (0.3)0.0 (0.0)Week 9-11 202038.027.0 (71.1)4.0 (10.5)7.0 (18.4)0.0 (0.0)0.0 (0.0)0.0 (0.0)Week 12-13 202048.031.5 (65.6)7.0 (14.6)7.0 (14.6)0.0 (0.0)2.5 (5.2) ↑0.0 (0.0)Week 14-17 202028.319.0 (67.3)3.0 (10.6)5.8 (20.4) ↑0.0 (0.0)0.5 (1.8)0.0 (0.0)Stage IWeek 2-17 2018/2019146.2104.5 (71.5)10.0 (6.8)17.8 (12.2)6.2 (4.3)7.0 (4.8)0.7 (0.5)Week 2-8 2020148.4107.9 (72.7)7.0 (4.7) ↓15.3 (10.3)10.0 (6.7) ↑7.4 (5.0)0.9 (0.6)Week 9-11 2020131.793.7 (71.1)8.0 (6.1)14.3 (10.9)6.3 (4.8)8.0 (6.1)1.3 (1.0)Week 12-13 2020163.0107.5 (66.0)a10.0 (6.1)20.0 (12.3)b4.5 (2.8)20.0 (12.3)c1.0 (0.6)Week 14-17 2020117.377.0 (65.7) ↓10.8 (9.2)16.8 (14.3)3.3 (2.8)9.0 (7.7) ↑0.5 (0.4)Stage IIWeek 2-17 2018/2019114.937.0 (32.2)5.0 (4.3)20.8 (18.1)34.3 (29.8)15.4 (13.4)2.5 (2.2)Week 2-8 2020116.133.4 (28.8) ↓4.1 (3.6)18.4 (15.9)38.4 (33.1) ↑18.3 (15.7)3.4 (3.0)Week 9-11 2020118.735.7 (30.1)5.7 (4.8)19.0 (16.0)36.0 (30.3)20.0 (16.9)2.3 (2.0)Week 12-13 2020142.042.5 (29.9)5.5 (3.9)26.5 (18.7)30.0 (21.1) ↓36.0 (25.4)d1.5 (1.1)Week 14-17 202083.327.5 (33.0)5.5 (6.6)16.0 (19.2)16.8 (20.1) ↓14.5 (17.4)e3.0 (3.6)Stage IIIWeek 2-17 2018/201931.12.0 (6.3)0.5 (1.7)5.8 (18.5)16.0 (51.5)5.3 (17.0)1.6 (5.0)Week 2-8 202027.92.4 (8.7)0.6 (2.1)5.0 (17.9)14.3 (51.3)4.7 (16.9)0.9 (3.1)Week 9-11 202026.72.0 (7.5)0.3 (1.3)5.7 (21.3)12.7 (47.5)f5.7 (21.3)0.3 (1.3)Week 12-13 202038.52.0 (5.2)0.5 (1.3)7.5 (19.5)19.0 (49.4)8.5 (22.1)1.0 (2.6)Week 14-17 202020.81.5 (7.2)1.3 (6.0) ↑4.5 (21.7)8.0 (38.6)4.5 (21.7)1.0 (4.8)Stage IVWeek 2-17 2018/201915.00.3 (2.3)0.0 (0.2)0.6 (4.0)5.3 (34.9)6.8 (44.9)2.1 (13.7)Week 2-8 202014.60.6 (3.9)0.0 (0.0)0.4 (2.9)4.7 (32.4)6.7 (46.1)2.1 (14.7)Week 9-11 202012.00.0 (0.0)0.0 (0.0)0.0 (0.0)3.3 (27.8)7.0 (58.3)1.3 (11.1)Week 12-13 202019.51.5 (7.7)0.0 (0.0)2.5 (12.8) ↑6.0 (30.8)7.5 (38.5)2.0 (10.3)Week 14-17 202013.80.3 (1.8)g0.0 (0.0)0.3 (1.8)3.8 (27.3)8.3 (60.0) ↑1.3 (9.1) Citation Format: Anouk H Eijkelboom, Linda de Munck, Marie-Jeanne Vrancken Peeters, Marjolein Smidt, Mireille Broeders, Monique Bos, Marjanka K Schmidt, Maud Bessems, Luc Strobbe, Desirée van den Bongard, Aafke Honkoop, Janneke Verloop, Cristina Guerrero Paez, Marc Lobbes, Sabine Linn, Pieter Westenend, Catharina W Menke-van der Houven van Oordt, Jelle Wesseling, Vivianne Tjan Heijnen, Sabine Siesling, On behalve of the NABON COVID-19 consortium. Effect of the COVID-19 pandemic on the initial treatment of breast cancer in the Netherlands: A population-based study [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PS7-88.

Background In the Dutch breast cancer screening program, mammograms are preread by technologists to identify possible abnormalities, leading to "warning signals" (an audible and visual alert if the technologist observed an abnormality suspicious for cancer) for radiologists. The best moment to present these warning signals is unknown. Purpose To determine the effect that blinding of technologists' warning signals has on radiologists' early screening outcome measures during interpretation of mammograms. Materials and Methods In this prospective study from September 2017 to May 2019, on alternating months, radiologists were either blinded or nonblinded to the warning signals of the technologist when interpreting screening mammograms for breast cancer. All discrepancies between radiologists and technologists were reviewed during quality assurance sessions every 6 weeks, which could result in secondary recalls. The outcome measures of this study were recall rate, cancer detection rate, and positive predictive value of recall. A χ

BackgroundA baseline computed tomography (CT) scan for lung cancer (LC) screening may reveal information indicating that certain LC screening participants can be screened less, and instead require dedicated early cardiac and respiratory clinical input. We aimed to develop and validate competing death (CD) risk models using CT information to identify participants with a low LC risk and a high CD risk.MethodsParticipant demographics and quantitative CT measures of LC, cardiovascular disease and chronic obstructive pulmonary disease were considered for deriving a logistic regression model for predicting 5-year CD risk using a sample from the National Lung Screening Trial (n=15 000). Multicentric Italian Lung Detection data were used to perform external validation (n=2287).ResultsOur final CD model outperformed an external pre-scan model (CD Risk Assessment Tool) in both the derivation (area under the curve (AUC) 0.744 (95% CI 0.727–0.761) and 0.677 (95% CI 0.658–0.695), respectively) and validation cohorts (AUC 0.744 (95% CI 0.652–0.835) and 0.725 (95% CI 0.633–0.816), respectively). By also taking LC incidence risk into consideration, we suggested a risk threshold where a subgroup (6258/23 096 (27%)) was identified with a number needed to screen to detect one LC of 216 (versus 23 in the remainder of the cohort) and ratio of 5.41 CDs per LC case (versus 0.88). The respective values in the validation cohort subgroup (774/2287 (34%)) were 129 (versus 29) and 1.67 (versus 0.43).ConclusionsEvaluating both LC and CD risks post-scan may improve the efficiency of LC screening and facilitate the initiation of multidisciplinary trajectories among certain participants.

Background During healthcare guideline development, panel members often have implicit, different definitions of health outcomes that can lead to misunderstandings about how important these outcomes are and how to balance benefits and harms. McMaster GRADE Centre researchers developed ‘health outcome descriptors’ for standardizing descriptions of health outcomes and overcoming these problems to support the European Commission Initiative on Breast Cancer (ECIBC) Guideline Development Group (GDG). We aimed to determine which aspects of the development, content, and use of health outcome descriptors were valuable to guideline developers. Methods We developed 24 health outcome descriptors related to breast cancer screening and diagnosis for the European Commission Breast Guideline Development Group (GDG). Eighteen GDG members provided feedback in written format or in interviews. We then evaluated the process and conducted two health utility rating surveys. Results Feedback from GDG members revealed that health outcome descriptors are probably useful for developing recommendations and improving transparency of guideline methods. Time commitment, methodology training, and need for multidisciplinary expertise throughout development were considered important determinants of the process. Comparison of the two health utility surveys showed a decrease in standard deviation in the second survey across 21 (88%) of the outcomes. Conclusions Health outcome descriptors are feasible and should be developed prior to the outcome prioritization step in the guideline development process. Guideline developers should involve a subgroup of multidisciplinary experts in all stages of development and ensure all guideline panel members are trained in guideline methodology that includes understanding the importance of defining and understanding the outcomes of interest.

Background Delay in detection of breast cancer may worsen tumour characteristics, with progression of tumour size and a higher risk of metastatic lymph nodes. The purpose of this study was to investigate delayed breast cancer diagnosis after repeated recall for the same mammographic abnormality at screening. Methods This was a retrospective study performed in two cohorts of women enrolled in a mammography screening programme in the Netherlands. All women aged 50−75 who underwent biennial screening mammography either between January 1, 1997 and December 31, 2006 (cohort 1) or between January 1, 2007 and December 31, 2016 (cohort 2) were included. Results The cohorts showed no difference in proportions of women with delayed breast cancer diagnosis of at least 2 years (2.2% versus 2.8%, P = 0.29). Most delays were caused by incorrect BI-RADS classifications after recall (74.2%). An increase in mean tumour size was seen when comparing sizes at initial false-negative recall and at diagnosis of breast cancer (P Conclusions The proportion of women with a long delay in breast cancer confirmation following repeated recall at screening mammography has not decreased during 20 years of screening. These delays lead to larger tumour size at detection and may negatively influence prognosis.

Background To estimate the percentages of advanced-stage breast cancers (BCs) detected during the course of a steady-state screening programme when using different definitions of advanced BC. Methods Data of women aged 49–74 years, diagnosed with BC in 2006–2015, were selected from the Netherlands Cancer Registry and linked to the screening registry. BCs were classified as screen-detected, interval or non-screened. Three definitions of advanced BC were used for comparison: TNM stage (III–IV), NM stage (N+ and/or M+) and T size (invasive tumour ≥15 mm). Analyses were performed assuming a 10% overdiagnosis rate. In sensitivity analyses, this assumption varied from 0 to 30%. Results We included 46,734 screen-detected, 17,362 interval and 24,189 non-screened BCs. By TNM stage, 4.9% of screen-detected BCs were advanced, compared with 19.4% and 22.8% of interval and non-screened BCs, respectively (p Conclusion Irrespective of the definition, screen-detected BCs were less frequently in the advanced stage. These findings provide evidence of a stage shift to early detection and support the potential of mammographic screening to reduce treatment-related burdens and the mortality associated with BC.

The goal of this study was to describe the variation in hospital-based diagnostic care activities for patients with symptomatology suspect for breast cancer in The Netherlands. Two cohorts were included: the ‘benign’ cohort (30,334 women suspected of, but without breast cancer) and the ‘malignant’ cohort (2236 breast cancer patients). Hospital-based financial data was combined with tumor data (malignant cohort) from The Netherlands Cancer Registry. Patterns within diagnostic pathways were analyzed. Factors influencing the number of visits and number of diagnostic care activities until diagnosis were identified in the malignant cohort with multivariable Cox and Poisson regression models. Compared to patients with benign diagnosis, patients with malignant disease received their diagnosis less frequently in one day, after an equal average number of hospital visits and higher average number of diagnostic activities. Factors increasing the number of diagnostic care activities were the following: lower age and higher cM-and cN-stages. Factors increasing the number of days until (malignant) diagnosis were as follows: higher BIRADS-score, screen-detected and higher cN-and cT-stages. Hospital of diagnosis influenced both number of activities and days to diagnosis. The diagnostic care pathway of patients with malignant disease required more time and diagnostic activities than benign disease and depends on hospital, tumor and patient characteristics.

The magnitude of the tradeoff between recall rate (RR) and cancer detection rate (CDR) in breast-cancer screening is not clear, and it is expected to depend on target population and screening program characteristics. Multi-reader multi-case research studies, which may be used to estimate this tradeoff, rely on enriched datasets with artificially high prevalence rates, which may bias the results. Furthermore, readers participating in research studies are subject to "laboratory" effects, which can alter their performance relative to actual practice. The Recall and detection Of breast Cancer in Screening (ROCS) trial uses a novel data acquisition system that minimizes these limitations while obtaining an estimate of the RR-CDR curve during actual practice in the Dutch National Breast Cancer Screening Program. ROCS involves collection of at least 40,000 probability-of-malignancy ratings from at least 20 radiologists during interpretation of approximately 2,000 digital mammography screening cases each. With the use of custom-built software on a tablet, and a webcam, this data was obtained in the usual reading environment with minimal workflow disruption and without electronic access to the review workstation software. Comparison of the results to short- and medium-term follow-up allows for estimation of the RR-CDR and receiver operating characteristics curves, respectively. The anticipated result of the study is that performance-based evidence from practice will be available to determine the optimal operating point for breast-cancer screening. In addition, this data will be useful as a benchmark when evaluating the impact of potential new screening technologies, such as digital breast tomosynthesis or artificial intelligence. KEY POINTS: • The ROCS trial aims to estimate the recall rate-cancer detection rate curve during actual screening practice in the Dutch National Breast Cancer Screening Program. • The study design is aimed at avoiding the influence of the "laboratory effect" in usual observer performance studies. • The use of a tablet and a webcam allows for the acquisition of probability of malignancy ratings without access to the review workstation software.

Objectives To study how radiologists’ perceived ability to interpret digital mammography (DM) images is affected by decreases in image quality. Methods One view from 45 DM cases (including 30 cancers) was degraded to six levels each of two acquisition-related issues (lower spatial resolution and increased quantum noise) and three post-processing-related issues (lower and higher contrast and increased correlated noise) seen during clinical evaluation of DM systems. The images were shown to fifteen breast screening radiologists from five countries. Aware of lesion location, the radiologists selected the most-degraded mammogram (indexed from 1 (reference) to 7 (most degraded)) they still felt was acceptable for interpretation. The median selected index, per degradation type, was calculated separately for calcification and soft tissue (including normal) cases. Using the two-sided, non-parametric Mann-Whitney test, the median indices for each case and degradation type were compared. Results Radiologists were not tolerant to increases (medians: 1.5 (calcifications) and 2 (soft tissue)) or decreases (median: 2, for both types) in contrast, but were more tolerant to correlated noise (median: 3, for both types). Increases in quantum noise were tolerated more for calcifications than for soft tissue cases (medians: 3 vs. 4, p = 0.02). Spatial resolution losses were considered less acceptable for calcification detection than for soft tissue cases (medians: 3.5 vs. 5, p = 0.001). Conclusions Perceived ability of radiologists for image interpretation in DM was affected not only by image acquisition-related issues but also by image post-processing issues, and some of those issues affected calcification cases more than soft tissue cases. Key Points • Lower spatial resolution and increased quantum noise affected the radiologists’ perceived ability to interpret calcification cases more than soft tissue lesion or normal cases. • Post-acquisition image processing-related effects, not only image acquisition-related effects, also impact the perceived ability of radiologists to interpret images and detect lesions. • In addition to current practices, post-acquisition image processing-related effects need to also be considered during the testing and evaluation of digital mammography systems.

Item does not contain fulltext Purpose: To validate a previously proposed algorithm that modifies a mammogram to appear as if it was acquired with different technique factors using realistic phantom-based mammograms. Approach: Two digital mammography systems (an indirect- and a direct-detector-based system) were used to acquire realistic mammographic images of five 3D-printed breast phantoms with the technique factors selected by the automatic exposure control and at various other conditions (denoted by the original images). Additional images under other simulated conditions were also acquired: higher or lower tube voltages, different anode/filter combinations, or lower tube current-time products (target images). The signal and noise in the original images were modified to simulate the target images (simulated images). The accuracy of the image modification algorithm was validated by comparing the target and simulated images using the local mean, local standard deviation (SD), local variance, and power spectra (PS) of the image signals. The absolute relative percent error between the target and simulated images for each parameter was calculated at each sub-region of interest (local parameters) and frequency (PS), and then averaged. Results: The local mean signal, local SD, local variance, and PS of the target and simulated images were very similar, with a relative percent error of 5.5%, 3.8%, 7.8%, and 4.4% (indirect system), respectively, and of 3.7%, 3.8%, 7.7%, and 7.5% (direct system), respectively. Conclusions: The algorithm is appropriate for simulating different technique factors. Therefore, it can be used in various studies, for instance to evaluate the impact of technique factors in cancer detection using clinical images.

ObjectivesWe investigated whether changes in mammographic technique and screening policy have improved mammographic sensitivity, and elongated the mean sojourn time, since the introduction of biennial breast cancer screening in Nijmegen, the Netherlands, in 1975.MethodsMaximum likelihood estimation, non-linear regression, and Markov Chain Monte Carlo simulation were used to estimate test sensitivity, mean sojourn time, and underlying breast cancer incidence in four time periods, covering 40 years of breast cancer screening in Nijmegen (1975–2012).ResultsMaximum likelihood estimation generated an estimated test sensitivity of approximately 90% and a mean sojourn time around three years, while the estimates based on non-linear regression and Markov Chain Monte Carlo simulation were 80% and four years, respectively. All three methods estimated a rise in the underlying breast cancer incidence over time, with approximately one case more per 1000 women per year in the final period compared with the first period.ConclusionsThe three methods showed a slightly higher mammographic sensitivity and a longer mean sojourn time in the last period, after the introduction of digital mammography. Estimates were more realistic for the more sophisticated methods, non-linear regression and Markov Chain Monte Carlo simulation, while the simple closed form approximation of maximum likelihood estimation led to rather high estimates for sensitivity in the early periods.

Background Artificial intelligence (AI) systems performing at radiologist-like levels in the evaluation of digital mammography (DM) would improve breast cancer screening accuracy and efficiency. We aimed to compare the stand-alone performance of an AI system to that of radiologists in detecting breast cancer in DM. Methods Nine multi-reader, multi-case study datasets previously used for different research purposes in seven countries were collected. Each dataset consisted of DM exams acquired with systems from four different vendors, multiple radiologists’ assessments per exam, and ground truth verified by histopathological analysis or follow-up, yielding a total of 2652 exams (653 malignant) and interpretations by 101 radiologists (28 296 independent interpretations). An AI system analyzed these exams yielding a level of suspicion of cancer present between 1 and 10. The detection performance between the radiologists and the AI system was compared using a noninferiority null hypothesis at a margin of 0.05. Results The performance of the AI system was statistically noninferior to that of the average of the 101 radiologists. The AI system had a 0.840 (95% confidence interval [CI] = 0.820 to 0.860) area under the ROC curve and the average of the radiologists was 0.814 (95% CI = 0.787 to 0.841) (difference 95% CI = −0.003 to 0.055). The AI system had an AUC higher than 61.4% of the radiologists. Conclusions The evaluated AI system achieved a cancer detection accuracy comparable to an average breast radiologist in this retrospective setting. Although promising, the performance and impact of such a system in a screening setting needs further investigation.

Purpose To study the feasibility of automatically identifying normal digital mammography (DM) exams with artificial intelligence (AI) to reduce the breast cancer screening reading workload. Methods and materials A total of 2652 DM exams (653 cancer) and interpretations by 101 radiologists were gathered from nine previously performed multi-reader multi-case receiver operating characteristic (MRMC ROC) studies. An AI system was used to obtain a score between 1 and 10 for each exam, representing the likelihood of cancer present. Using all AI scores between 1 and 9 as possible thresholds, the exams were divided into groups of low- and high likelihood of cancer present. It was assumed that, under the pre-selection scenario, only the high-likelihood group would be read by radiologists, while all low-likelihood exams would be reported as normal. The area under the reader-averaged ROC curve (AUC) was calculated for the original evaluations and for the pre-selection scenarios and compared using a non-inferiority hypothesis. Results Setting the low/high-likelihood threshold at an AI score of 5 (high likelihood > 5) results in a trade-off of approximately halving (− 47%) the workload to be read by radiologists while excluding 7% of true-positive exams. Using an AI score of 2 as threshold yields a workload reduction of 17% while only excluding 1% of true-positive exams. Pre-selection did not change the average AUC of radiologists (inferior 95% CI > − 0.05) for any threshold except at the extreme AI score of 9. Conclusion It is possible to automatically pre-select exams using AI to significantly reduce the breast cancer screening reading workload., European Radiology, 29 (9), ISSN:0938-7994, ISSN:1432-1084

ObjectiveIncreased knowledge of breast cancer risk factors enables a shift from one‐size‐fits‐all breast cancer screening to a risk‐based approach, tailoring screening policy to a woman's individual risk. New opportunities for prevention will arise. However, before this novel screening and prevention program is introduced, its acceptability from a woman's perspective needs to be explored.MethodsWomen eligible for breast cancer screening in the Netherlands, United Kingdom, and Sweden were invited to take part in focus groups. A total of 143 women participated. Data were transcribed verbatim and analyzed using thematic analysis.ResultsAnalysis identified five themes across the three countries. The first theme “impact of knowledge” describes women's concern of not being able to unlearn their risk, perceiving it as either a motivator for change or a burden which may lead to stigma. The second theme “belief in science” explains women's need to trust the science behind the risk assessment and subsequent care pathways. Theme three “emotional impact” explores, eg, women's perceived anxiety and (false) reassurance, which may result from knowing their risk. Theme four “decision making” highlights cultural differences in shared versus individual decision making. Theme five “attitude to medication” explores the controversial topic of offering preventative medication for breast cancer risk reduction.ConclusionsAcceptability of risk‐based screening and prevention is mixed. Women's perceptions are informed by a lack of knowledge, cultural norms, and common emotional concerns, which highlights the importance of tailored educational materials and risk counselling to aid either shared or individual informed decision making.

Objectives: To determine the extent and characteristics of delay in breast cancer diagnosis in women recalled at screening mammography.Methods: We included a consecutive series of 817,656 screens of women who received biennial screening mammography in a Dutch breast cancer screening region between 1997 and 2016. During at least 3.5 years follow-up, radiological reports and biopsy reports were collected of all recalled women. The inclusion period was divided into four cohorts of four years each. We determined the number of screen-detected cancers and their characteristics, and assessed the proportion of recalled women who experienced a diagnostic delay of at least 4 months in breast cancer confirmation.Results: The proportion of recalled women who experienced diagnostic delay decreased from 7.5 % in 1997 2001 (47/623) to 3.0 % in 2012 2016 (67/2223, P < 0.001). The proportion of women with a delay of at least two years increased from 27.7 % (13/47) in 1997 2001 to 75.7 % (53/70) in 2012 2016 (P < 0.001). Cancers with a diagnostic delay > 2 years were more frequently invasive (P = 0.009) than cancers with a diagnostic delay of 4 24 months. The most frequent cause of diagnostic delays was incorrect radiological classifications by clinical radiologists (55.2 % overall) after recall.Conclusions: The proportion of recalled women with a delayed breast cancer diagnosis has more than halved during two decades of screening mammography. Delays in breast cancer diagnosis are characterized by longer delay intervals, although the proportion of these delays among all screen-detected cancers has not increased. Preventing longer delays in breast cancer confirmation may help improve breast cancer survival.

Risk-stratified screening for breast cancer (BC) is increasingly considered as a promising approach. However, its implementation is challenging and needs to be acceptable to women. We examined Canadian women’s attitudes towards, comfort level about, and willingness to take part in BC risk-stratified screening. We conducted an online survey in women aged 30 to 69 years in four Canadian provinces. In total, 4293 women completed the questionnaire (response rate of 63%). The majority of women (63.5% to 72.8%) expressed favorable attitudes towards BC risk-stratified screening. Most women reported that they would be comfortable providing personal and genetic information for BC risk assessment (61.5% to 67.4%) and showed a willingness to have their BC risk assessed if offered (74.8%). Most women (85.9%) would also accept an increase in screening frequency if they were at higher risk, but fewer (49.3%) would accept a reduction in screening frequency if they were at lower risk. There were few differences by province, however, outcomes varied by age, education level, marital status, income, perceived risk, history of BC, prior mammography, and history of genetic test for BC (all p ≤ 0.01). Risk-based BC screening using multifactorial risk assessment appears to be acceptable to most women. This suggests that the implementation of this approach is likely to be well-supported by Canadian women.

Screening can decrease the burden of breast, cervical, and colorectal cancers. The COVID-19 pandemic led many countries to suspend cancer screening services as part of their response to the pandemic. The International Cancer Screening Network (ICSN) carried out an online survey to assess the effects of the first wave of the COVID-19 pandemic on cancer screening. A 33-item survey was distributed to 834 email addresses to gather information about settings and assess decision-making processes that led to cancer screening suspension. Information about communication, impact on resources, and patient follow-up was collected. Quantitative data was analyzed as frequencies overall and by setting, while a comment section under each survey item captured nuanced details. Responses were recategorized into 66 settings, representing 35 countries. Most settings suspended cancer screening services (n = 60, 90.9%) in March 2020 (n = 45, 68.2%), guided by a government decision (n = 51, 77.3%). Few settings made the decision whether to suspend services based on a preparedness plan (n = 17, 25.8%). In most settings, professionals were reassigned (n = 41, 62.1%) and infrastructure repurposed (n = 35, 53.0%). The first wave of the COVID-19 pandemic has had profound effects on cancer screening worldwide, including the suspension of services in almost all settings. Most settings were unprepared to deal with the scale of the pandemic but demonstrated flexibility in the response. These results contribute to inform, through experiences and lessons learned, the next steps for the global cancer screening community to further evaluate the impact of COVID-19 and prepare for future disruptions.

The COVID-19 pandemic forced the Dutch national breast screening program to a halt in week 12, 2020. In week 26, the breast program was resumed at 40% capacity, which increased to 60% in week 34. We examined the impact of the suspension and restart of the screening program on the incidence of screen-detected and non-screen-detected breast cancer. We selected women aged 50-74, diagnosed during weeks 2-35 of 2018 (n = 7250), 2019 (n = 7302), or 2020 (n = 5306), from the Netherlands Cancer Registry. Weeks 2-35 were divided in seven periods, based on events occurring at the start of the COVID-19 pandemic. Incidence of screen-detected and non-screen-detected tumors was calculated overall and by age group, cT-stage, and cTNM-stage for each period in 2020, and compared to the incidence in the same period of 2018/2019 (averaged). The incidence of screen-detected tumors decreased during weeks 12-13, reached almost zero during weeks 14-25, and increased during weeks 26-35. Incidence of non-screen-detected tumors decreased to a lesser extent during weeks 12-16. The decrease in incidence was seen in all age groups and mainly occurred for cTis, cT1, DCIS, and stage I tumors. Due to the suspension of the breast cancer screening program, and the restart at reduced capacity, the incidence of screen-detected breast tumors decreased by 67% during weeks 9-35 2020, which equates to about 2000 potentially delayed breast cancer diagnoses. Up to August 2020 there was no indication of a shift towards higher stage breast cancers after restart of the screening.

Contains fulltext : 229548.pdf (Publisher’s version ) (Open Access) PURPOSE: To develop a candidate instrument to assess image quality in digital mammography, by identifying clinically relevant features in images that are affected by lower image quality. METHODS: Interviews with fifteen expert breast radiologists from five countries were conducted and analysed by using adapted directed content analysis. During these interviews, 45 mammographic cases, containing 44 lesions (30 cancers, 14 benign findings), and 5 normal cases, were shown with varying image quality. The interviews were performed to identify the structures from breast tissue and lesions relevant for image interpretation, and to investigate how image quality affected the visibility of those structures. The interview findings were used to develop tentative items, which were evaluated in terms of wording, understandability, and ambiguity with expert breast radiologists. The relevance of the tentative items was evaluated using the content validity index (CVI) and modified kappa index (k*). RESULTS: Twelve content areas, representing the content of image quality in digital mammography, emerged from the interviews and were converted into 29 tentative items. Fourteen of these items demonstrated excellent CVI>/=0.78 (k* > 0.74), one showed good CVI

Contains fulltext : 229806.pdf (Publisher’s version ) (Open Access) Oncological care was largely derailed due to the reprioritisation of health care services to handle the initial surge of COVID-19 patients adequately. Cancer screening programmes were no exception in this reprioritisation. They were temporarily halted in the Netherlands (1) to alleviate the pressure on health care services overwhelmed by the upsurge of COVID-19 patients, (2) to reallocate staff and personal protective equipment to support critical COVID-19 care, and (3) to mitigate the spread of COVID-19. Utilising data from the Netherlands Cancer Registry on provisional cancer diagnoses between 6 January 2020 and 4 October 2020, we assessed the impact of the temporary halt of national population screening programmes on the diagnosis of breast and colorectal cancer in the Netherlands. A dynamic harmonic regression model with ARIMA error components was applied to assess the observed versus expected number of cancer diagnoses per calendar week. Fewer diagnoses of breast and colorectal cancer were objectified amid the early stages of the initial COVID-19 outbreak in the Netherlands. This effect was most pronounced among the age groups eligible for cancer screening programmes, especially in breast cancer (age group 50-74 years). Encouragingly enough, the observed number of diagnoses ultimately reached and virtually remained at the level of the expected values. This finding, which emerged earlier in age groups not invited for cancer screening programmes, comes on account of the decreased demand for critical COVID-19 care since early April 2020, which, in turn, paved the way forward to resume screening programmes and a broad range of non-critical health care services, albeit with limited operating and workforce capacity. Collectively, transient changes in health-seeking behaviour, referral practices, and cancer screening programmes amid the early stages of the initial COVID-19 epidemic in the Netherlands conjointly acted as an accelerant for fewer breast and colorectal cancer diagnoses in age groups eligible for cancer screening programmes. Forthcoming research is warranted to assess whether the decreased diagnostic scrutiny of cancer during the COVID-19 pandemic resulted in stage migration and altered clinical management, as well as poorer outcomes.

The European Collaborative on Personalized Early Detection and Prevention of Breast Cancer (ENVISION) brings together several international research consortia working on different aspects of the personalized early detection and prevention of breast cancer. In a consensus conference held in 2019, the members of this network identified research areas requiring development to enable evidence-based personalized interventions that might improve the benefits and reduce the harms of existing breast cancer screening and prevention programmes. The priority areas identified were: 1) breast cancer subtype-specific risk assessment tools applicable to women of all ancestries; 2) intermediate surrogate markers of response to preventive measures; 3) novel non-surgical preventive measures to reduce the incidence of breast cancer of poor prognosis; and 4) hybrid effectiveness-implementation research combined with modelling studies to evaluate the long-term population outcomes of risk-based early detection strategies. The implementation of such programmes would require health-care systems to be open to learning and adapting, the engagement of a diverse range of stakeholders and tailoring to societal norms and values, while also addressing the ethical and legal issues. In this Consensus Statement, we discuss the current state of breast cancer risk prediction, risk-stratified prevention and early detection strategies, and their implementation. Throughout, we highlight priorities for advancing each of these areas.

ObjectivesCombined assessment of cardiovascular disease (CVD), COPD and lung cancer may improve the effectiveness of lung cancer screening in smokers. The aims were to derive and assess risk models for predicting lung cancer incidence, CVD mortality and COPD mortality by combining quantitative computed tomography (CT) measures from each disease, and to quantify the added predictive benefit of self-reported patient characteristics given the availability of a CT scan.MethodsA survey model (patient characteristics only), CT model (CT information only) and final model (all variables) were derived for each outcome using parsimonious Cox regression on a sample from the National Lung Screening Trial (n=15 000). Validation was performed using Multicentric Italian Lung Detection data (n=2287). Time-dependent measures of model discrimination and calibration are reported.ResultsAge, mean lung density, emphysema score, bronchial wall thickness and aorta calcium volume are variables that contributed to all final models. Nodule features were crucial for lung cancer incidence predictions but did not contribute to CVD and COPD mortality prediction. In the derivation cohort, the lung cancer incidence CT model had a 5-year area under the receiver operating characteristic curve of 82.5% (95% CI 80.9–84.0%), significantly inferior to that of the final model (84.0%, 82.6–85.5%). However, the addition of patient characteristics did not improve the lung cancer incidence model performance in the validation cohort (CT model 80.1%, 74.2–86.0%; final model 79.9%, 73.9–85.8%). Similarly, the final CVD mortality model outperformed the other two models in the derivation cohort (survey model 74.9%, 72.7–77.1%; CT model 76.3%, 74.1–78.5%; final model 79.1%, 77.0–81.2%), but not the validation cohort (survey model 74.8%, 62.2–87.5%; CT model 72.1%, 61.1–83.2%; final model 72.2%, 60.4–84.0%). Combining patient characteristics and CT measures provided the largest increase in accuracy for the COPD mortality final model (92.3%, 90.1–94.5%) compared to either other model individually (survey model 87.5%, 84.3–90.6%; CT model 87.9%, 84.8–91.0%), but no external validation was performed due to a very low event frequency.ConclusionsCT measures of CVD and COPD provides small but reproducible improvements to nodule-based lung cancer risk prediction accuracy from 3 years onwards. Self-reported patient characteristics may not be of added predictive value when CT information is available.