Background:The staging of interstitial lung disease (ILD) is important to monitor disease progression and for prognostication. A disease severity scale of Systemic Sclerosis (SSc)-related lung disease has long been proposed (i.e. Medsger’s severity scale). This scale was mostly developed by discussion and consensus and stage thresholds were not computed by a data-driven approach. Hidden Markov models (HMM) are methods to estimate population quantities for chronic diseases with a staged interpretation which are diagnosed by markers measured at irregular intervals.Objectives:To build a SSc-ILD specific disease severity scale with prognostic relevance via HMM modeling.Methods:A total of 358 SSc patients at risk for or with ILD were enrolled in a discovery (207 cases, Milan1) and in a validation (151 cases, Milan2, Pavia and Rome) cohort. Patients were included if satisfied the following criteria: 1) Diagnosis of SSc according to the EULAR/ACR 2013 criteria, 2) absence of anticentromere antibodies, 3) dcSSc subset or 4) other subsets with either 4a) ILD-related antibodies (Scl70, PmScl, Ku) or 4b) evidence of ILD on HRCT, 5) disease duration < 5 years at the time of the first pulmonary function test (PFT). Serial PFTs were retrieved and the time up to the last available visit -if the patient alive-, or to death due to pulmonary complications, was recorded. HMM were used to estimate the threshold of a 3-stage model (SL3SI, Scleroderma Lung 3-Stage Index) based on PFT functional values (normal/mild, moderate, severe involvement) in the discovery cohort. Survival estimates of the SL3SI model were compared to Medsger’s severity classes estimates and their predictive capability evaluated via the explained residual variation (R2) of prediction errors (the higher the better). One-hundred random replicates were generated to simulate the prediction effort in patients with different disease duration and lung severity.Results:Patients characteristics are summarized in the Table. Fifteen-years survival estimates for Mesdger’s classes in the discovery set were: normal=0.88, mild=0.86, moderate=0.84 and severe=0.71. The SL3SI was defined by the following thresholds: normal/mild, FVC and DLco >=75%; moderate FVC or DLco 74-55%; severe, FVC or DLco <55%. SL3SI 15-yrs survival estimates were: normal/mild=0.89, moderate=0.82 and severe=0.63. Prediction analysis showed a higher R2values at 15 yrs for the SL3SI compared to Medsger’s classes, providing evidence for a better predictive capability of the former (discovery: 0.31 vs 0.25; validation: 0.28 vs 0.19).Conclusion:The SL3SI, a simplified 3-stage functional model of SSc-ILD, yields better survival estimates and long-term prognostic information than Medsger’s classes. Its reproducibility and ease of use make it a useful tool for the functional and prognostic evaluation of SSc patients at risk for or with ILD.Table:VariablesDiscovery (n=207)Replication (n=151)DcSSc62 (30%)98 (64%)Age at first PFR48.6±1249.1±14.4Disease duration at first PFR1.7±1.61.3±2.4FVC90.5±18.191.1±20.2DLco70.7±19.861.3±20.1ILD on HRCT179 (86%)125 (80%)Scl70157 (76%)153 (78%)SSA63 (30%)32 (21%)n of visits38571473Follow-up time, yrs11±5.610.6±5.7Deaths27 (13%)23 (15%)Disclosure of Interests:Alessandro Santaniello: None declared, Chiara Bellocchi: None declared, Luca Bettolini: None declared, Marcello Cassavia: None declared, Gaia Montanelli: None declared, Adriana Severino: None declared, Monica Caronni: None declared, Corrado Campochiaro Speakers bureau: Novartis, Pfizer, Roche, GSK, SOBI, Enrico De Lorenzis: None declared, Gerlando Natalello: None declared, Paolo Delvino: None declared, Claudio Tirelli: None declared, Lorenzo Cavagna: None declared, Giacomo De Luca Speakers bureau: SOBI, Novartis, Celgene, Pfizer, MSD, Silvia Laura Bosello: None declared, Lorenzo Beretta Grant/research support from: Pfizer
Genetic Segregation of Inflammatory Lung Disease and Autoimmune Disease Severity in SHIP-1−/−Mice
