Lung Function and Survival in Systemic Sclerosis Interstitial Lung Disease

Ahmed, Samar Shadly; Meaney, Christopher; Chau, Cathy; Marras, Theodore K.

doi:10.3899/jrheum.140156

Cited by 12 publications

(6 citation statements)

References 10 publications

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“…A large SSc-ILD cohort study demonstrated that FVC (hazard ratio [HR] 0.97; p=0.0009), DL CO (HR 0.97; p=0.0004) and increasing age (HR 1.03; p=0.04) were significantly associated with mortality after adjusting for sex, body mass index, smoking status, serology, disease subtype and immunosuppressive use [66]. A recent analysis showed that a decline in FVC or DL CO over 2 years was a better predictor of mortality than baseline FVC and DL CO [10].…”

Section: Risk Factors For Progression Of Ildmentioning

confidence: 99%

Predictors of progression in systemic sclerosis patients with interstitial lung disease

Assassi²,

et al. 2020

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Systemic sclerosis (SSc) is a systemic autoimmune disease affecting multiple organ systems, including the lungs. Interstitial lung disease (ILD) is the leading cause of death in SSc.There are no valid biomarkers to predict the occurrence of SSc-ILD, although auto-antibodies against anti-topoisomerase I and several inflammatory markers are candidate biomarkers that need further evaluation. Chest auscultation, presence of shortness of breath and pulmonary function testing are important diagnostic tools, but lack sensitivity to detect early ILD. Baseline screening with high-resolution computed tomography (HRCT) is therefore necessary to confirm an SSc-ILD diagnosis. Once diagnosed with SSc-ILD, patients' clinical courses are variable and difficult to predict, although certain patient characteristics and biomarkers are associated with disease progression. It is important to monitor patients with SSc-ILD for signs of disease progression, although there is no consensus about which diagnostic tools to use or how often monitoring should occur. In this article, we review methods used to define and predict disease progression in SSc-ILD.There is no valid definition of SSc-ILD disease progression, but we suggest that either a decline in forced vital capacity (FVC) from baseline of ≥10%, or a decline in FVC of 5–9% in association with a decline in diffusing capacity of the lung for carbon monoxide of ≥15% represents progression. An increase in the radiographic extent of ILD on HRCT imaging would also signify progression. A time period of 1–2 years is generally used for this definition, but a decline over a longer time period may also reflect clinically relevant disease progression.

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Section: Risk Factors For Progression Of Ildmentioning

confidence: 99%

Predictors of progression in systemic sclerosis patients with interstitial lung disease

Assassi²,

et al. 2020

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“…Other published risk factors for developing ILD include higher baseline skin score, dcSSc (versus lcSSc), dcSSc with an inflammatory skin phenotype, and particularly antitopoisomerase I antibody positivity [37,[70][71][72]. In patients with SSc-ILD specifically, some studies have shown that PFT values, HRCT patterns and other factors in the early stages of the disease are correlated with long-term outcomes [2,4,5,30,71,[73][74][75][76][77][78][79]. In particular, low FVC seems to be strongly associated with faster disease progression as it was the most frequent risk factor in these studies (table 2).…”

Section: Risk Factors For Development and Progression Of Ssc-ildmentioning

confidence: 99%

Natural variability in the disease course of SSc-ILD: implications for treatment

et al. 2021

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Interstitial lung disease (ILD) affects approximately 50% of patients with systemic sclerosis (SSc) and is the leading cause of death in SSc. Our objective was to gain insight into the progression of SSc-associated ILD (SSc-ILD). Using data from longitudinal clinical trials and observational studies, we assessed definitions and patterns of progression, risk factors for progression, and implications for treatment. SSc-ILD progression was commonly defined as exceeding specific thresholds of lung function worsening and/or increasing radiographic involvement. One definition used in several studies is decline in forced vital capacity (FVC) of ≥10%, or ≥5–10% plus a decline in diffusing capacity of the lung for carbon monoxide ≥15%. Based on these criteria, 20–30% of patients in observational cohorts develop progressive ILD, starting early in the disease course and progressing at a highly variable rate.Risk factors such as age, FVC, extent of fibrosis and presence of anti-topoisomerase I antibodies can help predict progression of SSc-ILD, though composite risk scores may offer greater predictive power. Whilst the variability of the disease course in SSc-ILD makes risk stratification of patients challenging, the decision to initiate, change or stop treatment should be based on a combination of the current disease state and the speed of progression.

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“…Values for DL CO were referenced to those reported in [ 28 , 29 ]. Presence of ILD was defined as a FVC value less than 80 % of standardized predicted value [ 30 , 31 ] – but we note that there exist other thresholds, most commonly, < 70 % [ 32 , 33 ] – and confirmed in some cases by presence of fibrosis on high-resolution computerized tomography of the chest.…”

Section: Methodsmentioning

confidence: 99%

A methodology for exploring biomarker – phenotype associations: application to flow cytometry data and systemic sclerosis clinical manifestations

et al. 2015

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BackgroundThis work seeks to develop a methodology for identifying reliable biomarkers of disease activity, progression and outcome through the identification of significant associations between high-throughput flow cytometry (FC) data and interstitial lung disease (ILD) - a systemic sclerosis (SSc, or scleroderma) clinical phenotype which is the leading cause of morbidity and mortality in SSc. A specific aim of the work involves developing a clinically useful screening tool that could yield accurate assessments of disease state such as the risk or presence of SSc-ILD, the activity of lung involvement and the likelihood to respond to therapeutic intervention. Ultimately this instrument could facilitate a refined stratification of SSc patients into clinically relevant subsets at the time of diagnosis and subsequently during the course of the disease and thus help in preventing bad outcomes from disease progression or unnecessary treatment side effects.The methods utilized in the work involve: (1) clinical and peripheral blood flow cytometry data (Immune Response In Scleroderma, IRIS) from consented patients followed at the Johns Hopkins Scleroderma Center. (2) machine learning (Conditional Random Forests - CRF) coupled with Gene Set Enrichment Analysis (GSEA) to identify subsets of FC variables that are highly effective in classifying ILD patients; and (3) stochastic simulation to design, train and validate ILD risk screening tools.ResultsOur hybrid analysis approach (CRF-GSEA) proved successful in predicting SSc patient ILD status with a high degree of success (>82 % correct classification in validation; 79 patients in the training data set, 40 patients in the validation data set).ConclusionsIRIS flow cytometry data provides useful information in assessing the ILD status of SSc patients. Our new approach combining Conditional Random Forests and Gene Set Enrichment Analysis was successful in identifying a subset of flow cytometry variables to create a screening tool that proved effective in correctly identifying ILD patients in the training and validation data sets. From a somewhat broader perspective, the identification of subsets of flow cytometry variables that exhibit coordinated movement (i.e., multi-variable up or down regulation) may lead to insights into possible effector pathways and thereby improve the state of knowledge of systemic sclerosis pathogenesis.Electronic supplementary materialThe online version of this article (doi:10.1186/s12859-015-0722-x) contains supplementary material, which is available to authorized users.

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Lung Function and Survival in Systemic Sclerosis Interstitial Lung Disease

Cited by 12 publications

References 10 publications

Predictors of progression in systemic sclerosis patients with interstitial lung disease

Predictors of progression in systemic sclerosis patients with interstitial lung disease

Natural variability in the disease course of SSc-ILD: implications for treatment

A methodology for exploring biomarker – phenotype associations: application to flow cytometry data and systemic sclerosis clinical manifestations

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