The relative contribution of co-morbidities to health-related quality of life of people with idiopathic pulmonary fibrosis using the Assessment of Quality of Life-8-Dimension multi-attribute utility instrument.

PURPOSE: Little is known about the impact of co-morbidities on health-related quality of life (HRQoL) for people with idiopathic pulmonary fibrosis (IPF). We aimed to investigate the relative contribution of co-morbidities to HRQoL of people with IPF. METHODS: N = 157 participants were recruited from the Australian IPF Registry (AIPFR). Health state utilities (HSUs), and the super-dimensions of physical and psychosocial scores were measured using the Assessment of Quality of Life-8-Dimensions (AQoL-8D). The impact of co-morbidities on HRQoL was investigated using linear regression and general dominance analyses. RESULTS: A higher number of co-morbidities was associated with lower HSUs (p trend = 0.002). Co-morbidities explained 9.1% of the variance of HSUs, 16.0% of physical super-dimensional scores, and 4.2% of psychosocial super-dimensional scores. Arthritis was associated with a significant reduction on HSUs (ß = - 0.09, 95% confidence interval [CI] - 0.16 to - 0.02), largely driven by reduced scores on the physical super-dimension (ß = - 0.13, 95% CI - 0.20 to - 0.06). Heart diseases were associated with a significant reduction on HSUs (ß = - 0.09, 95% CI - 0.16 to - 0.02), driven by reduced scores on physical (ß = - 0.09, 95% CI - 0.16 to - 0.02) and psychosocial (ß = -0.10, 95% CI - 0.17 to - 0.02) super-dimensions. CONCLUSIONS: Co-morbidities significantly impact HRQoL of people with IPF, with markedly negative impacts on their HSUs and physical health. A more holistic approach to the care of people with IPF is important as better management of these co-morbidities could lead to improved HRQoL in people with IPF.

Incidence, prevalence and mortality of idiopathic pulmonary fibrosis in Australia.

BACKGROUND AND OBJECTIVE: Idiopathic pulmonary fibrosis (IPF) is one of the most common forms of interstitial lung diseases. While studies have been conducted in other countries to determine the epidemiological burden of IPF, there is limited information in Australia. Our study aimed to address this gap and generate the first estimates for the mortality, incidence and prevalence of IPF in Australia. METHODS: Estimates were generated by utilizing the novel Mortality Incidence Analysis Model (MIAMOD) method and software based on the illness-death model. Data inputs included population estimates and mortality data from the Australian Bureau of Statistics (ABS) for the period 1997-2015 and participant data from the Australian IPF Registry (AIPFR). Projections were estimated for a 10-year period up to 2025. RESULTS: Overall crude and age-standardized estimates for mortality were 5.9 and 6.3 per 100,000 population; incidence, 10.4 and 11.2 per 100,000 population; and prevalence, 32.6 and 35.1 per 100,000 population. Crude and age-standardized mortality, incidence and prevalence increased over the study period; however, they demonstrated a decreasing trend over the projected period. Persons older than 70 years constituted 9% of the population; however, they accounted for approximately 82%-83% of all deaths, incident and prevalent cases. All estimates were higher in males than in females. CONCLUSION: Our study provides the first estimates for incidence, prevalence and mortality of IPF in Australia. By reporting national estimates for IPF, our study addresses an information gap important for policy, planning and to help optimize the allocation of resources for the management of patients with IPF.

Eligibility for anti-fibrotic treatment in idiopathic pulmonary fibrosis depends on the predictive equation used for pulmonary function testing.

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 (FEV1 )/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.