Purpose: This study evaluated the reliability of cancer cases reported to the National Cancer Database (NCDB) during 2020, the first year of the COVID-19 pandemic.
Methods: Total number of cancer cases reported to the NCDB between January 2018 and December 2020 were calculated for all cancers and 21 selected cancer sites. The additive outlier method was used to identify structural breaks in trends compared with previous years. The difference between expected (estimated using the vector autoregressive method) and observed number of cases diagnosed in 2020 was estimated using generalized estimating equation under assumptions of the Poisson distribution for count data. Interrupted time series analysis was used to compare changes in the number of records processed by registrars each month of 2020. All models accounted for seasonality, regional variation, and random error.
Results: There was a statistically significant decrease (structural break) in the number of cases diagnosed in April 2020, with no recovery in number of cases during subsequent months, leading to a 12.4% deficit in the number of cases diagnosed during the first year of the pandemic. While the number of cancer records initiated by cancer registrars also decreased, the number of records marked completed increased during the first months of the pandemic.
Conclusion: There was a significant deficit in the number of cancer diagnoses in 2020 that was not due to cancer registrars' inability to extract data during the pandemic. Future studies can use NCDB data to evaluate the impact of the pandemic on cancer care and outcomes.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9767395 | PMC |
http://dx.doi.org/10.1245/s10434-022-12935-w | DOI Listing |
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