Predicted long-term impact of COVID-19 pandemic-related care delays on cancer incidence and mortality in Canada
Abstract
Objectives: The COVID-19 pandemic has affected cancer care worldwide. This study aimed to estimate the long-term impacts of the pandemic on cancer incidence and mortality in Canada using a mathematical model. Methods: We developed a stochastic microsimulation model to estimate the cancer care disruptions and its long-term impact on cancer incidence and mortality in Canada. The model reproduces cancer incidence, survival, and epidemiology in Canada, by using cancer incidence, stage at diagnosis and survival data from the Canadian Cancer Registries. We modeled reported declines in cancer diagnoses and treatments recorded in provincial administrative datasets from March 2020-June 2021. We assumed that diagnostic and treatment delays lead to an increased rate of death. Based on the literature, we assumed each 4-week delay in diagnosis and treatment would lead to a 6% to 50% higher rate of cancer death. Results are the median predictions of 10 stochastic simulations. Findings: The model predicts that cancer care disruptions during the COVID-19 pandemic could lead to 21,247 (2.0%) more cancer deaths in Canada in 2020-2030, assuming treatment capacity is recovered to 2019 pre-pandemic levels in 2021. This represents 355,172 life years lost expected due to pandemic-related diagnostic and treatment delays. The highest absolute expected excess cancer mortality was predicted in breast, lung, and colorectal cancers, and in the provinces of Ontario, Quebec, and British Columbia.…
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