OBJECTIVES: Extent of systemic sclerosis (SSc)-related interstitial lung disease (ILD) assessed from thoracic high-resolution CT (HRCT) predicts disease course, mortality and treatment response. While quantitative HRCT analyses of extent of lung fibrosis (QLFib) or total interstitial lung disease (QILD) are more sensitive and reproducible than visual HRCT assessments of SSc-ILD, these analyses are not widely available. This study evaluates the relationship between clinical disease parameters and QLFib and QILD scores to identify potential surrogate measures of radiographic extent of ILD. METHODS: Using baseline data from the Scleroderma Lung Study I (SLS I; N=158), multivariate regression analyses were performed using the best subset selection method to identify one to five variable models that best correlated with QLFib and QILD scores in both whole lung (WL) and the zone of maximal involvement (ZM). These models were subsequently validated using baseline data from SLS II (N=142). Bivariate analyses of the radiographic and clinical variables were also performed using pooled data. SLS I and II did not include patients with clinically significant pulmonary hypertension (PH). RESULTS:Diffusing capacity for carbon monoxide (DLCO) was the single best predictor of both QLF and QILD in the WL and ZM in all of the best subset models. Adding other disease parameters to the models did not substantially improve model performance. Forced vital capacity (FVC) did not predict QLF or QILD scores in any of the models. CONCLUSIONS: In the absence of PH, DLCO provides the best overall estimate of HRCT-measured lung disease in patients from two large SSc cohorts. FVC, although commonly used, may not be the best surrogate measure of extent of SSc-ILD at any point in time. TRIAL REGISTRATION NUMBERS: SLS I: www.clinicaltrials.gov NCT 00000-4563; SLS II: www.clinicaltrials.gov NCT 00883129. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/
RCT Entities:
OBJECTIVES: Extent of systemic sclerosis (SSc)-related interstitial lung disease (ILD) assessed from thoracic high-resolution CT (HRCT) predicts disease course, mortality and treatment response. While quantitative HRCT analyses of extent of lung fibrosis (QLFib) or total interstitial lung disease (QILD) are more sensitive and reproducible than visual HRCT assessments of SSc-ILD, these analyses are not widely available. This study evaluates the relationship between clinical disease parameters and QLFib and QILD scores to identify potential surrogate measures of radiographic extent of ILD. METHODS: Using baseline data from the Scleroderma Lung Study I (SLS I; N=158), multivariate regression analyses were performed using the best subset selection method to identify one to five variable models that best correlated with QLFib and QILD scores in both whole lung (WL) and the zone of maximal involvement (ZM). These models were subsequently validated using baseline data from SLS II (N=142). Bivariate analyses of the radiographic and clinical variables were also performed using pooled data. SLS I and II did not include patients with clinically significant pulmonary hypertension (PH). RESULTS: Diffusing capacity for carbon monoxide (DLCO) was the single best predictor of both QLF and QILD in the WL and ZM in all of the best subset models. Adding other disease parameters to the models did not substantially improve model performance. Forced vital capacity (FVC) did not predict QLF or QILD scores in any of the models. CONCLUSIONS: In the absence of PH, DLCO provides the best overall estimate of HRCT-measured lung disease in patients from two large SSc cohorts. FVC, although commonly used, may not be the best surrogate measure of extent of SSc-ILD at any point in time. TRIAL REGISTRATION NUMBERS: SLS I: www.clinicaltrials.gov NCT 00000-4563; SLS II: www.clinicaltrials.gov NCT 00883129. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/
Authors: David Manners; Patrick Wong; Conor Murray; Joelin Teh; Yi Jin Kwok; Nick de Klerk; Helman Alfonso; Peter Franklin; Alison Reid; A W Bill Musk; Fraser J H Brims Journal: Eur Radiol Date: 2017-01-12 Impact factor: 5.315
Authors: Julie Morisset; Eric Vittinghoff; Brett M Elicker; Xiaowen Hu; Stephanie Le; Jay H Ryu; Kirk D Jones; Anna Haemel; Jeffrey A Golden; Francesco Boin; Brett Ley; Paul J Wolters; Talmadge E King; Harold R Collard; Joyce S Lee Journal: Chest Date: 2017-06-16 Impact factor: 9.410
Authors: Alicia M Hinze; Cheng T Lin; Amira F Hussien; Jamie Perin; Aida Venado; Jeffrey A Golden; Francesco Boin; Robert H Brown; Robert A Wise; Fredrick M Wigley Journal: Rheumatology (Oxford) Date: 2020-04-01 Impact factor: 7.580