Unclassifiable-interstitial lung disease: Outcome prediction using CT and functional indices

Joseph Jacob, Brian Jack Bartholmai, Srinivasan Rajagopalan, Ryoko Egashira, Anne Laure Brun, Maria Kokosi, Arjun Nair, Simon L.F. Walsh, Ronald Karwoski, Andrew G. Nicholson, David M. Hansell, Athol U. Wells

Research output: Contribution to journalArticle

10 Citations (Scopus)

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.

Original languageEnglish (US)
Pages (from-to)43-51
Number of pages9
JournalRespiratory Medicine
Volume130
DOIs
StatePublished - Sep 1 2017

Fingerprint

Bronchiectasis
Interstitial Lung Diseases
Traction
Pulmonary Artery
Fibrosis
Lung
Mortality
Pulmonary Fibrosis
Proportional Hazards Models
Lung Diseases
Multivariate Analysis
Pathology

Keywords

  • Longitudinal analysis
  • Quantitative CT
  • Unclassifiable interstitial lung disease

ASJC Scopus subject areas

  • Pulmonary and Respiratory Medicine

Cite this

Unclassifiable-interstitial lung disease : Outcome prediction using CT and functional indices. / Jacob, Joseph; Bartholmai, Brian Jack; Rajagopalan, Srinivasan; Egashira, Ryoko; Brun, Anne Laure; Kokosi, Maria; Nair, Arjun; Walsh, Simon L.F.; Karwoski, Ronald; Nicholson, Andrew G.; Hansell, David M.; Wells, Athol U.

In: Respiratory Medicine, Vol. 130, 01.09.2017, p. 43-51.

Research output: Contribution to journalArticle

Jacob, J, Bartholmai, BJ, Rajagopalan, S, Egashira, R, Brun, AL, Kokosi, M, Nair, A, Walsh, SLF, Karwoski, R, Nicholson, AG, Hansell, DM & Wells, AU 2017, 'Unclassifiable-interstitial lung disease: Outcome prediction using CT and functional indices', Respiratory Medicine, vol. 130, pp. 43-51. https://doi.org/10.1016/j.rmed.2017.07.007
Jacob, Joseph ; Bartholmai, Brian Jack ; Rajagopalan, Srinivasan ; Egashira, Ryoko ; Brun, Anne Laure ; Kokosi, Maria ; Nair, Arjun ; Walsh, Simon L.F. ; Karwoski, Ronald ; Nicholson, Andrew G. ; Hansell, David M. ; Wells, Athol U. / Unclassifiable-interstitial lung disease : Outcome prediction using CT and functional indices. In: Respiratory Medicine. 2017 ; Vol. 130. pp. 43-51.
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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.",
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T2 - Outcome prediction using CT and functional indices

AU - Jacob, Joseph

AU - Bartholmai, Brian Jack

AU - Rajagopalan, Srinivasan

AU - Egashira, Ryoko

AU - Brun, Anne Laure

AU - Kokosi, Maria

AU - Nair, Arjun

AU - Walsh, Simon L.F.

AU - Karwoski, Ronald

AU - Nicholson, Andrew G.

AU - Hansell, David M.

AU - Wells, Athol U.

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N2 - 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.

AB - 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.

KW - Longitudinal analysis

KW - Quantitative CT

KW - Unclassifiable interstitial lung disease

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