Projected long-term effects of colorectal cancer screening disruptions following the COVID-19 pandemic

Pedro Nascimento de Lima*, Rosita van den Puttelaar, Anne I. Hahn, Matthias Harlass, Nicholson Collier, Jonathan Ozik, Ann G. Zauber, Iris Lansdorp-Vogelaar, Carolyn M. Rutter

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

4 Citations (Scopus)
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The aftermath of the initial phase of the COVID-19 pandemic may contribute to the widening of disparities in colorectal cancer (CRC) outcomes due to differential disruptions to CRC screening. This comparative microsimulation analysis uses two CISNET CRC models to simulate the impact of ongoing screening disruptions induced by the COVID-19 pandemic on long-term CRC outcomes. We evaluate three channels through which screening was disrupted: delays in screening, regimen switching, and screening discontinuation. The impact of these disruptions on long-term CRC outcomes was measured by the number of life-years lost due to CRC screening disruptions compared to a scenario without any disruptions. While short-term delays in screening of 3-18 months are predicted to result in minor life-years loss, discontinuing screening could result in much more significant reductions in the expected benefits of screening. These results demonstrate that unequal recovery of screening following the pandemic can widen disparities in CRC outcomes and emphasize the importance of ensuring equitable recovery to screening following the pandemic.

Original languageEnglish
Article numbere85264
Publication statusPublished - 2 May 2023

Bibliographical note

Funding Information:
This research was supported by grant U01-CA253913 from the National Cancer Institute (NCI) as part of the Cancer Intervention and Surveillance Modeling Network (CISNET). Dr. Zauber and Ms. Hahn were supported in part by NCI CCSG P30CA008748 (PI: Vickers). This research used resources of the Argonne Leadership Computing Facility, which is a DOE Office of Science User Facility supported under Contract DE-AC02-06CH11357. We would like to thank the Argonne Leadership Computing Facility staff for their timely and critical support. This research was completed with resources provided by the Laboratory Computing Resource Center at Argonne National Laboratory. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

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