Joseph Jacob1, Brian J Bartholmai2, Srinivasan Rajagopalan3, Ryoko Egashira4, Anne Laure Brun5, Maria Kokosi6, Arjun Nair7, Simon L F Walsh8, Ronald Karwoski3, Andrew G Nicholson9, David M Hansell5, Athol U Wells6. 1. Division of Radiology, Mayo Clinic Rochester, Rochester, MN, USA. Electronic address: joseph.jacob@nhs.net. 2. Division of Radiology, Mayo Clinic Rochester, Rochester, MN, USA. 3. Department of Physiology and Biomedical Engineering, Mayo Clinic Rochester, Rochester, MN, USA. 4. Department of Radiology, Faculty of Medicine, Saga University, Saga City, Japan. 5. Department of Radiology, Royal Brompton Hospital, Royal Brompton and Harefield NHS Foundation Trust, London, UK. 6. Interstitial Lung Disease Unit, Royal Brompton Hospital, Royal Brompton and Harefield NHS Foundation Trust, London, UK. 7. Department of Radiology, Guys and St Thomas' NHS Foundation Trust, London, UK. 8. Department of Radiology, Kings College Hospital NHS Foundation Trust, London, UK. 9. Department of Histopathology, Royal Brompton Hospital, Royal Brompton and Harefield NHS Foundation Trust London, UK.
Abstract
BACKGROUND: Unclassifiable-interstitial lung disease (uILD) represents a heterogeneous collection of pathologies encompassing those fibrosing lung diseases which do not fulfill current diagnostic criteria. We evaluated baseline and longitudinal functional and CT (visual and quantitative computer [CALIPER] analysis) variables to identify outcome predictors in uILD. METHODS: Consecutive patients with uILD on multidisciplinary review (n = 95) had baseline functional (FVC, DLco, CPI [composite physiologic index]) and CT features (visual evaluation: CT pattern, fibrosis extent, honeycombing presence, traction bronchiectasis severity, pulmonary artery (PA) diameter; CALIPER evaluation: fibrosis extent, pulmonary vessel volume (PVV)) examined in univariate and multivariate Cox regression models. Change in functional and CT variables were examined in a patient subset (n = 37), to identify indicators of outcome. RESULTS: On univariate analysis, CPI was the most powerful functional predictor of mortality (p < 0.0001). Visual traction bronchiectasis (p < 0.0001), PA diameter (p < 0.0001) and honeycombing presence (p = 0.0001) and CALIPER PVV (p = 0.0003) were the strongest CT outcome predictors. On multivariate analysis of baseline indices, traction bronchiectasis (p = 0.003), PA diameter (p = 0.003) and CPI (p = 0.0001) independently predicted mortality. Colinearity with functional indices precluded the evaluation of CALIPER PVV in multivariate models. On evaluation of longitudinal variables, increasing CALIPER fibrosis extent was the strongest outcome predictor, and remained so following adjustment for baseline disease severity, and when FVC declines were marginal. CONCLUSIONS: In uILD patients, CPI, traction bronchiectasis severity and PA diameter independently predicted outcome at baseline. Increasing fibrosis extent measured by CALIPER was the most powerful index of outcome regardless of baseline disease severity and strongly predicted outcome in patients with marginal FVC declines. Crown
BACKGROUND: Unclassifiable-interstitial lung disease (uILD) represents a heterogeneous collection of pathologies encompassing those fibrosing lung diseases which do not fulfill current diagnostic criteria. We evaluated baseline and longitudinal functional and CT (visual and quantitative computer [CALIPER] analysis) variables to identify outcome predictors in uILD. METHODS: Consecutive patients with uILD on multidisciplinary review (n = 95) had baseline functional (FVC, DLco, CPI [composite physiologic index]) and CT features (visual evaluation: CT pattern, fibrosis extent, honeycombing presence, traction bronchiectasis severity, pulmonary artery (PA) diameter; CALIPER evaluation: fibrosis extent, pulmonary vessel volume (PVV)) examined in univariate and multivariate Cox regression models. Change in functional and CT variables were examined in a patient subset (n = 37), to identify indicators of outcome. RESULTS: On univariate analysis, CPI was the most powerful functional predictor of mortality (p < 0.0001). Visual traction bronchiectasis (p < 0.0001), PA diameter (p < 0.0001) and honeycombing presence (p = 0.0001) and CALIPER PVV (p = 0.0003) were the strongest CT outcome predictors. On multivariate analysis of baseline indices, traction bronchiectasis (p = 0.003), PA diameter (p = 0.003) and CPI (p = 0.0001) independently predicted mortality. Colinearity with functional indices precluded the evaluation of CALIPER PVV in multivariate models. On evaluation of longitudinal variables, increasing CALIPER fibrosis extent was the strongest outcome predictor, and remained so following adjustment for baseline disease severity, and when FVC declines were marginal. CONCLUSIONS: In uILD patients, CPI, traction bronchiectasis severity and PA diameter independently predicted outcome at baseline. Increasing fibrosis extent measured by CALIPER was the most powerful index of outcome regardless of baseline disease severity and strongly predicted outcome in patients with marginal FVC declines. Crown
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