IMPORTANCECancer treatment delay has been reported to variably impact cancer-specific survival and coronavirus disease 2019 (COVID-19)-specific mortality during the severe acute respiratory syndrome coronavirus 2 pandemic. During the pandemic, treatment delay is being recommended in a nonquantitative, nonobjective, and nonpersonalized manner, and this approach may be associated with suboptimal outcomes. Quantitative integration of cancer mortality estimates and data on the consequences of treatment delay is needed to aid treatment decisions and improve patient outcomes.OBJECTIVE To obtain quantitative integration of cancer-specific and COVID-19-specific mortality estimates that can be used to make optimal decisions for individual patients and optimize resource allocation.
DESIGN, SETTING, AND PARTICIPANTSIn this decision analytical model, age-specific and stage-specific estimates of overall survival pre-COVID-19 were adjusted by the probability of COVID-19 (individualized by county, treatment-specific variables, hospital exposure frequency, and COVID-19 infectivity estimates), COVID-19 mortality (individualized by age-specific, comorbidity-specific, and treatment-specific variables), and delay of cancer treatment (impact and duration). These model estimates were integrated into a web application (OncCOVID) to calculate estimates of the cumulative overall survival and restricted mean survival time of patients who received immediate vs delayed cancer treatment. Using currently available information about COVID-19, a susceptible-infectedrecovered model that accounted for the increased risk among patients at health care treatment centers was developed. This model integrated the data on cancer mortality and the consequences of treatment delay to aid treatment decisions. Age-specific and cancer stage-specific estimates of overall survival pre-COVID-19 were extracted from the Surveillance, Epidemiology, and End Results database for 691 854 individuals with 25 cancer types who received cancer diagnoses in 2005 to 2006. Data from 5 436 896 individuals in the National Cancer Database were used to estimate the independent impact of treatment delay by cancer type and stage. In addition, data from 275 patients in a nested case-control study were used to estimate the COVID-19 mortality rate by age group and number of comorbidities. Data were analyzed from March 17 to May 21, 2020.
EXPOSURES COVID-19 and cancer.MAIN OUTCOMES AND MEASURES Estimates of restricted mean survival time after the receipt of immediate vs delayed cancer treatment.
COVID-19 is unique in the scope of its effects on morbidity and mortality. However, the factors contributing to its disparate racial, ethnic, and socioeconomic effects are part of an expansive and continuous history of oppressive social policy and marginalising geopolitics. This history is characterised by institutionally generated spatial inequalities forged through processes of residential segregation and neglectful urban planning. In the USA, aspects of COVID-19's manifestation closely mirror elements of the build-up and response to the Flint crisis, Michigan's racially and class-contoured water crisis that began in 2014, and to other prominent environmental injustice cases, such as the 1995 Chicago (IL, USA) heatwave that severely affected the city's south and west sides, predominantly inhabited by Black people. Each case shares common macrosocial and spatial characteristics and is instructive in showing how civic trust suffers in the aftermath of public health disasters, becoming especially degenerative among historically and spatially marginalised populations. Offering a commentary on the sociogeographical dynamics that gave rise to these crises and this institutional distrust, we discuss how COVID-19 has both inherited and augmented patterns of spatial inequality. We conclude by outlining particular steps that can be taken to prevent and reduce spatial inequalities generated by COVID-19, and by discussing the preliminary steps to restore trust between historically disenfranchised communities and the public officials and institutions tasked with responding to COVID-19.
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