Predicting Pulmonary Fibrosis Disease Course From Past Trends in Pulmonary Function

Schmidt, Shelley L.; Tayob, Nabihah; Han, MeiLan K.; Zappala, Christopher; Kervitsky, Dolly; Murray, Susan; Wells, Athol U.; Brown, Kevin K.; Martínez, Fernando J.; Flaherty, Kevin R.

doi:10.1378/chest.13-0844

Cited by 104 publications

(80 citation statements)

References 27 publications

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“…This is in contrast to the ability of these variables to predict risk of either respiratory hospitalization or death in IPF (5,6,24). These data support recent evidence that disease progression in IPF is nonlinear and unrelated to patient's previous disease behavior (1,2,25,26), and suggest that respiratory hospitalization and death may be more strongly correlated event types with similar predisposing clinical factors.…”

Section: Discussionsupporting

confidence: 74%

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

Ley¹,

Bradford²,

Vittinghoff

et al. 2016

Am J Respir Crit Care Med

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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.

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Section: Discussionsupporting

confidence: 74%

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

Ley¹,

Bradford²,

Vittinghoff

et al. 2016

Am J Respir Crit Care Med

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“…Our study is the only one, to the best of our knowledge, that evaluated the baseline GAP stage as a predictor of future rate of pulmonary function change. Schmidt et al 26 previously…”

Section: Discussionmentioning

confidence: 96%

“…[22][23][24][25] Patients with missing baseline DLCO data were excluded because this variable is needed to calculate GAP stage, 13 and we were not able to distinguish in our database patients with missing data due to respiratory limitation from those in whom the test was not ordered. This dataset was also used in a previously published study 26 approved by research oversight committees at each participating institution (studies HUM00018279, 01-246, and HS-1603).…”

Section: Patientsmentioning

confidence: 99%

Idiopathic Pulmonary Fibrosis

Salisbury

Xia

Zhou

et al. 2016

Chest

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BACKGROUND: Idiopathic pulmonary fibrosis is a progressive lung disease with variable course. The Gender-Age-Physiology (GAP) Index and staging system uses clinical variables to stage mortality risk. It is unknown whether clinical staging predicts future decline in pulmonary function. We assessed whether the GAP stage predicts future pulmonary function decline and whether interval pulmonary function change predicts mortality after accounting for stage.

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“…This composite endpoint was chosen as part of an enrichment strategy to improve statistical power (28) and because these endpoints have previously been shown to be clinically meaningful (29)(30)(31) Cox regression models were checked to ensure that the proportional hazards assumption was met. Based on SNP distributions, an additive allelic model was assumed for rs3750920 (TOLLIP) and a dominant model for rs5743890 (TOLLIP), rs5743894 (TOLLIP), rs5743854 (TOLLIP), and rs35705950 (MUC5B).…”

Section: Discussionmentioning

confidence: 99%

TOLLIP, MUC5B, and the Response to N-Acetylcysteine among Individuals with Idiopathic Pulmonary Fibrosis

Oldham

Fan

Martínez

et al. 2015

Am J Respir Crit Care Med

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273

191

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Rationale: Idiopathic pulmonary fibrosis (IPF) is a devastating lung disease of unknown etiology. The genes TOLLIP and MUC5B play important roles in lung host defense, which is an immune process influenced by oxidative signaling. Whether polymorphisms in TOLLIP and MUC5B modify the effect of immunosuppressive and antioxidant therapy in individuals with IPF is unknown.Objectives: To determine whether single-nucleotide polymorphisms (SNPs) within TOLLIP and MUC5B modify the effect of interventions in subjects participating in the Evaluating the Effectiveness of Prednisone, Azathioprine, and N-Acetylcysteine in Patients with Idiopathic Pulmonary Fibrosis (PANTHER-IPF) clinical trial.Methods: SNPs within TOLLIP (rs5743890/rs5743894/rs5743854/ rs3750920) and MUC5B (rs35705950) were genotyped. Interaction modeling was conducted with multivariable Cox regression followed by genotype-stratified survival analysis using a composite endpoint of death, transplantation, hospitalization, or a decline of >10% in FVC.Measurements and Main Results: Significant interaction was observed between N-acetylcysteine (NAC) therapy and rs3750920 within TOLLIP (P interaction = 0.001). After stratifying by rs3750920 genotype, NAC therapy was associated with a significant reduction in composite endpoint risk (hazard ratio, 0.14; 95% confidence interval, 0.02-0.83; P = 0.03) in those with a TT genotype, but a nonsignificant increase in composite endpoint risk (hazard ratio, 3.23; 95% confidence interval, 0.79-13.16; P = 0.10) was seen in those with a CC genotype. These findings were then replicated in an independent IPF cohort.Conclusions: NAC may be an efficacious therapy for individuals with IPF with an rs3750920 (TOLLIP) TT genotype, but it was associated with a trend toward harm in those with a CC genotype. A genotype-stratified prospective clinical trial should be conducted before any recommendation regarding the use of off-label NAC to treat IPF.

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Predicting Pulmonary Fibrosis Disease Course From Past Trends in Pulmonary Function

Cited by 104 publications

References 27 publications

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

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

Idiopathic Pulmonary Fibrosis

TOLLIP, MUC5B, and the Response to N-Acetylcysteine among Individuals with Idiopathic Pulmonary Fibrosis

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