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Phenotypic Clusters Predict Outcomes in a Longitudinal Interstitial Lung Disease Cohort.

ABSTRACT: BACKGROUND:The current interstitial lung disease (ILD) classification has overlapping clinical presentations and outcomes. Cluster analysis modeling is a valuable tool in identifying distinct clinical phenotypes in heterogeneous diseases. However, this approach has yet to be implemented in ILD. METHODS:Using cluster analysis, novel ILD phenotypes were identified among subjects from a longitudinal ILD cohort, and outcomes were stratified according to phenotypic clusters compared with subgroups according to current American Thoracic Society/European Respiratory Society ILD classification criteria. RESULTS:Among subjects with complete data for baseline variables (N = 770), four clusters were identified. Cluster 1 (ie, younger white obese female subjects) had the highest baseline FVC and diffusion capacity of the lung for carbon monoxide (Dlco). Cluster 2 (ie, younger African-American female subjects with elevated antinuclear antibody titers) had the lowest baseline FVC. Cluster 3 (ie, elderly white male smokers with coexistent emphysema) had intermediate FVC and Dlco. Cluster 4 (ie, elderly white male smokers with severe honeycombing) had the lowest baseline Dlco. Compared with classification according to ILD subgroup, stratification according to phenotypic clusters was associated with significant differences in monthly FVC decline (Cluster 4, -0.30% vs Cluster 2, 0.01%; P < .0001). Stratification by using clusters also independently predicted progression-free survival (P < .001) and transplant-free survival (P < .001). CONCLUSIONS:Among adults with diverse chronic ILDs, cluster analysis using baseline characteristics identified four distinct clinical phenotypes that might better predict meaningful clinical outcomes than current ILD diagnostic criteria.

SUBMITTER: Adegunsoye A

PROVIDER: S-EPMC5815877 | biostudies-other | 2018 Feb

REPOSITORIES: biostudies-other

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Phenotypic Clusters Predict Outcomes in a Longitudinal Interstitial Lung Disease Cohort.

Adegunsoye Ayodeji A Oldham Justin M JM Chung Jonathan H JH Montner Steven M SM Lee Cathryn C Witt Leah J LJ Stahlbaum Danielle D Bermea Rene S RS Chen Lena W LW Hsu Scully S Husain Aliya N AN Noth Imre I Vij Rekha R Strek Mary E ME Churpek Matthew M

Chest 20170928 2

<h4>Background</h4>The current interstitial lung disease (ILD) classification has overlapping clinical presentations and outcomes. Cluster analysis modeling is a valuable tool in identifying distinct clinical phenotypes in heterogeneous diseases. However, this approach has yet to be implemented in ILD.<h4>Methods</h4>Using cluster analysis, novel ILD phenotypes were identified among subjects from a longitudinal ILD cohort, and outcomes were stratified according to phenotypic clusters compared wi ...[more]

PMID: 28964798

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Project description:IntroductionThe objective of the present study was to examine the association of baseline demographic and clinical characteristics with sequentially obtained measurements of forced vital capacity (FVC), expressed as a percentage of the predicted value, and to identify predictors of the decline rate in FVC over time in the Genetics versus Environment in Scleroderma Outcome Study (GENISOS).MethodsTo date, 266 patients have been enrolled in GENISOS, a prospective, observational cohort of patients with early systemic sclerosis. In addition to pulmonary function tests (PFTs), clinical and laboratory data were obtained from each patient. We analyzed 926 FVC measurements utilizing generalized linear mixed models. The predictive significance of baseline variables for the decline rate in FVC was investigated by the interaction term between the variable and the follow-up time within the first 3 years after enrollment as well as throughout the entire follow-up time.ResultsThe cohort consisted of 125 white, 54 African American, and 77 Hispanic patients with average disease duration of 2.5 years at enrollment. The mean follow-up time was 3.8 years, ranging up to 11.4 years. A number of baseline variables, including antibody status, African American ethnicity, disease type, baseline PFT values, modified Rodnan Skin Score, fibrosis on chest radiograph, and lung and skin subscores of the Severity Index, were associated with serially measured FVC levels. However, only the presence of anti-topoisomerase I antibodies (ATA) was associated with lower FVC levels (P < 0.001) as well as accelerated decline rate in FVC within the first 3 years of follow-up (P = 0.02). None of the baseline variables predicted the rate of decline in FVC on long-term follow-up. Patients with rapidly progressive ILD, however, were under-represented in the long-term follow-up group because the accelerated rate of decline in FVC was associated with poor survival (P = 0.001).ConclusionsPresence of ATA was the only baseline variable associated with differential FVC levels, predicting the rate of decline in FVC within the first 3 years of follow-up. The association of faster decline in FVC with poor survival further emphasizes the need for identification of predictive biomarkers by collection of genetic information and serial blood samples in cohort studies.

Project description:RationaleMediastinal lymph node (MLN) enlargement on chest computed tomography (CT) is prevalent in patients with interstitial lung disease (ILD) and may reflect immunologic activation and subsequent cytokine-mediated immune cell trafficking.ObjectivesWe aimed to determine whether MLN enlargement on chest CT predicts clinical outcomes and circulating cytokine levels in ILD.MethodsMLN measurements were obtained from chest CT scans of patients with ILD at baseline evaluation over a 10-year period. Patients with sarcoidosis and drug toxicity-related ILD were excluded. MLN diameter and location were assessed. Plasma cytokine levels were analyzed in a subset of patients. The primary outcome was transplant-free survival (TFS). Secondary outcomes included all-cause and respiratory hospitalizations, lung function, and plasma cytokine concentrations. Cox regression was used to assess mortality risk. Outcomes were assessed in three independent ILD cohorts.Measurements and main resultsChest CT scans were assessed in 1,094 patients (mean age, 64 yr; 52% male). MLN enlargement (≥10 mm) was present in 66% (n = 726) and strongly predicted TFS (hazard ratio [HR], 1.53; 95% confidence interval [CI], 1.12-2.10; P = 0.008) and risk of all-cause and respiratory hospitalizations (internal rate of return [IRR], 1.52; 95% CI, 1.17-1.98; P = 0.002; and IRR, 1.71; 95% CI, 1.15-2.53; P = 0.008, respectively) when compared with subjects with MLN <10 mm. Patients with MLN enlargement had lower lung function and decreased plasma concentrations of soluble CD40L (376 pg/ml vs. 505 pg/ml, P = 0.001) compared with those without MLN enlargement. Plasma IL-10 concentration >45 pg/ml predicted mortality (HR, 4.21; 95% CI, 1.21-14.68; P = 0.024). Independent analysis of external datasets confirmed these findings.ConclusionsMLN enlargement predicts TFS and hospitalization risk in ILD and is associated with decreased levels of a key circulating cytokine, soluble CD40L. Incorporating MLN and cytokine findings into current prediction models might improve ILD prognostication.

Project description:Background:Interstitial lung disease (ILD) is a slowly progressing fatal fibrotic lung disease with a widely variable clinical course and a poor prognosis. Clinicians and patients would benefit from a highly efficient and accurate predictor for ILD. The purpose of this study was to evaluate whether blood biomarkers can predict ILD progression. Methods:In this study, 85 patients diagnosed as having ILD at the Guangzhou Institute of Respiratory Health participated, including 20 patients with idiopathic pulmonary fibrosis (IPF). During the mean follow-up time of 12 months, every patient was examined during four or five visits in our center. Serum samples were collected at baseline, and after 1, 2, 6, and 12 months and tested for the Klebs von den Lungen-6 (KL-6) concentration. Dynamic fluctuations in this biomarker concentration were examined using a logistic regression model to see if they reflected the progression of ILD. Results:The baseline levels of serum KL-6 in the ILD patients were significantly increased compared to healthy controls. Serum KL-6 levels were significantly elevated in patients with progression of disease (1,985.2±1,497.8 vs. 1,387.6±1,313.1 µg/mL; P<0.001). Logistic regression revealed sequential changes of KL-6 was a significant predictor of ILD progression in the next follow-up (OR, 2.569; 95% CI, 2.260-2.880; P=0.001), and that sequential changes of KL-6 were significant predictors for the progression of IPF (OR, 3.611; 95% CI, 1.048-12.442; P<0.01). Baseline concentrations were not predictive for ILD or IPF. Univariate Cox analysis showed that KL-6 was significantly associated with survival [relative risk (RR), 1.901; 95% CI, 1.294-2.793; P<0.001], along with other variables. Conclusions:Serum levels of KL-6 were elevated in ILD patients with severe respiratory function compared to those without. The rate of poor prognosis and mortality was associated with increased biomarker concentrations. Sequential measurements of biomarkers could be valuable in disease monitoring and evaluations in clinical management.

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Phenotypic Clusters Predict Outcomes in a Longitudinal Interstitial Lung Disease Cohort.

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Phenotypic Clusters Predict Outcomes in a Longitudinal Interstitial Lung Disease Cohort.

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