Information and communication priorities of patients and healthcare professionals in shared decision making regarding adjuvant systemic breast cancer treatment: A survey study.

PURPOSE: To assess information and communication priorities of patients and healthcare professionals in Shared Decision Making about adjuvant systemic treatment of primary breast cancer and identify key decision-relevant information accordingly. METHODS: Patients (N = 122) and professionals working with breast cancer patients (N = 118), of whom 38 were nurse practitioners and 32 nurses, were recruited using convenience sampling, and surveyed about information/communication aspects key to decision-making, using ranking assignments. We further posed a simple open question, questions about receiving population-based statistics versus personalized statistics concerning treatment outcomes, and their attitude and experience concerning Shared Decision Making. Data were analyzed using descriptive analysis and a qualitative analysis. RESULTS: Both patients and professionals prioritized information about treatment outcomes (i.e., survival, recurrence) as key decision-relevant information for patients. Patients prioritized information about relatively severe treatment side-effects and late effects (e.g., blood clot, stroke), whilst professionals prioritized information about effects that occur relatively often (e.g., hair loss, fatigue). Patients specifically wanted to know if the benefit of treatment is worth the negative impact. Both groups prioritized personalized statistics over population-based statistics. CONCLUSIONS: Some differences between patients and professionals were found in information and communication priorities, specifically related to the different side-effects. It seems worthwhile to precisely address these side-effects in Shared Decision Making concerning adjuvant systemic treatment. Furthermore, it seems important to deliberate together on the question if expected benefit of treatment is worth the potential negative impact for the individual patient.

Evaluation of the Implementation of the Dutch Breast Cancer Surveillance Decision Aid including Personalized Risk Estimates in the SHOUT-BC Study: A Mixed Methods Approach.

BACKGROUND: To improve Shared decision-making (SDM) regarding personalized post-treatment surveillance, the Breast Cancer Surveillance Decision Aid (BCS-PtDA), integrating personalized risk information, was developed and implemented in eight hospitals. The aim of this mixed-methods study was to (1) assess the implementation and participation rates, (2) identify facilitators and barriers for use by health care professionals (HCPs), (3) quantify the observed level of SDM, and (4) evaluate risk communication and SDM application in consultations. METHODS: Implementation and participation rates and patients' BCS-PtDA use were calculated using hospital registry data and BCS-PtDA log data. HCPs' perspective on facilitators and barriers were collected using the MIDI framework. Observed SDM levels in consultation transcripts were quantified using the OPTION-5 scale. Thematic analysis was performed to assess consultation content. RESULTS: The average PtDA implementation and participation rates were, respectively, 26% and 61%. HCPs reported that the PtDA supported choice awareness. Reported barriers for implementation were mainly increased workload and a lack of perceived benefits. The consultation analysis (n = 64) showed patients were offered a choice, but deliberation was lacking. Risk communication was generally adequate. DISCUSSION: When the BCS-PtDA was used, patients were clearly given a choice regarding their post-treatment surveillance, but information provision and SDM application can be improved.

Opportunities for personalised follow-up in breast cancer: the gap between daily practice and recurrence risk.

PURPOSE: Follow-up guidelines barely diverge from a one-size-fits-all approach, even though the risk of recurrence differs per patient. However, the personalization of breast cancer care improves outcomes for patients. This study explores the variation in follow-up pathways in the Netherlands using real-world data to determine guideline adherence and the gap between daily practice and risk-based surveillance, to demonstrate the benefits of personalized risk-based surveillance compared with usual care. METHODS: Patients with stage I-III invasive breast cancer who received surgical treatment in a general hospital between 2005 and 2020 were selected from the Netherlands Cancer Registry and included all imaging activities during follow-up from hospital-based electronic health records. Process analysis techniques were used to map patients and activities to investigate the real-world utilisation of resources and identify the opportunities for improvement. The INFLUENCE 2.0 nomogram was used for risk prediction of recurrence. RESULTS: In the period between 2005 and 2020, 3478 patients were included with a mean follow-up of 4.9 years. In the first 12 months following treatment, patients visited the hospital between 1 and 5 times (mean 1.3, IQR 1-1) and received between 1 and 9 imaging activities (mean 1.7, IQR 1-2). Mammogram was the prevailing imaging modality, accounting for 70% of imaging activities. Patients with a low predicted risk of recurrence visited the hospital more often. CONCLUSIONS: Deviations from the guideline were not in line with the risk of recurrence and revealed a large gap, indicating that it is hard for clinicians to accurately estimate this risk and therefore objective risk predictions could bridge this gap.

Clinical decision support systems for multidisciplinary team decision-making in patients with solid cancer: Composition of an implementation model based on a scoping review.

Generating guideline-based recommendations during multidisciplinary team (MDT) meetings in solid cancers is getting more complex due to increasing amount of information needed to follow the guidelines. Usage of clinical decision support systems (CDSSs) can simplify and optimize decision-making. However, CDSS implementation is lagging behind. Therefore, we aim to compose a CDSS implementation model. By performing a scoping review of the currently reported CDSSs for MDT decision-making we determined 102 barriers and 86 facilitators for CDSS implementation out of 44 papers describing 20 different CDSSs. The most frequently reported barriers and facilitators for CDSS implementation supporting MDT decision-making concerned CDSS maintenance (e.g. incorporating guideline updates), validity of recommendations and interoperability with electronic health records. Based on the identified barriers and facilitators, we composed a CDSS implementation model describing clinical utility, analytic validity and clinical validity to guide CDSS integration more successfully in the clinical workflow to support MDTs in the future.

Long-term outcomes of young, node-negative, chemotherapy-naïve, triple-negative breast cancer patients according to BRCA1 status.

BACKGROUND: Due to the abundant usage of chemotherapy in young triple-negative breast cancer (TNBC) patients, the unbiased prognostic value of BRCA1-related biomarkers in this population remains unclear. In addition, whether BRCA1-related biomarkers modify the well-established prognostic value of stromal tumor-infiltrating lymphocytes (sTILs) is unknown. This study aimed to compare the outcomes of young, node-negative, chemotherapy-naïve TNBC patients according to BRCA1 status, taking sTILs into account. METHODS: We included 485 Dutch women diagnosed with node-negative TNBC under age 40 between 1989 and 2000. During this period, these women were considered low-risk and did not receive chemotherapy. BRCA1 status, including pathogenic germline BRCA1 mutation (gBRCA1m), somatic BRCA1 mutation (sBRCA1m), and tumor BRCA1 promoter methylation (BRCA1-PM), was assessed using DNA from formalin-fixed paraffin-embedded tissue. sTILs were assessed according to the international guideline. Patients' outcomes were compared using Cox regression and competing risk models. RESULTS: Among the 399 patients with BRCA1 status, 26.3% had a gBRCA1m, 5.3% had a sBRCA1m, 36.6% had tumor BRCA1-PM, and 31.8% had BRCA1-non-altered tumors. Compared to BRCA1-non-alteration, gBRCA1m was associated with worse overall survival (OS) from the fourth year after diagnosis (adjusted HR, 2.11; 95% CI, 1.18-3.75), and this association attenuated after adjustment for second primary tumors. Every 10% sTIL increment was associated with 16% higher OS (adjusted HR, 0.84; 95% CI, 0.78-0.90) in gBRCA1m, sBRCA1m, or BRCA1-non-altered patients and 31% higher OS in tumor BRCA1-PM patients. Among the 66 patients with tumor BRCA1-PM and ≥ 50% sTILs, we observed excellent 15-year OS (97.0%; 95% CI, 92.9-100%). Conversely, among the 61 patients with gBRCA1m and < 50% sTILs, we observed poor 15-year OS (50.8%; 95% CI, 39.7-65.0%). Furthermore, gBRCA1m was associated with higher (adjusted subdistribution HR, 4.04; 95% CI, 2.29-7.13) and tumor BRCA1-PM with lower (adjusted subdistribution HR, 0.42; 95% CI, 0.19-0.95) incidence of second primary tumors, compared to BRCA1-non-alteration. CONCLUSIONS: Although both gBRCA1m and tumor BRCA1-PM alter BRCA1 gene transcription, they are associated with different outcomes in young, node-negative, chemotherapy-naïve TNBC patients. By combining sTILs and BRCA1 status for risk classification, we were able to identify potential subgroups in this population to intensify and optimize adjuvant treatment.

Continuity of care for patients with de novo metastatic cancer during the COVID-19 pandemic: A population-based observational study.

During the COVID-19 pandemic recommendations were made to adapt cancer care. This population-based study aimed to investigate possible differences between the treatment of patients with metastatic cancer before and during the pandemic by comparing the initial treatments in five COVID-19 periods (weeks 1-12 2020: pre-COVID-19, weeks 12-20 2020: 1st peak, weeks 21-41 2020: recovery, weeks 42-53 2020: 2nd peak, weeks 1-20 2021: prolonged 2nd peak) with reference data from 2017 to 2019. The proportion of patients receiving different treatment modalities (chemotherapy, hormonal therapy, immunotherapy or targeted therapy, radiotherapy primary tumor, resection primary tumor, resection metastases) within 6 weeks of diagnosis and the time between diagnosis and first treatment were compared by period. In total, 74,208 patients were included. Overall, patients were more likely to receive treatments in the COVID-19 periods than in previous years. This mainly holds for hormone therapy, immunotherapy or targeted therapy and resection of metastases. Lower odds were observed for resection of the primary tumor during the recovery period (OR 0.87; 95% CI 0.77-0.99) and for radiotherapy on the primary tumor during the prolonged 2nd peak (OR 0.84; 95% CI 0.72-0.98). The time from diagnosis to the start of first treatment was shorter, mainly during the 1st peak (average 5 days, p < .001). These findings show that during the first 1.5 years of the COVID-19 pandemic, there were only minor changes in the initial treatment of metastatic cancer. Remarkably, time from diagnosis to first treatment was shorter. Overall, the results suggest continuity of care for patients with metastatic cancer during the pandemic.

Impact of the COVID-19 pandemic on the in-hospital diagnostic pathway of breast and colorectal cancer in the Netherlands: A population-based study.

BACKGROUND: In the Netherlands, the COVID-19 pandemic resulted in a temporary halt of population screening for cancer and limited hospital capacity for non-COVID care. We aimed to investigate the impact of the pandemic on the in-hospital diagnostic pathway of breast cancer (BC) and colorectal cancer (CRC). METHODS: 71,159 BC and 48,900 CRC patients were selected from the Netherlands Cancer Registry. Patients, diagnosed between January 2020 and July 2021, were divided into six periods and compared to the average of patients diagnosed in the same periods in 2017-2019. Diagnostic procedures performed were analysed using logistic regression. Lead time of the diagnostic pathway was analysed using Cox regression. Analyses were stratified for cancer type and corrected for age, sex (only CRC), stage and region. RESULTS: For BC, less mammograms were performed during the first recovery period in 2020. More PET-CTs were performed during the first peak, first recovery and third peak period. For CRC, less ultrasounds and more CT scans and MRIs were performed during the first peak. Lead time decreased the most during the first peak by 2 days (BC) and 8 days (CRC). Significantly fewer patients, mainly in lower stages, were diagnosed with BC (-47%) and CRC (-36%) during the first peak. CONCLUSION: Significant impact of the COVID-19 pandemic was found on the diagnostic pathway, mainly during the first peak. In 2021, care returned to the same standards as before the pandemic. Long-term effects on patient outcomes are not known yet and will be the subject of future research.

European quality indicators developed by the European Commission Initiative on Breast Cancer: a first nationwide assessment for the Dutch setting.

PURPOSE: This observational study aims to assess the feasibility of calculating indicators developed by the European Commission Initiative on Breast Cancer (ECIBC) for the Dutch breast cancer population. METHODS: Patients diagnosed with invasive or in situ breast cancer between 2012 and 2018 were selected from the Netherlands Cancer Registry (NCR). Outcomes of the quality indicators (QI) were presented as mean scores and were compared to a stated norm. Variation between hospitals was assessed by standard deviations and funnel plots and trends over time were evaluated. The quality indicator calculator (QIC) was validated by comparing these outcomes with the outcomes of constructed algorithms in Stata. RESULTS: In total, 133,527 patients were included. Data for 24 out of 26 QIs were available in the NCR. For 67% and 67% of the QIs, a mean score above the norm and low or medium hospital variation was observed, respectively. The proportion of patients undergoing a breast reconstruction or neoadjuvant systemic therapy increased over time. The proportion treated within 4 weeks from diagnosis, having >10 lymph nodes removed or estrogen negative breast cancer who underwent adjuvant chemotherapy decreased. The outcomes of the constructed algorithms in this study and the QIC showed 100% similarity. CONCLUSION: Data from the NCR could be used for the calculation of more than 92% of the ECIBC indicators. The quality of breast cancer care in the Netherlands is high, as more than half of the QIs already score above the norm and medium hospital variation was observed. The QIC can be easy and reliably applied.

Prognostic effect of nodal status before and after neoadjuvant chemotherapy in breast cancer: a Dutch population-based study.

PURPOSE: In breast cancer, neoadjuvant chemotherapy (NAC) can downstage the nodal status, and can even result in a pathological complete response, which is associated with improved prognosis. This study aimed to determine the prognostic effect of nodal status before and after NAC. METHODS: Women with breast cancer treated with NAC were selected from the Netherlands Cancer Registry if diagnosed between 2005 and 2019, and classified based on nodal status before NAC: node-negative (cN0), or node-positive based on fine needle aspiration cytology or core needle biopsy (cN+). Subgroups were based on nodal status after NAC: absence (ypN0) or presence (ypN+) of nodal disease. Five-year overall survival (OS) was assessed with Kaplan-Meier survival analyses, also per breast cancer molecular subtype. To adjust for potential confounders, multivariable analyses were performed. RESULTS: A total of 6,580 patients were included in the cN0 group, and 11,878 in the cN+ group. The 5-year OS of the cN0ypN0-subgroup was statistically significant better than that of the cN+ypN0-subgroup (94.4% versus 90.1%, p < 0.0001). In cN0 as well as cN+ disease, ypN+ had a statistically significant worse 5-year OS compared to ypN0. For hormone receptor (HR)+ human epidermal growth factor receptor 2 (HER2)-, HR+ HER2+, HR-HER2+, and triple negative disease, respectively, 5-year OS in the cN0ypN+-subgroup was 89.7%, 90.4%, 73.7%, and 53.6%, and in the cN+ypN+-subgroup 84.7%, 83.2%, 61.4%, and 48.8%. In multivariable analyses, cN+ and ypN+ disease were both associated with worse OS. CONCLUSION: This study suggests that both cN-status and ypN-status, and molecular subtype should be considered to further improve prognostication.

Reduction in potentially inappropriate end-of-life hospital care for cancer patients during the COVID-19 pandemic: A retrospective population-based study.

BACKGROUND: The COVID-19 pandemic impacted cancer diagnosis and treatment. However, little is known about end-of-life cancer care during the pandemic. AIM: To investigate potentially inappropriate end-of-life hospital care for cancer patients before and during the COVID-19 pandemic. DESIGN: Retrospective population-based cohort study using data from the Netherlands Cancer Registry and the Dutch National Hospital Care Registration. Potentially inappropriate care in the last month of life (chemotherapy administration, >1 emergency room contact, >1 hospitalization, hospitalization >14 days, intensive care unit admission or hospital death) was compared between four COVID-19 periods and corresponding periods in 2018/2019. PARTICIPANTS: A total of 112,919 cancer patients (⩾18 years) who died between January 2018 and May 2021 were included. RESULTS: Fewer patients received potentially inappropriate end-of-life care during the COVID-19 pandemic compared to previous years, especially during the first COVID-19 peak (22.4% vs 26.0%). Regression analysis showed lower odds of potentially inappropriate end-of-life care during all COVID-19 periods (between OR 0.81; 95% CI 0.74-0.88 and OR 0.92; 95% CI 0.87-0.97) after adjustment for age, sex and cancer type. For the individual indicators, fewer patients experienced multiple or long hospitalizations, intensive care unit admission or hospital death during the pandemic. CONCLUSIONS: Cancer patients received less potentially inappropriate end-of-life care during the COVID-19 pandemic. Because several factors may have contributed, it is unclear whether this reflects better quality care. However, these findings raise important questions about what pandemic-induced changes in care practices can help provide appropriate end-of-life care for future patients in the context of increasing patient numbers and limited resources.

Development of machine learning models to predict cancer-related fatigue in Dutch breast cancer survivors up to 15 years after diagnosis.

PURPOSE: To prevent (chronic) cancer-related fatigue (CRF) after breast cancer, it is important to identify survivors at risk on time. In literature, factors related to CRF are identified, but not often linked to individual risks. Therefore, our aim was to predict individual risks for developing CRF. METHODS: Two pre-existing datasets were used. The Nivel-Primary Care Database and the Netherlands Cancer Registry (NCR) formed the Primary Secondary Cancer Care Registry (PSCCR). NCR data with Patient Reported Outcomes Following Initial treatment and Long-term Evaluation of Survivorship (PROFILES) data resulted in the PSCCR-PROFILES dataset. Predictors were patient, tumor and treatment characteristics, and pre-diagnosis health. Fatigue was GP-reported (PSCCR) or patient-reported (PSCCR-PROFILES). Machine learning models were developed, and performances compared using the C-statistic. RESULTS: In PSCCR, 2224/12813 (17%) experienced fatigue up to 7.6 ± 4.4 years after diagnosis. In PSCCR-PROFILES, 254 (65%) of 390 patients reported fatigue 3.4 ± 1.4 years after diagnosis. For both, models predicted fatigue poorly with best C-statistics of 0.561 ± 0.006 (PSCCR) and 0.669 ± 0.040 (PSCCR-PROFILES). CONCLUSION: Fatigue (GP-reported or patient-reported) could not be predicted accurately using available data of the PSCCR and PSCCR-PROFILES datasets. IMPLICATIONS FOR CANCER SURVIVORS: CRF is a common but underreported problem after breast cancer. We aimed to develop a model that could identify individuals with a high risk of developing CRF, ideally to help them prevent (chronic) CRF. As our models had poor predictive abilities, they cannot be used for this purpose yet. Adding patient-reported data as predictor could lead to improved results. Until then, awareness for CRF stays crucial.

A holistic profile for cancer-related fatigue for women with breast cancer - a qualitative study.

Objective: Cancer- related fatigue (CRF) is one of the most reported long-term effects after breast cancer and severely impacts quality of life. To come towards optimal treatment of multidimensional CRF, the first step is to use a holistic approach to develop a holistic patient profile including the patient's experience and impact of CRF on their life. Methods and measures: Four semi- structured focus groups with twenty- seven breast cancer patients and fourteen interviews with healthcare professionals (HCPs) were held. Reflexive thematic analysis was used to define (sub)themes for the holistic patient profile. The themes of the interviews and focus groups were compared for validity. Results: Breast cancer patients and HCPs described the same five major themes, consisting of experience of CRF, impact and consequences, coping, personality, and CRF treatment. Experience of CRF consists of cognitive, emotional, and physical aspects. Impact and consequences include work, family, partner relation, social contact and hobbies, body, and misunderstanding. Coping consists of twelve (mal)adaptive strategies. Personality and CRF treatment were summarised as themes. Conclusions: A first holistic patient profile was introduced for CRF for breast cancer. This profile can be conceptualized into a questionnaire to collect information for personalized treatment recommendations and monitoring of CRF over time.

Method of primary breast cancer detection and the disease-free interval, adjusting for lead time.

BACKGROUND: Little is known about the impact of screen-detected breast cancer compared with clinically-detected breast cancer on the disease-free interval (i.e. free from locoregional recurrences, distant metastasis, contralateral breast cancer). Moreover, it is thought that most studies overestimate the beneficial effect of screening, as they do not adjust for lead time. We investigated the association between method of breast cancer detection and disease-free interval, taking lead time into account. METHOD: Women, 50-76 years old, diagnosed with breast cancer between 2005-2008 were selected from the Netherlands Cancer Registry. Women diagnosed in 2005 were divided into screen-detected and clinically-detected cancer and had a follow-up of ten-years (2005 cohort). Women diagnosed in 2006-2008 were divided into screen-detected, interval, and non-screen-related cancer, and had a follow-up of five years (2006-2008 cohort). A previously published method was used to adjust for lead time. Analyses were repeated correcting for confounding variables instead of lead time. RESULTS: The 2005 cohort included 6,215 women. Women with screen-detected cancer had an improved disease-free interval compared to women with clinically-detected cancer (HR: 0.77, 95% CI: 0.68 to 0.87). The 2006-2008 cohort included 15,176 women. Women with screen-detected or interval cancer had an improved disease-free interval compared to women with non-screen-related cancer (HR: 0.76, 95% CI: 0.66 to 0.88; HR: 0.88, 95% CI: 0.78 to 0.99, respectively). Correcting for confounders instead of lead-time did not change associations. CONCLUSION: Women with screen-detected cancer had an improved disease-free interval compared to women with a non-screen-related or clinically-detected cancer, after correction for lead time.

External validation and clinical utility assessment of PREDICT breast cancer prognostic model in young, systemic treatment-naïve women with node-negative breast cancer.

BACKGROUND: The validity of the PREDICT breast cancer prognostic model is unclear for young patients without adjuvant systemic treatment. This study aimed to validate PREDICT and assess its clinical utility in young women with node-negative breast cancer who did not receive systemic treatment. METHODS: We selected all women from the Netherlands Cancer Registry who were diagnosed with node-negative breast cancer under age 40 between 1989 and 2000, a period when adjuvant systemic treatment was not standard practice for women with node-negative disease. We evaluated the calibration and discrimination of PREDICT using the observed/expected (O/E) mortality ratio, and the area under the receiver operating characteristic curve (AUC), respectively. Additionally, we compared the potential clinical utility of PREDICT for selectively administering chemotherapy to the chemotherapy-to-all strategy using decision curve analysis at predefined thresholds. RESULTS: A total of 2264 women with a median age at diagnosis of 36 years were included. Of them, 71.2% had estrogen receptor (ER)-positive tumors and 44.0% had grade 3 tumors. Median tumor size was 16 mm. PREDICT v2.2 underestimated 10-year all-cause mortality by 33% in all women (O/E ratio:1.33, 95%CI:1.22-1.43). Model discrimination was moderate overall (AUC10-year:0.65, 95%CI:0.62-0.68), and poor for women with ER-negative tumors (AUC10-year:0.56, 95%CI:0.51-0.62). Compared to the chemotherapy-to-all strategy, PREDICT only showed a slightly higher net benefit in women with ER-positive tumors, but not in women with ER-negative tumors. CONCLUSIONS: PREDICT yields unreliable predictions for young women with node-negative breast cancer. Further model updates are needed before PREDICT can be routinely used in this patient subset.

5-year adherence to adjuvant endocrine treatment in Dutch women with early stage breast cancer: A population-based database study (2006-2016).

BACKGROUND: Hormonal receptor (HR) positive breast tumors are common. Adjuvant hormonal therapy (AHT) with tamoxifen or Aromatase Inhibitors (AIs) is beneficial depending on the stage of the tumor. Despite the fact that AHT has been shown to improve survival and recurrence, Dutch adherence rates, which were mostly dependent on Tamoxifen prescriptions until 2006, plummeted from 80% after one year to 50% after five years. Nonadherence with AHT reduces its effectiveness. This research presents more recent adherence statistics (from 2006 to 2016), on a larger sample (7,996 vs 1,451), as well as factors that influence AHT adherence. In addition to tamoxifen data, AIs are now included. OBJECTIVE: As low use of adjuvant endocrine therapy is a potentially important and modifiable risk factor for poor outcome, it is important to monitor the rate as an indicator of women's burden of disease and the direction of adherence trends. METHODS: The Netherlands Cancer Registry (NCR) was used to find women with early-stage breast cancer who started AHT within a year of surgery and were linked to the PHARMO Database Network (n = 8,679). The Kaplan-Meier approach was used to measure AHT adherence five years after treatment was started, with a 60-day gap between refills as our primary outcome. Furthermore, the Medication Possession Rate (MPR) was determined using a cutoff of ≥80%. Analysis was performed on influential factors of adherence. RESULTS: The proportion of persistent women declined over time to reach 46.6% at the end of the fifth year and 53.3% of the women had a MPR ≥80% during the fifth year. Older and being diagnosed in 2006-2010 were associated with AHT adherence. CONCLUSION: Dutch 5-year AHT adherence appears to remain poor. Improving AHT adherence in HR+ breast cancer survivors is a critical medical need.

Prolonged screening interval due to the COVID-19 pandemic and its association with tumor characteristics and treatment; a register-based study from BreastScreen Norway.

OBJECTIVE: During the COVID-19 pandemic Norway had to suspend its national breast cancer screening program. We aimed to investigate the effect of the pandemic-induced suspension on the screening interval, and its subsequent association with the tumor characteristics and treatment of screen-detected (SDC) and interval breast cancer (IC). METHODS: Information about women aged 50-69, participating in BreastScreen Norway, and diagnosed with a SDC (N = 3799) or IC (N = 1806) between 2018 and 2021 was extracted from the Cancer Registry of Norway. Logistic regression was used to investigate the association between COVID-19 induced prolonged screening intervals and tumor characteristics and treatment. RESULTS: Women with a SDC and their last screening exam before the pandemic had a median screening interval of 24.0 months (interquartile range: 23.8-24.5), compared to 27.0 months (interquartile range: 25.8-28.5) for those with their last screening during the pandemic. The tumor characteristics and treatment of women with a SDC, last screening during the pandemic, and a screening interval of 29-31 months, did not differ from those of women with a SDC, last screening before the pandemic, and a screening interval of 23-25 months. ICs detected 24-31 months after screening, were more likely to be histological grade 3 compared to ICs detected 0-23 months after screening (odds ratio: 1.40, 95% confidence interval: 1.06-1.84). CONCLUSIONS: Pandemic-induced prolonged screening intervals were not associated with the tumor characteristics and treatment of SDCs, but did increase the risk of a histopathological grade 3 IC. This study provides insights into the possible effects of extending the screening interval.

Impact of the COVID-19 pandemic on breast cancer incidence and tumor stage in the Netherlands and Norway: A population-based study.

BACKGROUND: Comparing the impact of the COVID-19 pandemic on the incidence of newly diagnosed breast tumors and their tumor stage between the Netherlands and Norway will help us understand the effect of differences in governmental and social reactions towards the pandemic. METHODS: Women newly diagnosed with breast cancer in 2017-2021 were selected from the Netherlands Cancer Registry and the Cancer Registry of Norway. The crude breast cancer incidence rate (tumors per 100,000 women) during the first (March-September 2020), second (October 2020-April 2021), and Delta COVID-19 wave (May-December 2021) was compared with the incidence rate in the corresponding periods in 2017, 2018, and 2019. Incidence rates were stratified by age group, method of detection, and clinical tumor stage. RESULTS: During the first wave breast cancer incidence declined to a larger extent in the Netherlands than in Norway (27.7% vs. 17.2% decrease, respectively). In both countries, incidence decreased in women eligible for screening. In the Netherlands, incidence also decreased in women not eligible for screening. During the second wave an increase in the incidence of stage IV tumors in women aged 50-69 years was seen in the Netherlands. During the Delta wave an increase in overall incidence and incidence of stage I tumors was seen in Norway. CONCLUSION: Alterations in breast cancer incidence and tumor stage seem related to a combined effect of the suspension of the screening program, health care avoidance due to the severity of the pandemic, and other unknown factors.

Characterization of the Tumor Microenvironment of De Novo Oligometastatic Breast Cancer in a Nationwide Cohort.

PURPOSE: Oligometastatic breast cancer (OMBC) has a more favorable outcome than widespread metastatic breast cancer. Some patients with OMBC achieve long-term remission if treated with multimodality therapy, including systemic and locally ablative therapies. However, not all patients with OMBC benefit from such treatment, while all experience toxicity. To explore biomarkers identifying patients with OMBC and potential long-term survival, we compared tumor-immune characteristics of patients with OMBC and long-term versus shorter-term survival. MATERIALS AND METHODS: We collected tumor tissue of 97 patients with de novo OMBC (≤5 metastases) via the Dutch nationwide cancer and pathology registries using a case-control design. Long-term survivors (LTS) were defined as patients alive ≥10 years since OMBC diagnosis. Fifty-five LTS and 42 shorter-term survivors (STS) were included. Median follow-up was 15 years (IQR, 14-16). Tumor characteristics and infiltrating immune cells were assessed by immunohistochemistry and next-generation RNA-sequencing. Association of the resulting 52 biomarkers with long-term survival was assessed using logistic regression. Associations with survival within LTS were assessed using Cox-proportional hazards modeling. P values were adjusted for multiple hypothesis testing. RESULTS: Most patients had estrogen receptor (ER)-positive OMBC (n = 86; 89%) and 23 (24%) had human epidermal growth factor receptor 2-positive disease. ER positivity in primary tumors distinguished LTS from STS. In addition, extracellular matrix (ECM)2-low and ECM4-high distinguished between long-term and shorter-term survival. Immune levels in the primary tumor did not associate with LTS. However, within the LTS subset, higher immune levels associated with improved progression-free survival. CONCLUSION: We identified tumor and ECM features in the primary tumor of patients with de novo OMBC that were associated with long-term survival. Our data should be validated in other patients with OMBC before they can be used in clinical practice.

Validation and Clinical Utility of a Prediction Model for the Risk of Upstaging to Invasive Breast Cancer After a Biopsy Diagnosis Ductal Carcinoma In Situ.

BACKGROUND: This study aimed to validate the DCIS-upstage model, a previously developed model to predict the risk of upstaging to invasive breast cancer in patients with biopsy-proven ductal carcinoma in situ (DCIS) in a more recent cohort and to assess the model's clinical utility. METHODS: The model was validated in a registry cohort (n = 2269) and in an institution cohort (n = 302). A calibration plot was made, followed by a decision curve analysis (DCA). The model's area under the curve (AUC) was compared with the AUC of another published model and with the AUCs of new models using the risk factors of the DCIS-upstage model and additional risk factors. RESULTS: The DCIS-upstage model had an AUC of 0.67 at development; in the validation, the AUC was 0.65 in the registry cohort and 0.73 in the institution cohort. The DCA showed that the model has clinical utility. The other published model had an AUC of 0.66 in the institution cohort. Adding risk factors to the DCIS-upstage model slightly increased the AUC. CONCLUSIONS: The DCIS-upstage prediction model is valid in other cohorts. The model has clinical utility and may be used to select patients with biopsy-proven DCIS for sentinel lymph node biopsy.