ABSTRACT
Background: The COVID-19 pandemic has significantly reduced routinely scheduled in person assessment and examination of early breast cancer patients (EBC). To assess if this is likely to impact the detection of recurrent disease, we reviewed recurrence patterns of EBC patients enrolled in a survivorship program that adheres to ASCO guidelines. Methods: Charts of EBC patients transferred through a single center Wellness Beyond Cancer Program (WBCP) and who subsequently had a breast cancer recurrence between February 1, 2013 and January 1, 2019 were reviewed. Patient, tumor and treatment characteristics were evaluated. Results: Of 206 patients eligible for the current study, 41 patients had ipsilateral breast recurrences (19.9%), 135 had distant recurrences (65.5%) and 30 had contralateral new breast cancers (14.6%). Ipsilateral breast recurrences were detected by the patient in 53.7% (22/41) and by routine imaging in 41.5% (17/21). The majority of distant recurrences (125/135, 92.6%) were detected via patient-reported symptoms. Contralateral breast primaries were detected by patients 16.7% (5/30) or by routine imaging (83.3%, 25/30). Only 2/206 (1.14%) recurrences/new primaries were detected by healthcare providers at routinely scheduled follow-up visits. There was a statistical difference in recurrence detection between image detected vs. self-detected in the following factors: grade 3 (26.5% vs 51%, p < 0.007), triple negative breast cancer (3.9% vs. 15.1%, p = 0.03), HER2 disease (18.4% vs. 9.8%, p = 0.04). Conclusions: Despite following ASCO follow-up guidelines for routinely scheduled follow-up appointments with physical examination, healthcare providers rarely detect recurrence disease. While reduced in person visits may affect other aspects of follow- up (e.g., toxicity management), it appears unlikely, provided patients attend regular screening tests, that reduced in-person follow-up is associated with worse breast cancer-related outcomes during the COVID-19 pandemic.
ABSTRACT
The optimal timing of commencing adjuvant endocrine therapy (ET) relative to adjuvant radiotherapy (RT) (i.e. concurrent with or sequential to radiotherapy) remains unknown. A systematic review performed by our team was unable to answer this question due to a lack of high quality, randomized data on concurrent versus sequential ET and RT. Surveys of physicians confirmed this uncertainty and highlighted theoretical concerns for increased side effects with concurrent treatment. Respondents showed keen interest in obtaining real world, randomized data to guide clinical practice. REaCT-RETT is a pragmatic, randomized, non-inferiority trial comparing concurrent and sequential ET and RT in early breast cancer (EBC). The primary endpoint will assess the change in ET side effects at baseline and 3 months post radiation, using the Functional Assessment of Cancer Therapy-Endocrine Subscale (FACT-ES), with primary analysis based on an analysis of covariance (ANCOVA). With a sample size of 176 patients (88 per arm), an ANCOVA would have 80% power (α=0.05) to detect effect sizes as small as 0.25 regardless of the correlation with covariates. It is hypothesized that concurrent therapy will be non-inferior to sequential therapy in terms of ET side effects. Secondary endpoints will examine RT toxicity, ET compliance, quality of S life, and cost-effectiveness. Patients with HR positive EBC planned to receive both adjuvant ET and RT were eligible. Patients who previously received ET for invasive breast cancer, or RT in the same breast, were excluded. The trial is conducted by The Ottawa Hospital's (TOH) innovative Rethinking Clinical Trials (REaCT) program (https://react.ohri.ca/) which strives to improve access to patient-centered, pragmatic clinical trials by removing barriers for patients and researchers. Integral features of the program include broad eligibility criteria, a verbal consent model, and pragmatic data collection and assessment procedures. REaCT is the largest pragmatic cancer clinical trials program in Canada, with over 3, 200 patients randomized in 18 clinical trials at 15 sites across Canada. REaCT-RETT accrued patients from September 2019 to January 2021. Data collection is ongoing, with final patient follow up expected April 2022. The timing of accrual provided a unique opportunity to adapt in response to restrictions due to the COVID-19 pandemic, which began to impact trial sites in March 2020. The target sample size was met with 262 patients randomized (1:1) across 3 sites in Ontario, 98% from TOH. A mean of 19 patients/month were accrued prior to the pandemic, compared to a mean of 13 patients/month after March 2020. Twenty-two patients were removed due to withdrawal of consent, ineligibility, or physician choice, and the pandemic was not a significant contributing factor. Since March 2020 there have been 772 patient follow ups, of which 47% (364/772) have been virtual. Only 10% (102/1028) of trial mandated appointments have been missed to date. Compliance with baseline and 3-month FACT-ES questionnaires for the primary endpoint in evaluable patients was 90% (215/240) and 83% (198/240), respectively. The pandemic posed several challenges to the REaCT-RETT study including a decline in patient accrual, poor accrual at peripheral sites due to delayed opening, and a rapid switch to virtual patient care. However, the nimble REaCT methodology enabled virtual patient consent and data collection during the pandemic, allowing the trial to continue successfully, with final data expected for presentation summer 2022. Finally, despite the challenges of COVID-19 we have seen that patients and physicians remain interested in research, and we are applying valuable lessons learned to forthcoming REaCT trials to strengthen their performance during and beyond the ongoing pandemic.
ABSTRACT
The outbreak of the COVID-19 pandemic in 2020 posed unique challenges for academic and professional education, while at the same time offering opportunities related to the mass switching of the delivery of courses to the online mode. In this paper, we share the experience of organizing and delivering an online doctoral-level course on Agent-Based Modeling for Social Research. Our aim was to teach interdisciplinary content on various elements of the modeling process in a coherent and practical way. In the paper, we offer a critical assessment of different aspects of the course, related to content as well as organization and delivery. By looking at the course in the light of the current knowledge on good teaching and learning practices from the educational and psychological literature, and reflecting on the lessons learned, we offer a blueprint for designing and running complex, multi-thread simulation courses in an efficient way. © 2021 IEEE.
ABSTRACT
Background: During the coronavirus disease 2019 (COVID-19) lockdown, contact clustering in social bubbles may allow extending contacts beyond the household at minimal additional risk and hence has been considered as part of modified lockdown policy or a gradual lockdown exit strategy. We estimated the impact of such strategies on epidemic and mortality risk using the UK as a case study. Methods: We used an individual based model for a synthetic population similar to the UK, stratified into transmission risks from the community, within the household and from other households in the same social bubble. The base case considers a situation where non-essential shops and schools are closed, the secondary household attack rate is 20% and the initial reproduction number is 0.8. We simulate social bubble strategies (where two households form an exclusive pair) for households including children, for single occupancy households, and for all households. We test the sensitivity of results to a range of alternative model assumptions and parameters. Results: Clustering contacts outside the household into exclusive bubbles is an effective strategy of increasing contacts while limiting the associated increase in epidemic risk. In the base case, social bubbles reduced fatalities by 42% compared to an unclustered increase of contacts. We find that if all households were to form social bubbles the reproduction number would likely increase to above the epidemic threshold of R=1. Strategies allowing households with young children or single occupancy households to form social bubbles increased the reproduction number by less than 11%. The corresponding increase in mortality is proportional to the increase in the epidemic risk but is focussed in older adults irrespective of inclusion in social bubbles. Conclusions: If managed appropriately, social bubbles can be an effective way of extending contacts beyond the household while limiting the increase in epidemic risk.