Background and objective: Publicly funded therapy for idiopathic pulmonary fibrosis (IPF) relies on percentage predicted values from pulmonary function testing, for example Australian patients must have a forced vital capacity ≥50% (%FVC), transfer factor of the lung for carbon monoxide ≥ 30% (%TLco) and forced expiratory volume in 1 s (FEV 1 )/FVC ratio > 0.7. Despite defined cut-off values, no jurisdiction prescribes a reference equation for use; multiple equations exist. We hypothesized that access to subsidized treatment varies depending on the chosen equation. The %FVC and %TLco from different commonly used reference equations across general respiratory patients, and IPF-specific patients, were compared. Methods: FVC and TLco measurements from a large general respiratory laboratory and the Australian Idiopathic Pulmonary Fibrosis Registry (AIPFR) database were analysed using multiple equations. Differences between %FVC and %TLco for each equation were calculated, with particular interest in classification of patients (%) at the threshold for subsidized treatment. Results: A total of 20 378 general respiratory database results were analysed. The %FVC ≥ 50% increased from 86% with the Roca equation to 96% with Quanjer (European Coal and Steal Community, ECSC) and %TLco≥30% increased from 91% with Paoletti to 98% with Thompson. However, overall increase in eligibility for subsidized treatment was modest, varying from 48.2% to 49.2%. A total of 545 AIPFR database results were analysed. The %FVC ≥ 50% increased from 73% with Roca to 94% with Quanjer (ECSC) and %TLco≥30% increased from 87% with Paoletti to 96% with Miller. Overall eligibility for subsidized treatment in the AIPFR group varied from 73.6% to 82.8% between surveyed interstitial lung disease (ILD) centres based entirely on the equation used. Conclusion: Substantial variability exists between reference equations, impacting access to subsidized treatment. Treating clinicians should be aware of this when assessing patients around public funding thresholds.
- lung function
- predicted equations