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Impact of COVID-19 Restrictions on Estimating Causal Effects: Fluoroquinolones and Tendon Rupture
Angel Y S Wong1, Jeremy P Brown2, John Tazare1
1Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, UK.
Purpose:
The COVID-19 pandemic disrupted healthcare services, potentially affecting causal effect estimation using real-world data. As a case study, we replicated a cohort study using Clinical Practice Research Datalink Aurum to evaluate whether pandemic-related disruptions influenced the measured association between fluoroquinolone use and tendon rupture.
Methods:
We included adults initiating fluoroquinolones/cephalosporins during 1 January 2006-31 March 2023. Four analyses compared treatment effect estimates using different periods for exposure and outcome ascertainment: pre-pandemic only, pre-pandemic exposure with follow-up extending through the pandemic, all available data and post-pandemic only. We estimated hazard ratios (HRs) for tendon rupture using Cox regression.
Results:
Among 891 968 fluoroquinolone users and 895 229 cephalosporin users, fluoroquinolone users had more comorbidities than cephalosporin users in the pre-pandemic period but fewer in the post-pandemic period. Pre-pandemic analysis showed an increased risk of tendon rupture associated with fluoroquinolones (Propensity score weighted [PSW]-HR: 1.94; 95% CI: 1.46-2.59), consistent with previous evidence. Estimates using all available data were similar for the overall study period (PSW-HR: 1.91; 95% CI: 1.46-2.51) and the pre-pandemic period (PSW-HR: 1.96; 95% CI: 1.47-2.61) but were less precise during/post-pandemic period (PSW-HR: 1.57; 95% CI: 0.72-3.41) with no evidence of a period-treatment interaction (PSW-HR: 0.80; 95% CI: 0.35-1.84). Post-pandemic analysis showed very few events among cephalosporin users but not fluoroquinolone users with a larger but imprecise estimate (PSW-HR: 3.32; 95% CI: 0.62-17.72).
Conclusion:
In this case study, there was no clear evidence that pandemic-related healthcare disruptions materially altered causal estimates, albeit with limited power to detect differences between before and during/post-pandemic effects. Studies using real-world data across the pandemic should routinely examine temporal changes in baseline characteristics and outcome incidence.
