☆ 4.7 Review

The Use and Utility of Machine Learning in Achieving Precision Medicine in Systemic Sclerosis: A Narrative Review

JOURNAL OF PERSONALIZED MEDICINE (2022)

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Article Respiratory System

Computed tomography-based radiomics decodes prognostic and molecular differences in interstitial lung disease related to systemic sclerosis

Janine Schniering et al.

Summary: This study explored the use of radiomic features for disease characterisation, risk stratification, and relaying information on lung pathophysiology in patients with systemic sclerosis associated interstitial lung disease (SSc-ILD). The study identified two distinct patient clusters based on radiomic profiling and derived a quantitative radiomic risk score that accurately predicted progression-free survival. The score was validated in a cross-species approach and correlated with fibrotic pathway activation. Radiomics-based risk stratification using routine CT images provides important clinical and prognostic information for clinical decision making in SSc-ILD.

EUROPEAN RESPIRATORY JOURNAL (2022)

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Article Rheumatology

A Machine Learning Approach for Predicting Sustained Remission in Rheumatoid Arthritis Patients on Biologic Agents

Vincenzo Venerito et al.

Summary: Machine learning models can be used to predict sustained remission in rheumatoid arthritis patients on biologic disease-modifying antirheumatic drugs (bDMARDs). The method relies on a few easy-to-collect patient attributes.

JCR-JOURNAL OF CLINICAL RHEUMATOLOGY (2022)

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Article Rheumatology

Predictors of rituximab effect on modified Rodnan skin score in systemic sclerosis: a machine-learning analysis of the DesiReS trial

Satoshi Ebata et al.

Summary: A post-hoc analysis of data from a clinical trial investigating the effectiveness of rituximab in patients with systemic sclerosis identified CD19-positive cell counts, modified Rodnan skin score (mRSS), and serum surfactant protein D (SP-D) levels as factors influencing the response to treatment. Patients with high CD19-positive cell counts and high mRSS showed the greatest improvement in mRSS with rituximab.

RHEUMATOLOGY (2022)

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Article Peripheral Vascular Disease

Characterization of Salivary Microbiota of a in Patients with Atherosclerotic Cardiovascular Disease: A Case-Control Study

Nahoko Kato-Kogoe et al.

Summary: This study investigated the differences in salivary microbiota between patients with atherosclerotic cardiovascular disease (ACVD) and individuals without ACVD, and characterized the salivary microbiota of patients with ACVD. The study found distinct salivary microbiota in patients with ACVD compared to non-ACVD individuals.

JOURNAL OF ATHEROSCLEROSIS AND THROMBOSIS (2022)

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Article Immunology

A Machine Learning Approach to Predict Remission in Patients With Psoriatic Arthritis on Treatment With Secukinumab

Vincenzo Venerito et al.

Summary: Machine learning algorithm can accurately predict the probability of remission in PsA patients on Secukinumab treatment. XGBoost algorithm outperforms LR algorithm in predicting 12-month DAPSA remission. Baseline DAPSA, fibromyalgia, and axial disease are the most important factors in the prediction algorithm.

FRONTIERS IN IMMUNOLOGY (2022)

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Article Rheumatology

Machine learning integration of scleroderma histology and gene expression identifies fibroblast polarisation as a hallmark of clinical severity and improvement

Kimberly Showalter et al.

Summary: Histologic and gene expression features were investigated in early diffuse cutaneous systemic sclerosis (dcSSc) to determine clinical improvement. The study found that CD34 and aSMA staining patterns can predict gene expression subsets and are associated with clinical assessments. Furthermore, a 47-gene fibroblast polarisation signature was identified in clinical improvers with CD34 and aSMA binarised scores.

ANNALS OF THE RHEUMATIC DISEASES (2021)

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Article Respiratory System

Identifying early pulmonary arterial hypertension biomarkers in systemic sclerosis: machine learning on proteomics from the DETECT cohort

Yasmina Bauer et al.

Summary: This study identified a novel eight-protein biomarker panel that can discriminate between SSc patients with and without PAH. The findings suggest that this biomarker panel has the potential to improve early detection of PAH in SSc patients and may provide new insights into the pathogenesis of PAH in the context of SSc.

EUROPEAN RESPIRATORY JOURNAL (2021)

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Article Medicine, General & Internal

A convolutional neural network with transfer learning for automatic discrimination between low and high-grade synovitis: a pilot study

Vincenzo Venerito et al.

Summary: This study demonstrates that computer vision with transfer learning is suitable for scoring synovitis, which may help personalize treatment for patients with arthritis.

INTERNAL AND EMERGENCY MEDICINE (2021)

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Article Critical Care Medicine

Safety and Efficacy of B-Cell Depletion with Rituximab for the Treatment of Systemic Sclerosis-associated Pulmonary Arterial Hypertension A Multicenter, Double-Blind, Randomized, Placebo-controlled Trial

Roham T. Zamanian et al.

Summary: The study suggested that B-cell depletion therapy may have potential efficacy and safety for SSc-PAH. Low levels of RF, IL-12, and IL-17 may serve as promising predictors of rituximab response. Despite initially showing no significant difference in the primary analysis, the rituximab group demonstrated a statistically significant improvement in 6MWD at Week 24 when considering data through Week 48.

AMERICAN JOURNAL OF RESPIRATORY AND CRITICAL CARE MEDICINE (2021)

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Article Engineering, Biomedical

Machine learning associated with respiratory oscillometry: a computer-aided diagnosis system for the detection of respiratory abnormalities in systemic sclerosis

Domingos S. M. Andrade et al.

Summary: This study evaluates the performance of various machine learning algorithms in diagnosing respiratory changes in patients with systemic sclerosis. The findings suggest that combining oscillometric principles with machine learning algorithms could assist in the early diagnosis of respiratory changes in these patients.

BIOMEDICAL ENGINEERING ONLINE (2021)

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Article Medicine, General & Internal

A Machine Learning Application to Predict Early Lung Involvement in Scleroderma: A Feasibility Evaluation

Giuseppe Murdaca et al.

Summary: Machine Learning algorithms can be used to predict early lung involvement in Systemic sclerosis (SSc) patients and provide useful exams for diagnostic purposes. The random forest algorithm performed well in this study, however, other classifiers are also valuable when shorter response time is needed.

DIAGNOSTICS (2021)

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Article Rheumatology

Progression of patients with Raynaud's phenomenon to systemic sclerosis: a five-year analysis of the European Scleroderma Trial and Research group multicentre, longitudinal registry study for Very Early Diagnosis of Systemic Sclerosis (VEDOSS)

Silvia Bellando-Randone et al.

Lancet Rheumatology (2021)

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Review Oncology

Systemic sclerosis (scleroderma): remaining challenges

Mary Karin Connolly

Summary: Effective treatments for cutaneous fibrosis in systemic sclerosis remain elusive, with none of the disease-modifying antirheumatic drugs showing proven efficacy. This review article highlights the challenges in assessing meaningful clinical trials and the lack of understanding of the basic molecular mechanisms driving pathologic fibrosis in the disease.

ANNALS OF TRANSLATIONAL MEDICINE (2021)

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Exploring the Oral Microbiome in Rheumatic Diseases, State of Art and Future Prospective in Personalized Medicine with an AI Approach

Silvia Bellando-Randone et al.

Summary: The oral microbiome plays a potential role in various rheumatic diseases, serving as promising diagnostic biomarkers. Emphasis is placed on its involvement in conditions like rheumatoid arthritis, Sjogren's syndrome, and systemic lupus erythematosus.

JOURNAL OF PERSONALIZED MEDICINE (2021)

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Article Rheumatology

New risk model is able to identify patients with a low risk of progression in systemic sclerosis

Nina Marijn van Leeuwen et al.

Summary: A machine learning model was developed to predict disease progression in systemic sclerosis patients, using data from a prospective cohort. Relevant clinical variables were identified for predicting disease progression.

RMD OPEN (2021)

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Article Rheumatology

The multifaceted problem of pulmonary arterial hypertension in systemic sclerosis

Cosimo Bruni et al.

Summary: This paragraph highlights the significance of cardiopulmonary complications in systemic sclerosis, particularly pulmonary hypertension. It also emphasizes the importance of early screening and detection, as well as the need for a holistic treatment approach targeting multiple components of the disease.

LANCET RHEUMATOLOGY (2021)

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Editorial Material Rheumatology

Recent advances steer the future of systemic sclerosis toward precision medicine

Gemma Lepri et al.

CLINICAL RHEUMATOLOGY (2020)

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Review Rheumatology

Drug repurposing to improve treatment of rheumatic autoimmune inflammatory diseases

Kathryn M. Kingsmore et al.

NATURE REVIEWS RHEUMATOLOGY (2020)

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Review Medicine, General & Internal

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Cosimo Bruni et al.

EUROPEAN JOURNAL OF INTERNAL MEDICINE (2020)

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Machine learning predicts stem cell transplant response in severe scleroderma

Jennifer M. Franks et al.

ANNALS OF THE RHEUMATIC DISEASES (2020)

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Giovanni Cammarota et al.

NATURE REVIEWS GASTROENTEROLOGY & HEPATOLOGY (2020)

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Transcriptional insights into pathogenesis of cutaneous systemic sclerosis using pathway driven meta-analysis assisted by machine learning methods

Xiao Xu et al.

PLOS ONE (2020)

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Deep Learning-based Approach for Automated Assessment of Interstitial Lung Disease in Systemic Sclerosis on CT Images

Guillaume Chassagnon et al.

RADIOLOGY-ARTIFICIAL INTELLIGENCE (2020)

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Article Rheumatology

The identification and management of interstitial lung disease in systemic sclerosis: evidence-based European consensus statements

Anna-Maria Hoffmann-Vold et al.

LANCET RHEUMATOLOGY (2020)

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Review Rheumatology

Use of artificial intelligence in imaging in rheumatology - current status and future perspectives

Berend Stoel

RMD OPEN (2020)

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Article Rheumatology

A Machine Learning Classifier for Assigning Individual Patients With Systemic Sclerosis to Intrinsic Molecular Subsets

Jennifer M. Franks et al.

ARTHRITIS & RHEUMATOLOGY (2019)

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Letter Medicine, General & Internal

Deep medicine, artificial intelligence, and the practising clinician

Claude Matuchansky

LANCET (2019)

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Review Biochemistry & Molecular Biology

High-performance medicine: the convergence of human and artificial intelligence

Eric J. Topol

NATURE MEDICINE (2019)

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Article Medical Informatics

An image-based deep learning framework for individualising radiotherapy dose: a retrospective analysis of outcome prediction

Bin Lou et al.

LANCET DIGITAL HEALTH (2019)

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Editorial Material Respiratory System

Pulmonary arterial hypertension: screening challenges in systemic sclerosis and future directions

Nermin Diab et al.

EUROPEAN RESPIRATORY JOURNAL (2017)

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Article Dermatology

A Functional Genomic Meta-Analysis of Clinical Trials in Systemic Sclerosis: Toward Precision Medicine and Combination Therapy

Jaclyn N. Taroni et al.

JOURNAL OF INVESTIGATIVE DERMATOLOGY (2017)

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Review Rheumatology

The genetics revolution in rheumatology: large scale genomic arrays and genetic mapping

Stephen Eyre et al.

NATURE REVIEWS RHEUMATOLOGY (2017)

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Article Rheumatology

Early Mortality in a Multinational Systemic Sclerosis Inception Cohort

Yanjie Hao et al.

ARTHRITIS & RHEUMATOLOGY (2017)

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Pathogenesis of systemic sclerosis: recent insights of molecular and cellular mechanisms and therapeutic opportunities

John Varga et al.

JOURNAL OF SCLERODERMA AND RELATED DISORDERS (2017)

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Muriel Elhai et al.

ANNALS OF THE RHEUMATIC DISEASES (2017)

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Review Rheumatology

Management of connective tissue diseases associated interstitial lung disease: a review of the published literature

Beth Wallace et al.

CURRENT OPINION IN RHEUMATOLOGY (2016)

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Editorial Material Computer Science, Artificial Intelligence

Machine learning approaches in medical image analysis: From detection to diagnosis

Marleen de Bruijne

MEDICAL IMAGE ANALYSIS (2016)

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Clinical Trial Design Issues in Systemic Sclerosis: an Update

Jessica K. Gordon et al.

CURRENT RHEUMATOLOGY REPORTS (2016)

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JOURNAL OF SCLERODERMA AND RELATED DISORDERS (2016)

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Sally J. Deeb et al.

MOLECULAR & CELLULAR PROTEOMICS (2015)

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M. I. Jordan et al.

SCIENCE (2015)

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Jasmin Raja et al.

SEMINARS IN IMMUNOPATHOLOGY (2015)

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Article Biochemical Research Methods

Systems Level Analysis of Systemic Sclerosis Shows a Network of Immune and Profibrotic Pathways Connected with Genetic Polymorphisms

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PLOS COMPUTATIONAL BIOLOGY (2015)

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PLoS One (2014)

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Article Dermatology

Molecular Signatures in Skin Associated with Clinical Improvement during Mycophenolate Treatment in Systemic Sclerosis

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JOURNAL OF INVESTIGATIVE DERMATOLOGY (2013)

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Extent of disease on high-resolution computed tomography lung is a predictor of decline and mortality in systemic sclerosis-related interstitial lung disease

Owen A. Moore et al.

RHEUMATOLOGY (2013)

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Intrinsic Gene Expression Subsets of Diffuse Cutaneous Systemic Sclerosis Are Stable in Serial Skin Biopsies

Sarah A. Pendergrass et al.

JOURNAL OF INVESTIGATIVE DERMATOLOGY (2012)

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JOURNAL OF COMPUTER ASSISTED TOMOGRAPHY (2011)

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Risk factors for death and the 3-year survival of patients with systemic sclerosis: the French ItinrAIR-Sclrodermie study

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Prevalence and outcome in systemic sclerosis associated pulmonary arterial hypertension: application of a registry approach

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