Impact of day-to-day variation in FEV1 on measures of change: A conceptual description

Abstract

Clinical trials often demonstrate treatment efficacy through change in forced expiratory volume in one second (FEV₁), comparing single FEV₁ measurements from post- versus pre-treatment timepoints. Day-to-day variation in measured FEV₁ is common for reasons such as diurnal variation and intermittent health changes, relative to a stable, monthly average. This variation can alter estimation of associations between change in FEV₁ and baseline in predictable ways, through a phenomenon called regression to the mean. We quantify and explain day-to-day variation in percent-predicted FEV₁ (ppFEV₁) from 4 previous trials, and we present a statistical, data-driven explanation for potential bias in ceiling and floor effects due to commonly observed amounts of variation. We recommend accounting for variation when assessing associations between baseline value and change in CF outcomes in single-arm trials, and we consider possible impact of variation on conventional standards for study eligibility.

Keywords: Clinical trials; Eligibility; FEV; Measurement error; Regression to the mean.

Figure 1.

The first 30 days (excluding exacerbations) from the 13 pwCF who participated in Thornton’s study of near-daily home spirometry, along with their individual-level steady state means $\mu$ and standard deviations $\sigma$. The best measurement from each day was used for the analyses, and spirometry collected during and 14 days before and after episodic antibiotic treatment for pulmonary exacerbation was excluded. Shaded areas show range of min and max ppFEV₁ over the interval. Average within-person standard deviation was 5.2 ppFEV₁ and ranged from 2.4 to 10.7.

Figure 2.

Using spirometry from a single individual in figure 1, an example of how change from current to next is associated with current level. This is way of visualizing regression to the mean.