Brett Ley

Clinical course and prediction of survival in idiopathic pulmonary fibrosis.

Idiopathic pulmonary fibrosis (IPF) is a progressive, life-threatening, interstitial lung disease of unknown etiology. The median survival of patients with IPF is only 2 to 3 years, yet some patients live much longer. Respiratory failure resulting from disease progression is the most frequent cause of death. To date we have limited information as to predictors of mortality in patients with IPF, and research in this area has failed to yield prediction models that can be reliably used in clinical practice to predict individual risk of mortality. The goal of this concise clinical review is to examine and summarize the current data on the clinical course, individual predictors of survival, and proposed clinical prediction models in IPF. Finally, we will discuss challenges and future directions related to predicting survival in IPF.

A Multidimensional Index and Staging System for Idiopathic Pulmonary Fibrosis

BACKGROUND Idiopathic pulmonary fibrosis (IPF) is a progressive fibrotic lung disease with an overall poor prognosis. A simple-to-use staging system for IPF may improve prognostication, help guide management, and facilitate research. OBJECTIVE To develop a multidimensional prognostic staging system for IPF by using commonly measured clinical and physiologic variables. DESIGN A clinical prediction model was developed and validated by using retrospective data from 3 large, geographically distinct cohorts. SETTING Interstitial lung disease referral centers in California, Minnesota, and Italy. PATIENTS 228 patients with IPF at the University of California, San Francisco (derivation cohort), and 330 patients at the Mayo Clinic and Morgagni-Pierantoni Hospital (validation cohort). MEASUREMENTS The primary outcome was mortality, treating transplantation as a competing risk. Model discrimination was assessed by the c-index, and calibration was assessed by comparing predicted and observed cumulative mortality at 1, 2, and 3 years. RESULTS Four variables were included in the final model: gender (G), age (A), and 2 lung physiology variables (P) (FVC and Dlco). A model using continuous predictors (GAP calculator) and a simple point-scoring system (GAP index) performed similarly in derivation (c-index of 70.8 and 69.3, respectively) and validation (c-index of 69.1 and 68.7, respectively). Three stages (stages I, II, and III) were identified based on the GAP index with 1-year mortality of 6%, 16%, and 39%, respectively. The GAP models performed similarly in pooled follow-up visits (c-index ≥71.9). LIMITATION Patients were drawn from academic centers and analyzed retrospectively. CONCLUSION The GAP models use commonly measured clinical and physiologic variables to predict mortality in patients with IPF.

Clinical features and outcomes in combined pulmonary fibrosis and emphysema in idiopathic pulmonary fibrosis

BACKGROUND Combined pulmonary fibrosis and emphysema (CPFE) is increasingly recognized, but its prevalence and prognosis remain unclear. We sought to determine the prevalence, clinical features, and prognosis of CPFE in idiopathic pulmonary fibrosis (IPF), using a standardized and reproducible definition. METHODS Patients with IPF were identified from two ongoing cohorts. Two radiologists scored emphysema and fibrosis severity on high-resolution CT (HRCT) scans. CPFE was defined as ≥10% emphysema on HRCT scan. Clinical characteristics and outcomes of patients with CPFE and IPF and those with non-CPFE IPF were compared with unadjusted analysis and then analysis after adjustment for HRCT fibrosis score. Mortality was compared using competing risks regression to handle lung transplantation. Sensitivity analyses were performed using Cox proportional hazards, including time to death (transplantation censored) and time to death or transplant. RESULTS CPFE criteria were met in 29 of 365 patients with IPF (8%), with high agreement between radiologists (κ=0.74). Patients with CPFE had less fibrosis on HRCT scans and higher FVC, but greater oxygen requirements (P≤.01 for all comparisons). Findings were maintained with adjustment for fibrosis severity. Inhaled therapies for COPD were used by 53% of patients with CPFE. There was no significant difference in mortality comparing patients with CPFE and IPF to those with non-CPFE IPF (hazard ratio, 1.14; 95% CI, 0.61-2.13; P=.69). CONCLUSIONS CPFE was identified in 8% of patients with IPF and is a distinct, clinical phenotype with potential therapies that remain underutilized. Patients with CPFE and IPF and those with non-CPFE IPF have similar mortality.

Epidemiology of idiopathic pulmonary fibrosis

Idiopathic pulmonary fibrosis is a chronic fibrotic lung disease of unknown cause that occurs in adults and has a poor prognosis. Its epidemiology has been difficult to study because of its rarity and evolution in diagnostic and coding practices. Though uncommon, it is likely underappreciated both in terms of its occurrence (ie, incidence, prevalence) and public health impact (ie, health care costs and resource utilization). Incidence and mortality appear to be on the rise, and prevalence is expected to increase with the aging population. Potential risk factors include occupational and environmental exposures, tobacco smoking, gastroesophageal reflux, and genetic factors. An accurate understanding of its epidemiology is important, especially as novel therapies are emerging.

Predicting Survival Across Chronic Interstitial Lung Disease: The ILD-GAP Model

BACKGROUND Risk prediction is challenging in chronic interstitial lung disease (ILD) because of heterogeneity in disease-specific and patient-specific variables. Our objective was to determine whether mortality is accurately predicted in patients with chronic ILD using the GAP model, a clinical prediction model based on sex, age, and lung physiology, that was previously validated in patients with idiopathic pulmonary fibrosis. METHODS Patients with idiopathic pulmonary fibrosis (n=307), chronic hypersensitivity pneumonitis (n=206), connective tissue disease-associated ILD (n=281), idiopathic nonspecific interstitial pneumonia (n=45), or unclassifiable ILD (n=173) were selected from an ongoing database (N=1,012). Performance of the previously validated GAP model was compared with novel prediction models in each ILD subtype and the combined cohort. Patients with follow-up pulmonary function data were used for longitudinal model validation. RESULTS The GAP model had good performance in all ILD subtypes (c-index, 74.6 in the combined cohort), which was maintained at all stages of disease severity and during follow-up evaluation. The GAP model had similar performance compared with alternative prediction models. A modified ILD-GAP Index was developed for application across all ILD subtypes to provide disease-specific survival estimates using a single risk prediction model. This was done by adding a disease subtype variable that accounted for better adjusted survival in connective tissue disease-associated ILD, chronic hypersensitivity pneumonitis, and idiopathic nonspecific interstitial pneumonia. CONCLUSION The GAP model accurately predicts risk of death in chronic ILD. The ILD-GAP model accurately predicts mortality in major chronic ILD subtypes and at all stages of disease.

Relative versus absolute change in forced vital capacity in idiopathic pulmonary fibrosis

Background Decline in forced vital capacity (FVC) over time reliably predicts mortality in patients with idiopathic pulmonary fibrosis. The use of this measure in clinical practice is recommended by current evidence-based guidelines. It is unknown if the method of calculating decline in FVC (relative vs absolute change) impacts its frequency or its ability to predict mortality. Methods Patients with idiopathic pulmonary fibrosis from two prospective cohorts were included if they had a baseline and 12-month follow-up FVC. A ≥10% decline in FVC from baseline was calculated in two ways: a relative decline of 10% (eg, from 60% predicted to 54% predicted) and an absolute decline of 10% (eg, from 60% predicted to 50% predicted). The frequency of a ≥10% decline in FVC and its ability to predict 2-year transplant-free survival were compared between these two methods. Declines in FVC of ≥5% and ≥15% were similarly compared. Analyses were performed unadjusted and adjusted for age, gender, use of oxygen, baseline FVC and baseline diffusion capacity for carbon monoxide. Results The frequency of any given FVC decline was significantly greater using the relative change in FVC method. For ≥10% decline, both methods predicted 2-year transplant-free survival with similar accuracy, and remained significant predictors after adjusting for baseline characteristics. The absolute change method appeared more predictive for ≥5% decline. Conclusions Using the relative change in FVC maximises the chance of identifying a ≥10% decline in FVC without sacrificing prognostic accuracy. This may not hold true for ≥5% decline in FVC. These findings have important implications for clinical practice and the design of clinical trials.

Molecular biomarkers in idiopathic pulmonary fibrosis

Molecular biomarkers are highly desired in idiopathic pulmonary fibrosis (IPF), where they hold the potential to elucidate underlying disease mechanisms, accelerated drug development, and advance clinical management. Currently, there are no molecular biomarkers in widespread clinical use for IPF, and the search for potential markers remains in its infancy. Proposed core mechanisms in the pathogenesis of IPF for which candidate markers have been offered include alveolar epithelial cell dysfunction, immune dysregulation, and fibrogenesis. Useful markers reflect important pathological pathways, are practically and accurately measured, have undergone extensive validation, and are an improvement upon the current approach for their intended use. The successful development of useful molecular biomarkers is a central challenge for the future of translational research in IPF and will require collaborative efforts among those parties invested in advancing the care of patients with IPF.

Cough predicts prognosis in idiopathic pulmonary fibrosis

Background and objective:  The clinical associations and prognostic value of cough in IPF have not been adequately described. The objective of this study was to describe the characteristics and prognostic value of cough in IPF.

Idiopathic Pulmonary Fibrosis: CT and Risk of Death

PURPOSE To investigate the prognostic value of quantitative computed tomographic (CT) scoring for the extent of fibrosis or emphysema in the context of a clinical model that includes the gender, age, and physiology ( GAP gender, age, and physiology model) of the patient. MATERIALS AND METHODS Study cohorts were approved by local institutional review boards, and all patients provided written consent. This was a retrospective cohort study that included 348 patients (246 men, 102 women; mean age, 69 years ± 9) with idiopathic pulmonary fibrosis from two institutions. Fibrosis and emphysema visual scores were independently determined by two radiologists. Models were based on competing risks regression for death and were evaluated by using the C index and reclassification improvement. RESULTS The CT- GAP gender, age, and physiology model (a modification of the original GAP gender, age, and physiology model that replaces diffusion capacity of carbon monoxide with CT fibrosis score) had accuracy comparable to that of the original GAP gender, age, and physiology model, with a C index of 70.3 (95% confidence interval: 66.4, 74.0); difference in C index compared with the GAP gender, age, and physiology model of -0.4 (95% confidence interval: -2.2, 3.4). The performance of the original GAP gender, age, and physiology model did not change significantly with the simple addition of fibrosis score, with a change in C index of 0.0 (95% confidence interval: -1.8, 0.5) or of emphysema score, with a change in C index of 0.0 [95% confidence interval: -1.3, 0.4]). CONCLUSION CT fibrosis score can replace diffusion capacity of carbon monoxide test results in a modified GAP gender, age, and physiology model (the CT- GAP gender, age, and physiology model) with comparable performance. This may be a useful alternative model in situations where CT scoring is more reliable and available than diffusion capacity of carbon monoxide.

Predictors of Mortality Poorly Predict Common Measures of Disease Progression in Idiopathic Pulmonary Fibrosis.

RATIONALE Mortality prediction is well studied in idiopathic pulmonary fibrosis (IPF), but little is known about predictors of premortality disease progression. Identification of patients at risk for disease progression would be useful for clinical decision-making and designing clinical trials. OBJECTIVES To develop prediction models for disease progression in IPF. METHODS In a large clinical trial cohort of patients with IPF (n = 1,113), we comprehensively screened multivariate models of candidate baseline and past-change predictors for disease progression defined by 48-week worsening of FVC, dyspnea (University of California, San Diego Shortness of Breath Questionnaire [UCSD SOBQ]), 6-minute-walk distance (6MWD), and occurrence of respiratory hospitalization, or death. Progression outcomes were modeled as appropriate, by slope change using linear regression models and time to binary outcomes using Cox proportional hazards models. MEASUREMENTS AND MAIN RESULTS The overall cohort experienced considerable disease progression. Top-performing prediction models did not meaningfully predict most measures of disease progression. For example, prediction modeling explained less than or equal to 1% of the observed variation in 48-week slope change in FVC, UCSD SOBQ, and 6MWD. Models performed better for binary measures of time to disease progression but were still largely inaccurate (cross-validated C statistic ≤0.63 for ≥10% decline in FVC or death, ≤0.68 for ≥20-U increase in UCSD SOBQ or death, ≤0.70 for ≥100 m decline in 6MWD or death). Models for time to respiratory hospitalization or death (C statistic ≤0.77) or death alone (C statistic ≤0.81) demonstrated acceptable discriminative performance. CONCLUSIONS Clinical prediction models poorly predicted physiologic and functional disease progression in IPF. This is in contrast to respiratory hospitalization and mortality prediction.