Quality assessment of radiotherapy in the prospective randomized SENOMAC trial.

BACKGROUND AND PURPOSE: Recommendations for regional radiotherapy (RT) of sentinel lymph node (SLN)-positive breast cancer are debated. We here report a RT quality assessment of the SENOMAC trial. MATERIALS AND METHODS: The SENOMAC trial randomized clinically node-negative breast cancer patients with 1-2 SLN macrometastases to completion axillary lymph node dissection (cALND) or SLN biopsy only between 2015-2021. Adjuvant RT followed national guidelines. RT plans for patients included in Sweden and Denmark until June 2019 were collected (N = 1176) and compared to case report forms (CRF). Dose to level I (N = 270) and the humeral head (N = 321) was analyzed in detail. RESULTS: CRF-data and RT plans agreed in 99.3 % (breast/chest wall) and in 96.6 % of patients (regional RT). Congruence for whether level I was an intended RT target was lower (78 %). In accordance with Danish national guidelines, level I was more often an intended target in the SLN biopsy only arm (N = 334/611, 55 %,) than in the cALND arm (N = 174/565, 31 %,). When an intended target, level I received prescribed dose to 100 % (IQR 98-100 %) of the volume. However, even when not an intended target, full dose was delivered to > 80 % of level I (IQR 75-90 %). The intentional inclusion of level I in the target volume more than doubled the dose received by ≥ 50 % of the humeral head. CONCLUSION: Congruence between CRF data and RT plans was excellent. Level I received a high dose coverage even when not intentionally included in the target. Including level I in target significantly increased dose to the humeral head.

A national repository of complete radiotherapy plans: design, Results, and experiences.

BACKGROUND: Previously, many radiotherapy (RT) trials were based on a few selected dose measures. Many research questions, however, rely on access to the complete dose information. To support such access, a national RT plan database was created. The system focuses on data security, ease of use, and re-use of data. This article reports on the development and structure, and the functionality and experience of this national database. METHODS AND MATERIALS: A system based on the DICOM-RT standard, DcmCollab, was implemented with direct connections to all Danish RT centres. Data is segregated into any number of collaboration projects. User access to the system is provided through a web interface. The database has a finely defined access permission model to support legal requirements. RESULTS: Currently, data for more than 14,000 patients have been submitted to the system, and more than 50 research projects are registered. The system is used for data collection, trial quality assurance, and audit data set generation.Users reported that the process of submitting data, waiting for it to be processed, and then manually attaching it to a project was resource intensive. This was accommodated with the introduction of triggering features, eliminating much of the need for users to manage data manually. Many other features, including structure name mapping, RT plan viewer, and the Audit Tool were developed based on user input. CONCLUSION: The DcmCollab system has provided an efficient means to collect and access complete datasets for multi-centre RT research. This stands in contrast with previous methods of collecting RT data in multi-centre settings, where only singular data points were manually reported. To accommodate the evolving legal environment, DcmCollab has been defined as a 'data processor', meaning that it is a tool for other research projects to use rather than a research project in and of itself.

Development of a national deep learning-based auto-segmentation model for the heart on clinical delineations from the DBCG RT nation cohort.

BACKGROUND: This study aimed at investigating the feasibility of developing a deep learning-based auto-segmentation model for the heart trained on clinical delineations. MATERIAL AND METHODS: This study included two different datasets. The first dataset contained clinical heart delineations from the DBCG RT Nation study (1,561 patients). The second dataset was smaller (114 patients), but with corrected heart delineations. Before training the model on the clinical delineations an outlier-detection was performed, to remove cases with gross deviations from the delineation guideline. No outlier detection was performed for the dataset with corrected heart delineations. Both models were trained with a 3D full resolution nnUNet. The models were evaluated with the dice similarity coefficient (DSC), 95% Hausdorff distance (HD95) and Mean Surface Distance (MSD). The difference between the models were tested with the Mann-Whitney U-test. The balance of dataset quantity versus quality was investigated, by stepwise reducing the cohort size for the model trained on clinical delineations. RESULTS: During the outlier-detection 137 patients were excluded from the clinical cohort due to non-compliance with delineation guidelines. The model trained on the curated clinical cohort performed with a median DSC of 0.96 (IQR 0.94-0.96), median HD95 of 4.00 mm (IQR 3.00 mm-6.00 mm) and a median MSD of 1.49 mm (IQR 1.12 mm-2.02 mm). The model trained on the dedicated and corrected cohort performed with a median DSC of 0.95 (IQR 0.93-0.96), median HD95 of 5.65 mm (IQR 3.37 mm-8.62 mm) and median MSD of 1.63 mm (IQR 1.35 mm-2.11 mm). The difference between the two models were found non-significant for all metrics (p > 0.05). Reduction of cohort size showed no significant difference for all metrics (p > 0.05). However, with the smallest cohort size, a few outlier structures were found. CONCLUSIONS: This study demonstrated a deep learning-based auto-segmentation model trained on curated clinical delineations which performs on par with a model trained on dedicated delineations, making it easier to develop multi-institutional auto-segmentation models.

Diagnosis and treatment of breast cancer in Denmark during the COVID-19 pandemic: a nationwide population-based study.

BACKGROUND: The COVID-19 pandemic was a global health crisis with population-wide behavioural restrictions imposed worldwide to reduce transmission of infection and to limit the potential burden on the healthcare systems. We examined whether there was any change in the diagnosis or treatment of breast cancer during the pandemic as compared to previous years. MATERIAL AND METHODS: The study population comprised all women aged ≥18 years diagnosed with breast cancer in 2015-2021 with data obtained from the clinical quality registry of the Danish Breast Cancer Cooperative Group (DBCG). Data on socioeconomic factors were retrieved from Statistics Denmark. Prevalence ratios (PR) with 95% confidence intervals (CI) were estimated from a generalised linear model (GLM) with a log link for the Poisson family with robust standard errors (SE) of each outcome, using the COVID-19 pandemic period in Denmark as the exposure of interest. RESULTS: In total, 30,598 breast cancers were diagnosed during the study period. There was a small decrease (4.5%) in the total number of breast cancer cases in 2020 compared with previous years. During the pandemic, a lower proportion of the patients diagnosed with breast cancer had a short educational level (28.5 vs. 26.9%; PR = 0.91; 95% CI: 0.88-0.95), a low income (20.5 vs. 19.0%; PR = 0.90; 0.85-0.95) and fewer than expected in the age group 60-69 years (27.8 vs. 25.3; PR = 0.90; 0.86-0.94) were diagnosed, as compared with the pre-pandemic period. No difference in type of surgery or tumour size was observed. A higher proportion of patients received neo-adjuvant chemotherapy (49.0 vs 55.0%; PR = 1.15; 1.06-1.24), whereas a lower proportion received adjuvant chemotherapy (93.5 vs 85.6%; PR = 0.92; 0.90-0.93) during the pandemic, compared with the pre-pandemic period. CONCLUSIONS: During the pandemic, a small decrease in the number of breast cancer diagnoses was observed particularly among socially disadvantaged groups. Overall, the quality of breast cancer treatment was maintained.

Prognosis of breast cancer patients with brain metastasis treated with radiotherapy.

BACKGROUND: Life expectancy for patients diagnosed with metastatic breast cancer (BC) has improved in recent years, especially due to better systemic treatment. This has led to an increased incidence of brain metastases (BM), and BC is now the leading cause of BM in women. Treatment of BM primarily consists of surgery and/or radiotherapy. We aimed to investigate survival time and prognostic factors for BC patients treated with radiotherapy for BM. MATERIAL & METHODS: During the period 1st of January 2015 to 1st of June 2020, 144 consecutive BC patients treated for BM from one centre were retrospectively analyzed. The patients were either diagnosed with BM as the first metastatic lesion, or developed BM during palliative therapy for distant non-brain metastasis. The study was approved by the Central Denmark Region. RESULTS: Median age at BM diagnosis was 66 years, and 90% of the patients already had extracranial metastatic disease at BM diagnosis. Median overall survival after diagnosis of BM was 6.1 months. Short survival was observed for patients with poor performance status, leptomeningeal metastasis or more than three solid BM. Several of these factors were overrepresented in patients with estrogen receptor-positive (ER+) tumours who had poorer survival than patients with different receptor status. CONCLUSION: The number of metastatic BC patients developing BM is high, and survival following local treatment remains poor. Several prognostic factors appear to influence survival after radiotherapy. Treatment of BC patients with BM should be individualized according to performance status, leptomeningeal disease, number of BM, and receptor status of the disease.

Radiation dose to heart and cardiac substructures and risk of coronary artery disease in early breast cancer patients: A DBCG study based on modern radiation therapy techniques.

BACKGROUND: Coronary artery disease (CAD) has been reported as a late effect following radiation therapy (RT) of early breast cancer (BC). This study aims to report individual RT doses to the heart and cardiac substructures in patients treated with CT-based RT and to investigate if a dose-response relationship between RT dose and CAD exists using modern radiation therapy techniques. METHODS: Patients registered in the Danish Breast Cancer Group database from 2005 to 2016 with CT-based RT were eligible. Among 15,765 patients, the study included 204 with CAD after irradiation (cases) and 408 matched controls. Individual planning CTs were retrieved, the heart and cardiac substructures were delineated and dose-volume parameters were extracted. RESULTS: The median follow-up time was 7.3 years (IQR: 4.6-10.0). Among cases, the median mean heart dose was 1.6 Gy (IQR 0.2-6.1) and 0.8 Gy (0.1-2.9) for left-sided and right-sided patients, respectively (p < 0.001). The highest RT doses were observed in the left ventricle and left anterior descending coronary artery for left-sided RT and in the right atrium and the right coronary artery after right-sided RT. The highest left-minus-right dose-difference was located in the distal part of the left anterior descending coronary artery where also the highest left-versus-right ratio of events was observed. However, no significant difference in the distribution of CAD was observed by laterality. Furthermore, no significant differences in the dose-volume parameters were observed for cases versus controls. CONCLUSIONS: CAD tended to occur in the part of the heart with the highest left-minus- right dose difference, however, no significant risk of CAD was observed at 7 years' median follow-up.

Patient-reported outcomes one year after positive sentinel lymph node biopsy with or without axillary lymph node dissection in the randomized SENOMAC trial.

INTRODUCTION: This report evaluates whether health related quality of life (HRQoL) and patient-reported arm morbidity one year after axillary surgery are affected by the omission of axillary lymph node dissection (ALND). METHODS: The ongoing international non-inferiority SENOMAC trial randomizes clinically node-negative breast cancer patients (T1-T3) with 1-2 sentinel lymph node (SLN) macrometastases to completion ALND or no further axillary surgery. For this analysis, the first 1181 patients enrolled in Sweden and Denmark between March 2015, and June 2019, were eligible. Data extraction from the trial database was on November 2020. This report covers the secondary outcomes of the SENOMAC trial: HRQoL and patient-reported arm morbidity. The EORTC QLQ-C30, EORTC QLQ-BR23 and Lymph-ICF questionnaires were completed in the early postoperative phase and at one-year follow-up. Adjusted one-year mean scores and mean differences between the groups are presented corrected for multiple testing. RESULTS: Overall, 976 questionnaires (501 in the SLN biopsy only group and 475 in the completion ALND group) were analysed, corresponding to a response rate of 82.6%. No significant group differences in overall HRQoL were identified. Participants receiving SLN biopsy only, reported significantly lower symptom scores on the EORTC subscales of pain, arm symptoms and breast symptoms. The Lymph-ICF domain scores of physical function, mental function and mobility activities were significantly in favour of the SLN biopsy only group. CONCLUSION: One year after surgery, arm morbidity is significantly worse affected by ALND than by SLN biopsy only. The results underline the importance of ongoing attempts to safely de-escalate axillary surgery. TRIAL REGISTRATION: The trial was registered at clinicaltrials.gov prior to initiation (https://clinicaltrials.gov/ct2/show/NCT02240472).

Symptom trajectories in breast cancer survivors: growth mixture analysis of patient-reported pain, fatigue, insomnia, breast and arm symptoms.

BACKGROUND: Variations in symptom development among breast cancer (BC) survivors are understudied. We examined: (Q1) Symptom trajectories of pain, fatigue, insomnia, breast, and arm symptoms in BC survivors, (Q2) possible patterns or cluster-like associations between trajectory classification of different symptoms, and (Q3) characteristics of survivors assigned to high-burden symptom trajectories. MATERIAL AND METHODS: Participants were 968 women (mean age = 59.6 years) treated for early-stage BC and followed across a three-year postoperative period. As part of routine follow-up procedures, patients reported symptom burden and functioning levels at each hospital visit using the European Organisation for Research and Treatment of Cancer (EORTC) Quality of Life Questionnaire (QLQ-C30) and the BC-specific module (QLQ-BR-23). Growth mixture modeling (GMM) analysis was used to differentiate potential subgroups of individuals with similar longitudinal symptom patterns, i.e., symptom trajectories (Q1). With this approach, groups experiencing persistent, highly distressing cancer- and treatment-related late effects (LEs) may be identified. Latent class analysis (LCA) was used for Q2 and logistic regression analysis for Q3. RESULTS: GMM identified two relatively parallel trajectories across the tested symptoms: The majority of the sample exhibited a low-burden symptom trajectory (74.4-89.2%) and a minority by a high-burden symptom trajectory (10.8-25.6%). LCA revealed that approximately one in five women (18.8%) were likely to be members of the high-burden symptom trajectory across all tested symptoms. In addition to a high probability of being burdened over time across multiple symptoms, these women were also characterized by poorer self-reported physical and social functioning. CONCLUSION: A substantial minority followed a high-burden symptom trajectory for several years following BC treatment. Associations were found in trajectory classification across symptoms, indicating that cancer-related LEs appear in clusters of multiple concurrent symptoms.

ESTRO ACROP consensus guideline for target volume delineation in the setting of postmastectomy radiation therapy after implant-based immediate reconstruction for early stage breast cancer.

Immediate breast reconstruction (IBR) rates after mastectomy are increasing. Postmastectomy radiation therapy (PMRT) contouring guidelines for target volumes in the setting of IBR are lacking. Therefore, many patients who have had IBR receive PMRT to target volumes similar to conventional simulator-based whole breast irradiation. The aim of this paper is to describe delineation guidelines for PMRT after implant-based IBR based on a thorough understanding of the surgical procedures, disease stage, patterns of recurrence and radiation techniques. They are based on a consensus endorsed by a global multidisciplinary group of breast cancer experts.

A validated algorithm for register-based identification of patients with recurrence of breast cancer-Based on Danish Breast Cancer Group (DBCG) data.

BACKGROUND: Cancer recurrence is not routinely and completely registered in Danish national health registers, which challenges register-based research. The aim of this study was to develop and validate a register-based algorithm to identify patients with recurrence of breast cancer (BC). METHODS: We conducted a cohort study based on data from Danish national health registers and used the Danish National Patient Register and the Danish National Pathology Register as sources to identify BC recurrence. We used data from the Danish Breast Cancer Group (DBCG) validated against medical records on recurrence status and recurrence date for 471 women with early stage unilateral BC as the gold standard of BC recurrence to assess the accuracy of the algorithm to identify BC recurrence. RESULTS: The algorithm displayed a sensitivity of 97.3% (95% confidence interval (CI): 93.2-99.3), a specificity of 97.2% (95% CI: 94.8-98.7) and a positive predictive value of 94.4% (95% CI: 89.2-97.3). The concordance correlation coefficient for the agreement between recurrence dates generated by the algorithm and the gold standard was 0.97 (95% CI: 0.96-0.98), and the date was estimated within +/-30 days of the gold standard in 66% of the patients and within +/-60 days in 76% of the patients. CONCLUSION: The developed algorithm almost perfectly identified BC recurrence and with reasonable timing compared to the gold standard.