ArticleRMD open2024
Prediction of progressive fibrosing interstitial lung disease in patients with systemic sclerosis: insight from the CRDC cohort study.
Article in RMD open, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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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.
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Who cites it
3 citing papers in PubMed, 4 citations in OpenAlex.
- Sex Disparity in Systemic Sclerosis-Associated Pulmonary Fibrosis.International journal of molecular sciences · 2026Article
- Harnessing artificial intelligence to advance insights in systemic sclerosis skin and lung disease.Current opinion in rheumatology · 2025Review
- Prediction of progressive fibrosing interstitial lung disease in patients with systemic sclerosis: insight from the CRDC cohort study.RMD open · 2024Article
Corrections and comments
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Authors and funding
9 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThis study aims to establish a reliable prediction model of progressive fibrosing interstitial lung disease (PF-ILD) in patients with systemic sclerosis (SSc)-ILD, to achieve early risk stratification and to help better in preventing disease progression.
methods304 SSc-ILD patients with no less than three pulmonary function tests within 6-24 months were included. We collected data at baseline and compared differences between SSc patients with and without PF-ILD. Least absolute shrinkage and selection operator regularisation regression and multivariable Cox regression were used to construct the prediction model, which were presented as nomogram and forest plot.
resultsAmong the 304 patients with SSc-ILD included, 92.1% were women, with a baseline average age of 46.7 years. Based on the 28 variables preselected by comparison between SSc patients without PF-ILD group (n=150) and patients with SSc PF-ILD group (n=154), a 9-variable prediction model was constructed, including age≥50 years (HR 1.8221, p=0.001), hyperlipidemia (HR 4.0516, p<0.001), smoking history (HR 3.8130, p<0.001), diffused cutaneous SSc subtype (HR 1.9753, p<0.001), arthritis (HR 2.0008, p<0.001), shortness of breath (HR 2.0487, p=0.012), decreased serum immunoglobulin A level (HR 2.3900, p=0.002), positive anti-Scl-70 antibody (HR 1.9573, p=0.016) and usage of cyclophosphamide/mycophenolate mofetil (HR 0.4267, p<0.001). The concordance index after enhanced bootstrap resampling adjustment was 0.874, while the optimism-corrected Brier Score was 0.144 in internal validation.
conclusionThis study developed the first prediction model for PF-ILD in patients with SSc-ILD, and internal validation showed favourable accuracy and stability of the model.
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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.