Sex-specific difference in cardiac function in patients with systemic sclerosis: association with cardiovascular outcomes.

BACKGROUND: Cardiovascular involvement is one of the leading causes of mortality in systemic sclerosis (SSc) and is reported to be higher in men as compared with women. However, the cause of this difference is largely unknown. The objective of this study was to assess sex differences in echocardiographic characteristics, including left ventricular global longitudinal strain (LV GLS), as a potential explanation of sex differences in outcomes. METHODS: A total of 746 patients with SSc from four centres, including 628 (84%, 54±13 years) women and 118 (16%, 55±15 years) men, were evaluated with standard and advanced echocardiographic examinations. The independent association of the echocardiographic parameters with the combined endpoint of cardiovascular events-hospitalisation/death was evaluated. RESULTS: Men and women with SSc showed significant differences in disease characteristics and cardiac function. After adjusting for the most important clinical characteristics, while LV ejection fraction and diastolic function were not significantly different anymore, men still presented with more impaired LV GLS as compared with women (-19% (IQR -20% to -17%) vs -21% (IQR: -22% to -19%), p<0.001). After a median follow-up of 48 months (IQR: 26-80), the combined endpoint occurred in 182 patients. Men with SSc experienced higher cumulative rates of cardiovascular events-hospitalisation/mortality (χ2=8.648; Log-rank=0.003), and sex differences were maintained after adjusting for clinical confounders, but neutralised when matching the groups for LV GLS. CONCLUSION: In patients with SSc, male sex is associated with worse cardiovascular outcomes even after adjusting for important clinical characteristics. LV GLS was more impaired in men as compared with women and potentially explains the sex difference in cardiovascular outcomes.

Step forward in early recognition of systemic sclerosis: data from the Leiden CCISS cohort.

BACKGROUND: Since 2009, Dutch patients with a confirmed diagnosis/suspicion of systemic sclerosis (SSc) can be referred to the Leiden Combined Care in Systemic Sclerosis (CCISS) cohort. This study evaluated whether early recognition of SSc has improved over time and whether disease characteristics and survival has changed over time. METHODS: 643 SSc patients fulfilling American College of Rheumatology/European Alliance of Associations for Rheumatology 2013 SSc criteria were included and categorised into three groups based on cohort-entry year: (1) 2010-2013 (n=229 (36%)), (2) 2014-2017 (n=207 (32%)) and (3) 2018-2021 (n=207 (32%)). Variables including disease duration, interstitial lung disease (ILD), digital ulcers (DU), diffuse cutaneous SSc (dcSSc), antitopoisomerase (ATA) and anticentromere (ACA) antibodies, and survival from disease onset were compared between cohort-entry groups, including analyses stratified for sex and autoantibodies. RESULTS: Over time, duration between onset of disease symptoms and cohort entry decreased in males and females, but was always longer in females than in males.The proportion of patients presenting with DU decreased, especially in ACA+SSc patients. Almost no ACA+ patients presented with ILD, while in ATA+ patients this proportion was 25% in 2010-2013 and decreased to 19% in 2018-2021. A reduction in patients presenting with clinically meaningful ILD and dcSSc was observed.Overall 8-year survival for males was 59% (95% CI 40% to 73%) and for females 89% (95% CI 82% to 93%). Eight-year survival showed a trend for improvement over time, and was always worse in males. CONCLUSION: We observed a decrease in disease duration in Leiden CCISS cohort at cohort entry, possibly indicating more timely diagnosis of SSc. This could provide opportunities for early interventions. While symptom duration at presentation is longer in females, mortality is consistently higher in males, underlining the urge for sex-specific treatment and follow-up.

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

OBJECTIVES: To develop a prediction model to guide annual assessment of systemic sclerosis (SSc) patients tailored in accordance to disease activity. METHODS: A machine learning approach was used to develop a model that can identify patients without disease progression. SSc patients included in the prospective Leiden SSc cohort and fulfilling the ACR/EULAR 2013 criteria were included. Disease progression was defined as progression in ≥1 organ system, and/or start of immunosuppression or death. Using elastic-net-regularisation, and including 90 independent clinical variables (100% complete), we trained the model on 75% and validated it on 25% of the patients, optimising on negative predictive value (NPV) to minimise the likelihood of missing progression. Probability cutoffs were identified for low and high risk for disease progression by expert assessment. RESULTS: Of the 492 SSc patients (follow-up range: 2-10 years), disease progression during follow-up was observed in 52% (median time 4.9 years). Performance of the model in the test set showed an AUC-ROC of 0.66. Probability score cutoffs were defined: low risk for disease progression (<0.197, NPV:1.0; 29% of patients), intermediate risk (0.197-0.223, NPV:0.82; 27%) and high risk (>0.223, NPV:0.78; 44%). The relevant variables for the model were: previous use of cyclophosphamide or corticosteroids, start with immunosuppressive drugs, previous gastrointestinal progression, previous cardiovascular event, pulmonary arterial hypertension, modified Rodnan Skin Score, creatine kinase and diffusing capacity for carbon monoxide. CONCLUSION: Our machine-learning-assisted model for progression enabled us to classify 29% of SSc patients as 'low risk'. In this group, annual assessment programmes could be less extensive than indicated by international guidelines.