Adherence to guidance for prioritizing higher risk groups for breast cancer screening during the COVID-19 pandemic in the Ontario Breast Screening Program: a descriptive study.

BACKGROUND: Breast cancer screening in Ontario, Canada, was deferred during the first wave of the COVID-19 pandemic, and a prioritization framework to resume services according to breast cancer risk was developed. The purpose of this study was to assess the impact of the pandemic within the Ontario Breast Screening Program (OBSP) by comparing total volumes of screening mammographic examinations and volumes of screening mammographic examinations with abnormal results before and during the pandemic, and to assess backlogs on the basis of adherence to the prioritization framework. METHODS: A descriptive study was conducted among women aged 50 to 74 years at average risk and women aged 30 to 69 years at high risk, who participated in the OBSP. Percentage change was calculated by comparing observed monthly volumes of mammographic examinations from March 2020 to March 2021 with 2019 volumes and proportions by risk group. We plotted estimates of backlog volumes of mammographic examinations by risk group, comparing pandemic with prepandemic screening practices. Volumes of mammographic examinations with abnormal results were plotted by risk group. RESULTS: Volumes of mammographic examinations in the OBSP showed the largest declines in April and May 2020 (> 99% decrease) and returned to prepandemic levels as of March 2021, with an accumulated backlog of 340 876 examinations. As of March 2021, prioritization had reduced the backlog volumes of screens for participants at high risk for breast cancer by 96.5% (186 v. 5469 expected) and annual rescreens for participants at average risk for breast cancer by 13.5% (62 432 v. 72 202 expected); there was a minimal decline for initial screens. Conversely, the backlog increased by 7.6% for biennial rescreens (221 674 v. 206 079 expected). More than half (59.4%) of mammographic examinations with abnormal results were for participants in the higher risk groups. INTERPRETATION: Prioritizing screening for those at higher risk for breast cancer may increase diagnostic yield and redirect resources to minimize potential long-term harms caused by the pandemic. This further supports the clinical utility of risk-stratified cancer screening.

Development of COVIDVax Model to Estimate the Risk of SARS-CoV-2-Related Death Among 7.6 Million US Veterans for Use in Vaccination Prioritization.

Importance: A strategy that prioritizes individuals for SARS-CoV-2 vaccination according to their risk of SARS-CoV-2-related mortality would help minimize deaths during vaccine rollout. Objective: To develop a model that estimates the risk of SARS-CoV-2-related mortality among all enrollees of the US Department of Veterans Affairs (VA) health care system. Design, Setting, and Participants: This prognostic study used data from 7 635 064 individuals enrolled in the VA health care system as of May 21, 2020, to develop and internally validate a logistic regression model (COVIDVax) that predicted SARS-CoV-2-related death (n = 2422) during the observation period (May 21 to November 2, 2020) using baseline characteristics known to be associated with SARS-CoV-2-related mortality, extracted from the VA electronic health records (EHRs). The cohort was split into a training period (May 21 to September 30) and testing period (October 1 to November 2). Main Outcomes and Measures: SARS-CoV-2-related death, defined as death within 30 days of testing positive for SARS-CoV-2. VA EHR data streams were imported on a data integration platform to demonstrate that the model could be executed in real-time to produce dashboards with risk scores for all current VA enrollees. Results: Of 7 635 064 individuals, the mean (SD) age was 66.2 (13.8) years, and most were men (7 051 912 [92.4%]) and White individuals (4 887 338 [64.0%]), with 1 116 435 (14.6%) Black individuals and 399 634 (5.2%) Hispanic individuals. From a starting pool of 16 potential predictors, 10 were included in the final COVIDVax model, as follows: sex, age, race, ethnicity, body mass index, Charlson Comorbidity Index, diabetes, chronic kidney disease, congestive heart failure, and Care Assessment Need score. The model exhibited excellent discrimination with area under the receiver operating characteristic curve (AUROC) of 85.3% (95% CI, 84.6%-86.1%), superior to the AUROC of using age alone to stratify risk (72.6%; 95% CI, 71.6%-73.6%). Assuming vaccination is 90% effective at preventing SARS-CoV-2-related death, using this model to prioritize vaccination was estimated to prevent 63.5% of deaths that would occur by the time 50% of VA enrollees are vaccinated, significantly higher than the estimate for prioritizing vaccination based on age (45.6%) or the US Centers for Disease Control and Prevention phases of vaccine allocation (41.1%). Conclusions and Relevance: In this prognostic study of all VA enrollees, prioritizing vaccination based on the COVIDVax model was estimated to prevent a large proportion of deaths expected to occur during vaccine rollout before sufficient herd immunity is achieved.

Thyroid fine-needle aspiration trends before, during, and after the lockdown: what we have learned so far from the COVID-19 pandemic.

PURPOSE: Nowadays, the clinical management of thyroid nodules needs to be multi-disciplinary. In particular, the crosstalk between endocrinologists and cytopathologists is key. When FNAs are properly requested by endocrinologists for nodules characterised by relevant clinical and ultrasound features, cytopathologists play a pivotal role in the diagnostic work-up. Conversely, improper FNA requests can lead to questionable diagnostic efficiency. Recently, recommendations to delay all non-urgent diagnostic procedures, such as thyroid FNAs, to contain the spread of COVID-19 infection, have made the interplay between endocrinologists and cytopathologists even more essential. The objective of this study was to assess the impact of COVID-19 pandemic on our practice by evaluating the total number of FNAs performed and the distribution of the Bethesda Categories before, during, and after the lockdown. METHODS: We analysed the FNA trends before (1st January 2019 to March 13th 2020), during (March 14th to May 15th), and after (May 16th to July 7th) the lockdown. RESULTS: Although the total number of weekly FNAs dropped from 62.1 to 23.1, our referring endocrinologists managed to prioritise patients with high-risk nodules. In fact, in the post-lockdown, the weekly proportion of benign diagnoses dropped on average by 12% and that of high-risk diagnoses increased by 6%. CONCLUSIONS: The lesson we have learned so far from this pandemic is that by applying safety protocols to avoid contagion and by increasing the threshold for FNA requests for thyroid nodules, we can continue to guarantee our services to high-risk patients even in times of a health crisis.