Combining Clinical and Biological Data to Predict Progressive Pulmonary Fibrosis in Patients With Systemic Sclerosis Despite Immunomodulatory Therapy.
Elizabeth R VolkmannHolly WilhalmeShervin AssassiGrace Hyun J KimJonathan GoldinMasataka KuwanaDonald P TashkinMichael D RothPublished in: ACR open rheumatology (2023)
The SLS II data set provided a unique opportunity to investigate predictors of PPF and develop a nomogram to help clinicians identify patients with SSc-ILD who require closer monitoring while on therapy and potentially an alternative treatment approach. This nomogram warrants external validation in other SSc-ILD cohorts to confirm its predictive power.
Keyphrases
- interstitial lung disease
- systemic sclerosis
- pulmonary fibrosis
- electronic health record
- rheumatoid arthritis
- lymph node metastasis
- big data
- multiple sclerosis
- idiopathic pulmonary fibrosis
- squamous cell carcinoma
- palliative care
- mesenchymal stem cells
- bone marrow
- machine learning
- combination therapy
- deep learning