An inverse stage-shift model to estimate the excess mortality and health economic impact of delayed access to cancer services due to the COVID-19 pandemic
Abstract
Background
Decreased cancer incidence and reported changes to clinical management indicate that the COVID-19 pandemic will result in diagnostic and treatment delays for cancer patients. We aimed to develop a flexible model to estimate the impact of delayed diagnosis and treatment initiation on survival outcomes and healthcare costs based on a shift in the disease stage at treatment initiation.
Methods
The stage-shift model estimates population-level health economic outcomes by weighting disease stage-specific outcomes by the distribution of stages at treatment initiation, assuming delays lead to stage-progression. It allows for extrapolation of population-level survival data using parametric distributions to calculate the expected survival in life years. The model was demonstrated based on an analysis of the impact of 3 and 6-month delays for stage I breast cancer, colorectal cancer and lung cancer patients, and for T1 melanoma, based on Australian data. In the absence of patient-level data about time to stage progression, two approaches were explored to estimate the proportion of patients that would experience a stage shift following the delay: 1) based on the relation between time to treatment initiation and overall survival (breast, colorectal and lung cancer), and 2) based on the tumour growth rate (melanoma). The model is available on <ext-link xmlns:xlink="http://www.w3.org/1999/xlink" ext-link-type="uri" xlink:href="http://stage-shift.personex.nl/">http://stage-shift.personex.nl/</ext-link>.
Results
A shift from stage I to stage II due to a 6-month delay is least likely for colorectal cancer patients, with an estimated proportion of 3% of the stage I patients diagnosed in 2020 progressing to stage II, resulting in 11 excess deaths after 5 years and a total of 96 life years lost over a 10-year time horizon. For breast and lung cancer, progression from stage I to stage II due to a 6-month delay were slightly higher at 5% (breast cancer) and 8% (lung cancer), resulting in 25 and 43 excess deaths after 5 years, and 239 and 373 life years lost over a 10-year time horizon, respectively. For melanoma, with 32% of T1 patients progressing to T2 disease following a 6-month delay, the model estimated 270 excess death after 5 years and 2584 life years lost over a 10-year time horizon.
Conclusions
Using a conservative 3-month delay in diagnosis and treatment initiation due to the COVID-19 pandemic, this study predicts nearly 90 excess deaths and $12 million excess healthcare costs in Australia over 5 years for the in 2020 diagnosed patients for 4 cancers. If the delays increase to 6 months, excess mortality and cost approach nearly 350 deaths and $46 million in Australia. More accurate data on stage of disease during and after the COVID-19 pandemic are critical to obtain more reliable estimates.
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