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1.
Cancer Research ; 82(4 SUPPL), 2022.
Article in English | EMBASE | ID: covidwho-1779442

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.

2.
2021 Winter Simulation Conference, WSC 2021 ; 2021-December, 2021.
Article in English | Scopus | ID: covidwho-1746020

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.

3.
Hiv Medicine ; 22:89-89, 2021.
Article in English | Web of Science | ID: covidwho-1377236
4.
Wellcome Open Research ; 5:213, 2020.
Article in English | MEDLINE | ID: covidwho-1175761

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.

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