ABSTRACT
To avoid delay in oncological treatment, a 6-weeks norm for time to treatment has been agreed on in The Netherlands. However, the impact of the COVID-19 pandemic on health systems resulted in reduced capacity for regular surgical care. In this study, we investigated the impact of the COVID-19 pandemic on time to treatment in surgical oncology in The Netherlands. METHODS: A population-based analysis of data derived from five surgical audits, including patients who underwent surgery for lung cancer, colorectal cancer, upper gastro-intestinal, and hepato-pancreato-biliary (HPB) malignancies, was performed. The COVID-19 cohort of 2020 was compared to the historic cohorts of 2018 and 2019. Primary endpoints were time to treatment initiation and the proportion of patients whose treatment started within 6 weeks. The secondary objective was to evaluate the differences in characteristics and tumour stage distribution between patients treated before and during the COVID-19 pandemic. RESULTS: A total of 14,567 surgical cancer patients were included in this study, of these 3292 treatments were started during the COVID-19 pandemic. The median time to treatment decreased during the pandemic (26 vs. 27 days, p < 0.001) and the proportion of patients whose treatment started within 6 weeks increased (76% vs. 73%, p < 0.001). In a multivariate logistic regression analysis, adjusting for patient characteristics, no significant difference in post-operative outcomes between patients who started treatment before or after 6 weeks was found. Overall, the number of procedures performed per week decreased by 8.1% during the pandemic. This reduction was most profound for patients with stage I lung carcinoma and colorectal carcinoma. There were fewer patients with pulmonary comorbidities in the pandemic cohort (11% vs. 13%, p = 0.003). CONCLUSIONS: Despite pressure on the capacity of the healthcare system during the COVID-19 pandemic, a larger proportion of surgical oncological patients started treatment within six weeks, possibly due to prioritisation of cancer care and reductions in elective procedures. However, during the pandemic, a decrease in the number of surgical oncological procedures performed in The Netherlands was observed, especially for patients with stage I disease.
ABSTRACT
AIM: A population-based COVID-19 cohort was set up in the Netherlands to gain comprehensive insight in the short- and long-term effects of COVID-19 in the general population. The present study aims to describe the methodology and infrastructure used to recruit individuals with COVID-19, and the representativeness of the population-based cohort. The second aim was to characterize the population by description of their symptoms and health care usage during the acute COVID-19 phase. METHOD: The starting point of the set-up of the cohort was to recruit participants in routinely recorded, general practice electronic health records (EHR) data, which are sent to the Netherlands Institute for Health Services Research Primary Care Database (Nivel-PCD) on a weekly basis. Patients registered with COVID-19 were flagged in the Nivel-PCD based on their COVID-19 diagnoses. Flagged patients were invited for participation by their general practitioner via a trusted third party. Participating patients received a series of four questionnaires over the duration of one year allowing for a combination of data from patient reported outcomes and EHRs. RESULTS: In this study, results from the first questionnaire are used. The Nivel Corona Cohort consists of 442 participants and is population-based, containing a complete image of severity of symptoms from patients with none or hardly any symptoms to those who were hospitalized due to the COVID-19. The five most prevalent symptoms during the acute COVID-19 phase were fatigue (90.5%), reduced condition (88.2%), coughing/sneezing/stuffy nose (79.3%), headache (75.4%), and myalgia (66.7%). CONCLUSION: The population-based Nivel Corona Cohort provides ample opportunities for future studies to gain comprehensive insight in the short- and long-term effects of COVID-19 by combining patients' perspectives and clinical parameters via the EHRs within a long-term follow-up of the cohort.
