Forced vital capacity trajectories in patients with idiopathic pulmonary fibrosis: a secondary analysis of a multicentre, prospective, observational cohort

BACKGROUND: Idiopathic pulmonary fibrosis is a progressive fibrotic lung disease with a variable clinical trajectory. Decline in forced vital capacity (FVC) is the main indicator of progression; however, missingness prevents long-term analysis of patterns in lung function. We aimed to identify distinct clusters of lung function trajectory among patients with idiopathic pulmonary fibrosis using machine learning techniques. METHODS: We did a secondary analysis of longitudinal data on FVC collected from a cohort of patients with idiopathic pulmonary fibrosis from the PROFILE study; a multicentre, prospective, observational cohort study. We evaluated the imputation performance of conventional and machine learning techniques to impute missing data and then analysed the fully imputed dataset by unsupervised clustering using self-organising maps. We compared anthropometric features, genomic associations, serum biomarkers, and clinical outcomes between clusters. We also performed a replication of the analysis on data from a cohort of patients with idiopathic pulmonary fibrosis from an independent dataset, obtained from the Chicago Consortium. FINDINGS: 415 (71%) of 581 participants recruited into the PROFILE study were eligible for further analysis. An unsupervised machine learning algorithm had the lowest imputation error among tested methods, and self-organising maps identified four distinct clusters (1-4), which was confirmed by sensitivity analysis. Cluster 1 comprised 140 (34%) participants and was associated with a disease trajectory showing a linear decline in FVC over 3 years. Cluster 2 comprised 100 (24%) participants and was associated with a trajectory showing an initial improvement in FVC before subsequently decreasing. Cluster 3 comprised 113 (27%) participants and was associated with a trajectory showing an initial decline in FVC before subsequent stabilisation. Cluster 4 comprised 62 (15%) participants and was associated with a trajectory showing stable lung function. Median survival was shortest in cluster 1 (2·87 years [IQR 2·29-3·40]) and cluster 3 (2·23 years [1·75-3·84]), followed by cluster 2 (4·74 years [3·96-5·73]), and was longest in cluster 4 (5·56 years [5·18-6·62]). Baseline FEV1 to FVC ratio and concentrations of the biomarker SP-D were significantly higher in clusters 1 and 3. Similar lung function clusters with some shared anthropometric features were identified in the replication cohort. INTERPRETATION: Using a data-driven unsupervised approach, we identified four clusters of lung function trajectory with distinct clinical and biochemical features. Enriching or stratifying longitudinal spirometric data into clusters might optimise evaluation of intervention efficacy during clinical trials and patient management. FUNDING: National Institute for Health and Care Research, Medical Research Council, and GlaxoSmithKline

Biomarkers of collagen turnover are related to annual change in FEV1 in patients with chronic obstructive pulmonary disease within the ECLIPSE study

BACKGROUND: Change in forced expiratory volume in one second (FEV1) is important for defining severity of chronic obstructive pulmonary disease (COPD). Serological neoepitope markers of collagen turnover may predict rate of change in FEV1. METHODS: One thousand COPD subjects from the observational, multicentre, three-year ECLIPSE (Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints) study (NCT00292552, trial registration in February 2006) were included. Matrix metalloproteinase (MMP)-generated fragments of collagen type I, and type VI (C1M and C6M) were assessed in month six serum samples. A random-coefficient model with both a random intercept and a random slope was used to test the ability of the markers to predict post-dose bronchodilator FEV1 (PD-FEV1) change over two years adjusting for sex, age, BMI, smoking, bronchodilator reversibility, prior exacerbations, emphysema and chronic bronchitis status at baseline. RESULTS: Annual change of PD-FEV1 was estimated from a linear model for the two-year study period. Serum C1M and C6M were independent predictors of lung function change (p = 0.007/0.005). Smoking, bronchodilator reversibility, plasma hsCRP and emphysema were also significant predictors. The effect estimate between annual change in PD-FEV1 per one standard deviation (1SD) increase of C1M and C6M was +10.4 mL/yr. and +8.6 mL/yr. C1M, and C6M, had a significant association with baseline FEV1. CONCLUSION: We demonstrated that markers of tissue turnover were significantly associated with lung function change. These markers may function as prognostic biomarkers and possibly as efficacy biomarkers in clinical trials focusing on lung function change in COPD. TRIAL REGISTRATION: NCT00292552 , Retrospectively registered, trial registration in February 2006

Can biomarkers of extracellular matrix remodelling and wound healing be used to identify high risk patients infected with SARS-CoV-2?: lessons learned from pulmonary fibrosis

Pulmonary fibrosis has been identified as a main factor leading to pulmonary dysfunction and poor quality of life in post-recovery Severe Acute Respiratory Syndrome (SARS) survivor's consequent to SARS-Cov-2 infection. Thus there is an urgent medical need for identification of readily available biomarkers that in patients with SARS-Cov-2 infection are able to; (1) identify patients in most need of medical care prior to admittance to an intensive care unit (ICU), and; (2) identify patients post-infection at risk of developing persistent fibrosis of lungs with subsequent impaired quality of life and increased morbidity and mortality. An intense amount of research have focused on wound healing and Extracellular Matrix (ECM) remodelling of the lungs related to lung function decline in pulmonary fibrosis (PF). A range of non-invasive serological biomarkers, reflecting tissue remodelling, and fibrosis have been shown to predict risk of acute exacerbations, lung function decline and mortality in PF and other interstitial lung diseases (Sand et al. in Respir Res 19:82, 2018). We suggest that lessons learned from such PF studies of the pathological processes leading to lung function decline could be used to better identify patients infected with SARS-Co-V2 at most risk of acute deterioration or persistent fibrotic damage of the lung and could consequently be used to guide treatment decisions

Proteolytic biomarkers are related to prognosis in COPD : report from a population-based cohort

BACKGROUND: The imbalance between proteases and anti-proteases is considered to contribute to the development of COPD. Our aim was to evaluate the protease MMP-9, the antiprotease TIMP-1 and the MMP-9/TIMP-1-ratio as biomarkers in relation to prognosis. Prognosis was assessed as lung function decline and mortality. This was done among subjects with COPD in a population-based cohort. METHODS: In 2005, clinical examinations including spirometry and peripheral blood sampling, were made in a longitudinal population-based cohort. In total, 1542 individuals participated, whereof 594 with COPD. In 2010, 1031 subjects participated in clinical examinations, and 952 subjects underwent spirometry in both 2005 and 2010. Serum MMP-9 and TIMP-1 concentrations were measured with enzyme linked immunosorbent assay (ELISA). Mortality data were collected from the Swedish national mortality register from the date of examination in 2005 until 31st December 2010. RESULTS: The correlation between biomarkers and lung function decline was similar in non-COPD and COPD, but only significant for MMP-9 and MMP-9/TIMP-1-ratio in non-COPD. Mortality was higher in COPD than non-COPD (16% vs. 10%, p = 0.008). MMP-9 concentrations and MMP-9/TIMP-1 ratios in 2005 were higher among those who died during follow up, as well as among those alive but not participating in 2010, when compared to those participating in the 2010-examination. In non-COPD, male sex, age, burden of smoking, heart disease and MMP-9/TIMP-1 ratio were associated with increased risk for death, while increased TIMP-1 was protective. Among those with COPD, age, current smoking, increased MMP-9 and MMP-9/TIMP-1 ratio were associated with an increased risk for death. CONCLUSIONS: The expected association between these biomarkers and lung function decline in COPD was not confirmed in this population-based study, probably due to a healthy survivor effect. Still, it is suggested that increased proteolytic imbalance may be of greater prognostic importance in COPD than in non-COPD