Baseline characteristics and survival of patients of idiopathic pulmonary fibrosis: a longitudinal analysis of the Swedish IPF Registry

Abstract

Background: Observational data under real-life conditions in idiopathic pulmonary fibrosis (IPF) is scarce. We explored anti-fibrotic treatment, disease severity and phenotypes in patients with IPF from the Swedish IPF Registry (SIPFR).

Methods: Patients enrolled between September 2014 and April 2020 and followed ≥ 6 months were investigated. Demographics, comorbidities, lung function, composite variables, six-minute walking test (6MWT), quality of life, and anti-fibrotic therapy were evaluated. Agreements between classification of mild physiological impairment (defined as gender-age-physiology (GAP) stage 1) with physiological and composite measures of severity was assessed using kappa values and their impact on mortality with hazard ratios. The factor analysis and the two-step cluster analysis were used to identify phenotypes. Univariate and multivariable survival analyses were performed between variables or groups.

Results: Among 662 patients with baseline data (median age 72.7 years, 74.0% males), 480 had a follow up ≥ 6 months with a 5 year survival rate of 48%. Lung function, 6MWT, age, and BMI were predictors of survival. Patients who received anti-fibrotic treatment ≥ 6 months had better survival compared to untreated patients [p = 0.007, HR (95% CI): 1.797 (1.173-2.753)] after adjustment of age, gender, BMI, smoking status, forced vital capacity (FVC) and diffusion capacity of carbon monoxide (DLCO). Patients with mild physiological impairment (GAP stage 1, composite physiological index (CPI) ≤ 45, DLCO ≥ 55%, FVC ≥ 75%, and total lung capacity (TLC) ≥ 65%, respectively) had better survival, after adjustment for age, gender, BMI and smoking status and treatment. Patients in cluster 1 had the worst survival and consisted mainly of male patients with moderate-severe disease and an increased prevalence of heart diseases at baseline; Cluster 2 was characterized by mild disease with more than 50% females and few comorbidities, and had the best survival; Cluster 3 were younger, with moderate-severe disease and had few comorbidities.

Conclusion: Disease severity, phenotypes, and anti-fibrotic treatment are closely associated with the outcome in IPF, with treated patients surviving longer. Phenotypes may contribute to predicting outcomes of patients with IPF and suggest the patients' need for special management, whereas single or composite variables have some limitations as disease predictors.

Keywords: Anti-fibrotic treatment; Disease severity; Idiopathic pulmonary fibrosis; Phenotype; Survival.

Fig. 1

Prevalence of comorbidities in the SIPFR. The number and percent of a single comorbidity, b the combination of comorbidities. COPD chronic obstructive pulmonary disease

Fig. 2

Kaplan–Meier analysis for survival in the cohort and in GAP stages. Kaplan–Meier analysis for mortality in the SIPFR cohort according to a time from the enrolment; b time from the diagnosis; c and d GAP stage GAP gender, age, physiology

Fig. 3

Kaplan–Meier analysis for survival in treatment. Kaplan–Meier analysis for mortality in the SIPFR cohort according to a, b patients with and without anti-fibrotic treatment in patients in all and GAP stage over 1; c, d patients with anti-fibrotic treatment (nintedanib, pirfenidone, switched treatment) and untreated in patients in all and GAP stage over 1

Fig. 4

Characteristics of clusters, distribution and survival. In a–d shown the basic characteristics of clusters; e The distribution in clusters, largest absolute correlation between each variable and any discriminant function in Function 1 (GAP stage 1, CPI ≤ 45% TLC ≥ 65%, DLCO ≥ 55%, males, LpSaO2, and 6MWD) and in Function 2 (CCI, the number of comorbidities, heart diseases, FVC ≥ 75%, age, smoking history, acid reflux and BMI); f Kaplan–Meier analysis for mortality in clusters