Decline in FEV1pp among people with CF is predicted by eight demographic and clinical predictor variables, an analysis of the Australian Cystic Fibrosis Data Registry has found.
Using data from 3655 patients in the registry with a median of 21.7 years of follow up, Monash University researchers performed a linear mixed methods analysis to identify which factors were associated with change in FEV1pp.
The study found that decline in lung function was non-linear, with an initial steeper decrease between the ages of six and 18, of − 2.2 to − 1.8 units/ year, lessening to − 1.8 to − 0.5 units from 19 to 30 years, then plateauing.
In multivariate analysis the study identified eight factors that significantly predicted change in FEV1pp:
- Age of patient at visit,
- BMI z-score,
- Age interaction with lung transplantation,
- Insulin dependent diabetes,
- Cirrhosis/portal hypertension,
- Pancreatic insufficiency,
- P. aeruginosa infection,
- Baseline variability in FEV1pp
The study investigators noted that unlike some previous studies the predictive factors did not include sex or genotype. But in contrast to other studies they said the Australian CF registry included long term data from a large cohort of patients, and had taken into account the impact of factors such as lung transplantation.
According to their paper, the CF registry covered more than 90% of patients in Australia, with the data derived from 23 centres in five states. The mean age at last visit was 25 years, around 27% were underweight at the last visit and around 55.3% presented with normal weight; 18% of patients had insulin dependent diabetes and 6.5% had cirrhosis or portal hypertension. The prevalence of P. aeruginosa infection was 50% while 9.6% of patients had a lung transplant and 7.8% of the entire cohort died.
Writing in Science Reports, they cautioned that the registry did not include data on symptoms and factors known to influence CF. Nevertheless, they said the findings should assist understanding of the natural trajectory of FEV1pp in people with CF, “which is essential to direct early intervention and prevent progression of lung damage, and to inform referral of patients for lung transplantation.”
“These models will prove useful for to study the impact of CFTR modulator therapies on rate of change of lung function among patients with CF,” they said.