Date: Sunday, November 5, 2017
Session Type: ACR Poster Session A
Session Time: 9:00AM-11:00AM
Pulmonary hypertension (PH) contributes substantially to systemic sclerosis (SSc)-related morbidity and mortality. It tends to develop later in the disease, creating an opportunity for early risk stratification.
Previously published prediction models for PH have been based on cross-sectional data.
We set out to develop a model predicting PH development within 12 months, accounting for disease duration and utilising time-updated clinical characteristics, including serial measurements of lung function. We compare the use of most recent lung function results and serial changes in lung function over the preceding 4 years.
We used data from a large unselected longitudinal cohort of SSc patients.
Sequential survival analyses with origins set at 6 consecutive landmark (LM) time-points, 12 months apart, starting at 60 months from disease onset were performed. The predictor variables included time-invariant characteristics (sex, subset and autoantibodies) and LM-specific information (age, presence of organ disease, FVC and DLCO, % predicted). Time to PH from the LMs was calculated with censoring at 12 months. Analyses were combined using a stratified Cox proportional hazards model, with each LM representing a stratum.
The study cohort consisted of 652 SSc patients. Of those 41.3% had diffuse SSc, 14.9% were male and the average age at disease onset was 48 years. Most patients (96%) either died during follow-up or were followed for over 10 years from disease onset. At the end of follow-up 13.3% of the subjects had developed PH.
The two final multivariable models both included the values at LM of age, presence of pulmonary fibrosis (PF) and antibody specificities (anti-U3RNP and anti-RNA polymerase (ARA)). Model 1 used most recent DLCO values, while Model 2 incorporated patient-specific intercept and slope of DLCO change over the 4 years prior to the LM (Table 1).
Both models were very similar, demonstrating that older age, ARA and anti-U3RNP positivity increase the hazard for PH development. Lower DLCO, both included as most recent measurement and as intercept and slope for the serial change in DLCO over the 4 years prior to LM, predicted increased hazard for PH. This effect was attenuated by presence of clinically-significant PF. None of the estimated effects varied between LM strata.
The two models had very similar fit and discrimination performance with C-index=0.88 for the model with most recent DLCO and C-index=0.87 for the one using intercept and slope for the linear change in DLCO.
Our results show that comparatively simple models, using only information on age, autoantibodies and serial DLCO assessments could be used for risk stratification and prediction of PH development with good discriminating ability. After validation, this model could be used in clinical practice or for cohort enrichment in clinical trials.
Table 1. Comparison of the two prediction models for PH development
|Model 1||Model 2|
|HR||(95% CI)||p-value||HR||(95% CI)||p-value|
|Anti-RNA polymerase antibody||4.9||(1.91, 12.56)||0.001||4.81||(1.87, 12.35)||0.001|
|Anti-U3RNP antibody||5.97||(1.73, 20.69)||0.005||5.7||(1.62, 20.11)||0.007|
|Age at landmark, years||1.03||(1.00, 1.06)||0.066||1.03||(1.00, 1.07)||0.043|
|DLCO last assessment, %||0.9||(0.87, 0.92)||<0.001|
|DLCO last assessment, % x Pulmonary fibrosis||1.05||(1.03, 1.07)||<0.001|
|DLCO intercept, %||0.91||(0.88, 0.94)||<0.001|
|DLCO intercept, % x Pulmonary fibrosis||1.05||(1.03, 1.08)||<0.001|
|DLCO slope, % (standardised)||0.57||(0.42, 0.79)||0.001|
|Akaike information criterion||320.023||325.192|
|Bayesian information criterion||348.283||359.105|
|Concordance Index (Harrell’s C)||0.8826||0.8724|
To cite this abstract in AMA style:Nihtyanova SI, Ong VH, Derrett-Smith EC, Schreiber B, Coghlan JG, DeStavola B, Denton C. Dynamic Prediction of Pulmonary Hypertension Development in Systemic Sclerosis Patients Using Landmark Analysis – Comparison of Two Models [abstract]. Arthritis Rheumatol. 2017; 69 (suppl 10). https://acrabstracts.org/abstract/dynamic-prediction-of-pulmonary-hypertension-development-in-systemic-sclerosis-patients-using-landmark-analysis-comparison-of-two-models/. Accessed April 16, 2021.
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