University of Twente Student Theses
The effect of the COVID-19 pandemic on cancer mortality due to diagnosis delay versus COVID mortality
Kremer, R.B. (2022) The effect of the COVID-19 pandemic on cancer mortality due to diagnosis delay versus COVID mortality.
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| Abstract: | In March 2020, COVID-19 made its appearance in the Netherlands after it emerged in China in late 2019. Initially, this lead to the disruption of medical care across several fields, as IC- and regular hospital beds had to be reserved for COVID-19 cases. This resulted in the delay of cancer diagnoses that can lead to adverse outcomes such as death. Objective By elaborating on the model of Hartmann et al. we wanted to create more insight into the effects of COVID-19 and cancer diagnosis delay on mortality. Design, setting, and participants We analyzed patient data of 772.517 cancer patients from 2005 to 2014 using the NCR database to establish hazard ratio’s on the effect of time till first treatment, age, gender, and SES on the 5-year mortality. We used the data from 2005-2013 (n = 680.643) for analysis as train-data and the data from 2014 (n = 91.874) as test-data. The effect of time till first treatment has been used to investigate the effect of diagnosis delay on cancer 5-year mortality, whereas other variables were included for mortality risk estimates. By using open data from the IKNL we were able to calculate the expected number of cancer diagnoses per tumor type over 2020, to correct for working with a dataset from 2014. Data from the Central Bureau for Statistics (CBS) has been used to analyze the incidence and the mortality risks of COVID-19 by age and gender, which we used to calculate mortality over the test data. Results from Chavez-MacGregor et al. gave insight into the increased risk cancer patients have due to their cancer type, stage, or treatment. Lastly, we assessed all-cause mortality rates via the CBS to correct for cancerunrelated mortality over the patient data. Main outcomes and measures When correcting the number of cancer cases due to working with an outdated dataset we expect 103.097 cancer cases over 2020 if COVID-19 did not occur. Of this, we calculated the 5-year mortality of 43.798 patients, which decreases by 2.96% to 42.501 due to diagnosis delay. After correcting for allcause mortality this decreases to respectively 30.387 and 29.090, after which the mortality decrease grows to 4.27%. We expect 438 extra deaths due to COVID-19 of which 59 are allocated due to increased mortality after cancer treatment. Conclusions and relevance The built model can be used for the COVID-19 outbreak to assess cancer mortality versus COVID-19 mortality. It can be altered for other pandemics or sort-like outbreaks. All tumor types and stages can be assessed individually and therefore it can be used to either focus on a specific group or prioritize treatments when necessary |
| Item Type: | Essay (Master) |
| Faculty: | TNW: Science and Technology |
| Subject: | 01 general works |
| Programme: | Health Sciences MSc (66851) |
| Link to this item: | https://purl.utwente.nl/essays/90563 |
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