Measuring the impact of COVID-19 on cancer survival using an interrupted time series analysis

JNCI Cancer Spectr. 2024 Jan 4;8(1):pkae001. doi: 10.1093/jncics/pkae001.

Abstract

Background: Few studies have investigated the impact of the COVID-19 pandemic on cancer survival. Those studies that have included pandemic vs prepandemic comparisons can mask differences during different periods of the pandemic such as COVID-19 waves. The objective of this study was to investigate the impact of the COVID-19 pandemic on cancer survival using an interrupted time series analysis and to identify time points during the pandemic when observed survival deviated from expected survival.

Methods: A retrospective population-based cohort study that included individuals diagnosed with cancer between January 2015 and September 2021 from Manitoba, Canada, was performed. Interrupted time series analyses with Royston-Parmar models as well as Kaplan-Meier survival estimates and delta restricted mean survival times at 1 year were used to compare survival rates for those diagnosed before and after the pandemic. Analyses were performed for 11 cancer types.

Results: Survival at 1 year for most cancer types was not statistically different during the pandemic compared with prepandemic except for individuals aged 50-74 years who were diagnosed with lung cancer from April to June 2021 (delta restricted mean survival times = -31.6 days, 95% confidence interval [CI] = -58.3 to -7.2 days).

Conclusions: With the exception of individuals diagnosed with lung cancer, the COVID-19 pandemic did not impact overall 1-year survival in Manitoba. Additional research is needed to examine the impact of the pandemic on long-term cancer survival.

MeSH terms

  • COVID-19*
  • Cohort Studies
  • Humans
  • Interrupted Time Series Analysis
  • Lung Neoplasms*
  • Pandemics
  • Retrospective Studies