Delivery of Cancer Care in Ontario, Canada, During the First Year of the COVID-19 Pandemic.

Importance: The COVID-19 pandemic has impacted cancer systems worldwide. Quantifying the changes is critical to informing the delivery of care while the pandemic continues, as well as for system recovery and future pandemic planning. Objective: To quantify change in the delivery of cancer services across the continuum of care during the COVID-19 pandemic. Design, Setting, and Participants: This population-based cohort study assessed cancer screening, imaging, diagnostic, treatment, and psychosocial oncological care services delivered in pediatric and adult populations in Ontario, Canada (population 14.7 million), from April 1, 2019, to March 1, 2021. Data were analyzed from May 1 to July 31, 2021. Exposures: COVID-19 pandemic. Main Outcomes and Measures: Cancer service volumes from the first year of the COVID-19 pandemic, defined as April 1, 2020, to March 31, 2021, were compared with volumes during a prepandemic period of April 1, 2019, to March 31, 2020. Results: During the first year of the pandemic, there were a total of 4 476 693 cancer care services, compared with 5 644 105 services in the year prior, a difference of 20.7% fewer services of cancer care, representing a potential backlog of 1 167 412 cancer services. While there were less pronounced changes in systemic treatments, emergency and urgent imaging examinations (eg, 1.9% more parenteral systemic treatments) and surgical procedures (eg, 65% more urgent surgical procedures), major reductions were observed for most services beginning in March 2020. Compared with the year prior, during the first pandemic year, cancer screenings were reduced by 42.4% (-1 016 181 screening tests), cancer treatment surgical procedures by 14.1% (-8020 procedures), and radiation treatment visits by 21.0% (-141 629 visits). Biopsies to confirm cancer decreased by up to 41.2% and surgical cancer resections by up to 27.8% during the first pandemic wave. New consultation volumes also decreased, such as for systemic treatment (-8.2%) and radiation treatment (-9.3%). The use of virtual cancer care increased for systemic treatment and radiation treatment and psychosocial oncological care visits, increasing from 0% to 20% of total new or follow-up visits prior to the pandemic up to 78% of total visits in the first pandemic year. Conclusions and Relevance: In this population-based cohort study in Ontario, Canada, large reductions in cancer service volumes were observed. While most services recovered to prepandemic levels at the end of the first pandemic year, a substantial care deficit likely accrued. The anticipated downstream morbidity and mortality associated with this deficit underscore the urgent need to address the backlog and recover cancer care and warrant further study.

Novel coronavirus disease 2019: predicting prognosis with a computed tomography-based disease severity score and clinical laboratory data.

INTRODUCTION: Currently, there are known contributing factors but no comprehensive methods for predicting the mortality risk or intensive care unit (ICU) admission in patients with novel coronavirus disease 2019 (COVID­19). OBJECTIVES: The aim of this study was to explore risk factors for mortality and ICU admission in patients with COVID­19, using computed tomography (CT) combined with clinical laboratory data. PATIENTS AND METHODS: Patients with polymerase chain reaction-confirmed COVID­19 (n = 63) from university hospitals in Tehran, Iran, were included. All patients underwent CT examination. Subsequently, a total CT score and the number of involved lung lobes were calculated and compared against collected laboratory and clinical characteristics. Univariable and multivariable proportional hazard analyses were used to determine the association among CT, laboratory and clinical data, ICU admission, and in­hospital death. RESULTS: By univariable analysis, in­hospital mortality was higher in patients with lower oxygen saturation on admission (below 88%), higher CT scores, and a higher number of lung lobes (more than 4) involved with a diffuse parenchymal pattern. By multivariable analysis, in­hospital mortality was higher in those with oxygen saturation below 88% on admission and a higher number of lung lobes involved with a diffuse parenchymal pattern. The risk of ICU admission was higher in patients with comorbidities (hypertension and ischemic heart disease), arterial oxygen saturation below 88%, and pericardial effusion. CONCLUSIONS: We can identify factors affecting in­hospital death and ICU admission in COVID-19. This can help clinicians to determine which patients are likely to require ICU admission and to inform strategic healthcare planning in critical conditions such as the COVID­19 pandemic.