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Updated: Jul 26, 2025
Imaging Features of Systemic Sclerosis-Associated Interstitial Lung Disease
Published on: June 16, 2020
Risk Prediction for Rapidly Progressive Interstitial Lung Disease in Anti-MDA5-Positive Dermatomyositis: The CRAFT
Jinqiang Guo1, Chunli Mei1, Qi Yu2
1Department of Rheumatology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China (mainland).
Abstract:
BACKGROUND Anti-melanoma differentiation-associated protein 5-positive dermatomyositis (MDA5⁺ DM) is characterized by a life-threatening complication of rapidly progressive interstitial lung disease (RP-ILD). Early prediction of RP-ILD can enhance diagnostic accuracy and therapeutic efficacy. This study was conducted to develop a nomogram model for predicting RP-ILD in patients with MDA5⁺ DM. MATERIAL AND METHODS We retrospectively analyzed 53 patients with MDA5⁺ DM, of whom 21 patients were diagnosed with RP-ILD between January 2018 and January 2021. Univariate analysis (t test, Mann-Whitney U test, chi-squared test, or Fisher's exact test) and receiver operating characteristic (ROC) analysis were used to select candidate variables. Multivariate logistic regression analysis was conducted to construct a prediction model, which was subsequently transformed into a nomogram. ROC analysis, calibration curve and decision curve analysis were performed to evaluate the model's performance. The bootstrapping method (resampling=500) was used for internal validation. RESULTS We successfully established a nomogram, called the CRAFT model, to predict RP-ILD in MDA5⁺ DM patients. The model included 4 variables, namely C-reactive protein-to-albumin ratio, red blood cell distribution width-coefficient of variation, fever status, and CD3⁺ T cells. The model presented high predictive power and a good performance in calibration curve and decision curve analysis. In addition, the model had a good predictive ability in internal validation. CONCLUSIONS The CRAFT model could help to predict RP-ILD in patients with MDA5⁺ DM.
Insights
A new CRAFT model can predict rapidly progressive interstitial lung disease (RP-ILD) in patients with anti-melanoma differentiation-associated protein 5-positive dermatomyositis (MDA5⁺ DM). This tool aids early diagnosis and treatment for this severe lung complication.
Area of Science:
- Rheumatology
- Pulmonology
- Medical Diagnostics
Background:
- Anti-melanoma differentiation-associated protein 5-positive dermatomyositis (MDA5⁺ DM) presents a significant risk of life-threatening rapidly progressive interstitial lung disease (RP-ILD).
- Accurate and early prediction of RP-ILD is crucial for timely intervention and improved patient outcomes in MDA5⁺ DM.
Purpose of the Study:
- To develop and validate a predictive model for identifying patients with MDA5⁺ DM at high risk of developing RP-ILD.
- To establish a user-friendly nomogram for clinical application in predicting RP-ILD.
Main Methods:
- Retrospective analysis of 53 MDA5⁺ DM patients, with 21 diagnosed with RP-ILD.
- Statistical analyses including univariate tests, ROC analysis, and multivariate logistic regression to identify predictive variables.
- Development of a nomogram (CRAFT model) and evaluation using ROC, calibration, and decision curve analyses with internal validation via bootstrapping.
Main Results:
- A nomogram, termed the CRAFT model, was successfully developed to predict RP-ILD in MDA5⁺ DM.
- The CRAFT model incorporates C-reactive protein-to-albumin ratio, red blood cell distribution width-coefficient of variation, fever, and CD3⁺ T cells.
- The model demonstrated high predictive power, good calibration, and decision-making utility, with strong internal validation.
Conclusions:
- The CRAFT model offers a valuable tool for predicting RP-ILD in patients diagnosed with MDA5⁺ DM.
- Early identification of RP-ILD risk through the CRAFT model can facilitate prompt therapeutic strategies.
- This predictive model enhances diagnostic accuracy and supports clinical decision-making for managing MDA5⁺ DM patients at risk of severe lung disease.
