ArticleBMC medicine2016
Evaluation of computer-based computer tomography stratification against outcome models in connective tissue disease-related interstitial lung disease: a patient outcome study.
Article in BMC medicine, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 49 papers, 2 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
49 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- A systematic review of the role of quantitative CT in the prognostication and disease monitoring of interstitial lung disease.European respiratory review : an official journal of the European Respiratory Society · 2025Pooled it
- Computed Tomography Predictors of Mortality or Disease Progression in Systemic Sclerosis-Interstitial Lung Disease: A Systematic Review.Frontiers in medicine · 2021Pooled it
- Radiomic analysis of high-resolution computed tomography predicts interstitial lung disease progression and mortality in systemic sclerosis.Rheumatology (Oxford, England) · 2026Article
- Prediction of intravenous cyclophosphamide treatment efficacy in idiopathic inflammatory myopathies-associated interstitial lung disease patients: a nomogram based on radiomics and clinical factors.BMC pulmonary medicine · 2026Article
- Using SFTPC and computed tomographic volumetric imaging to diagnose and predict outcomes in usual interstitial pneumonia-type idiopathic pulmonary fibrosis.Journal of cardiothoracic surgery · 2026Article
- Evolving landscape of imaging-based evaluation in systemic autoimmune rheumatic disease-associated interstitial lung disease: from visual assessment to quantitative artificial intelligence-assisted evaluation.Journal of rheumatic diseases · 2026Review
- Development and internal validation of a machine learning-based model for predicting 2-year mortality in interstitial lung disease.Respiratory research · 2026Article
- Absolute and lung volume-normalized deep learning-derived pulmonary vascular measures in idiopathic pulmonary fibrosis: distinct clinical associations and the role of lung volume in prognosis.Frontiers in medicine · 2026Article
- Computed tomography-based quantitative scoring system for rheumatoid arthritis-associated interstitial lung disease: a retrospective diagnostic accuracy study for progressive fibrosis detection.Clinical rheumatology · 2025Article
- The potential of semi-quantitative and quantitative methods in predicting progression in rheumatoid arthritis-associated interstitial lung disease.Clinical rheumatology · 2025Observational
- Assessing pulmonary vascular remodeling in connective tissue disease-associated interstitial lung disease: a CT-based quantitative analysis.Quantitative imaging in medicine and surgery · 2025Article
- Warrick score in rheumatoid-arthritis interstitial lung disease: a promising tool for assessing the extent and progression of lung involvement.Advances in rheumatology (London, England) · 2025Article
- Review
- From pixels to prognosis: unlocking the potential of deep learning in fibrotic lung disease imaging analysis.The British journal of radiology · 2024Review
- Quantitative chest computed tomography predicts mortality in systemic sclerosis: A longitudinal study.PloS one · 2024Article
- Generative Adversarial Network-Based Image Conversion Among Different Computed Tomography Protocols and Vendors: Effects on Accuracy and Variability in Quantifying Regional Disease Patterns of Interstitial Lung Disease.Korean journal of radiology · 2023Article
- Exploring computer-based imaging analysis in interstitial lung disease: opportunities and challenges.ERJ open research · 2023Review
- Recent innovations in the screening and diagnosis of systemic sclerosis-associated interstitial lung disease.Expert review of clinical immunology · 2023Review
- Clinically Relevant Biomarkers in Connective Tissue Disease-Associated Interstitial Lung Disease.Immunology and allergy clinics of North America · 2023Review
- Lung shrinking assessment on HRCT with elastic registration technique for monitoring idiopathic pulmonary fibrosis.European radiology · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
Abstract
backgroundTo evaluate computer-based computer tomography (CT) analysis (CALIPER) against visual CT scoring and pulmonary function tests (PFTs) when predicting mortality in patients with connective tissue disease-related interstitial lung disease (CTD-ILD). To identify outcome differences between distinct CTD-ILD groups derived following automated stratification of CALIPER variables.
methodsA total of 203 consecutive patients with assorted CTD-ILDs had CT parenchymal patterns evaluated by CALIPER and visual CT scoring: honeycombing, reticular pattern, ground glass opacities, pulmonary vessel volume, emphysema, and traction bronchiectasis. CT scores were evaluated against pulmonary function tests: forced vital capacity, diffusing capacity for carbon monoxide, carbon monoxide transfer coefficient, and composite physiologic index for mortality analysis. Automated stratification of CALIPER-CT variables was evaluated in place of and alongside forced vital capacity and diffusing capacity for carbon monoxide in the ILD gender, age physiology (ILD-GAP) model using receiver operating characteristic curve analysis.
resultsCox regression analyses identified four independent predictors of mortality: patient age (P < 0.0001), smoking history (P = 0.0003), carbon monoxide transfer coefficient (P = 0.003), and pulmonary vessel volume (P < 0.0001). Automated stratification of CALIPER variables identified three morphologically distinct groups which were stronger predictors of mortality than all CT and functional indices. The Stratified-CT model substituted automated stratified groups for functional indices in the ILD-GAP model and maintained model strength (area under curve (AUC) = 0.74, P < 0.0001), ILD-GAP (AUC = 0.72, P < 0.0001). Combining automated stratified groups with the ILD-GAP model (stratified CT-GAP model) strengthened predictions of 1- and 2-year mortality: ILD-GAP (AUC = 0.87 and 0.86, respectively); stratified CT-GAP (AUC = 0.89 and 0.88, respectively).
conclusionsCALIPER-derived pulmonary vessel volume is an independent predictor of mortality across all CTD-ILD patients. Furthermore, automated stratification of CALIPER CT variables represents a novel method of prognostication at least as robust as PFTs in CTD-ILD patients.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.