title: The REVEAL Registry risk score calculator in patients newly diagnosed with pulmonary arterial hypertension.
abstract: BACKGROUND
  In pulmonary arterial hypertension (PAH), survival predictions can be important for optimization of therapeutic strategies. The present study aimed to validate a quantitative algorithm for predicting survival derived from the Registry to Evaluate Early and Long-term PAH Disease Management (REVEAL Registry) and develop a simplified calculator for everyday clinical use.
  
  
  METHODS
  Prospectively collected data from patients with newly diagnosed (< 3 months) World Health Organization group I pulmonary hypertension enrolled in the REVEAL Registry were used to validate a predictive algorithm for 1-year survival. Model calibration was evaluated by comparing algorithm-predicted survival with observed Kaplan-Meier estimates for the overall validation cohort and for five risk groups. Similarly, the risk discriminators for the simplified calculator were compared with those of the quantitative algorithm.
  
  
  RESULTS
  The validation cohort comprised 504 individuals with mean ± SD 6-min walk distance 308 ± 128 m, and 61.5% were functional class III. The proportion of patients surviving 1 year fell within the range predicted by the model (95.1%, 91.5%, 84.6%, 76.3%, and 58.2%, respectively) among patients in the low (predicted survival ≥ 95%), average (90% to < 95%), moderate (85% to < 90%), high (70% to < 85%), and very high (< 70%) risk strata. Predicted and observed 1-year survival were similar across risk stratum, and the c-index indicated good discrimination for both the full equation (0.726) and the simplified risk calculator (0.724).
  
  
  CONCLUSIONS
  The REVEAL Registry predictive algorithm and simplified risk score calculator are well calibrated and demonstrate good discriminatory ability in patients with newly or previously diagnosed PAH.
  
  
  BACKGROUND
  ClinicalTrials.gov; No.: NCT00370214; URL: www.clinicaltrials.gov.
authors.affiliation: Gerald McGinnis Cardiovascular Institute, Allegheny General Hospital, Pittsburgh, PA. Electronic address: RBENZA@wpahs.org.
authors.forename: Raymond L
authors.initials: RL
authors.lastname: Benza
authors.affiliation: Department of Medicine, Section of Cardiology, University of Chicago Medical Center, Chicago, IL.
authors.forename: Mardi
authors.initials: M
authors.lastname: Gomberg-Maitland
authors.affiliation: Statistical Analysis, ICON Late Phase & Outcomes Research, San Francisco, CA.
authors.forename: Dave P
authors.initials: DP
authors.lastname: Miller
authors.affiliation: Department of Medicine, Section of Pulmonary, Critical Care, and Sleep Medicine, Baylor College of Medicine, Houston, TX.
authors.forename: Adaani
authors.initials: A
authors.lastname: Frost
authors.affiliation: Division of Cardiovascular Diseases, Mayo Clinic, Rochester, MN.
authors.forename: Robert P
authors.initials: RP
authors.lastname: Frantz
authors.affiliation: Statistical Analysis, ICON Late Phase & Outcomes Research, San Francisco, CA.
authors.forename: Aimee J
authors.initials: AJ
authors.lastname: Foreman
authors.affiliation: Department of Medicine, Division of Pulmonary Sciences and Critical Care Medicine, and Cardiology, University of Colorado, Denver, CO.
authors.forename: David B
authors.initials: DB
authors.lastname: Badesch
authors.affiliation: Division of Cardiovascular Diseases, Mayo Clinic, Rochester, MN.
authors.forename: Michael D
authors.initials: MD
authors.lastname: McGoon
mesh_terms: D000465:Algorithms; D019468:Disease Management; D005260:Female; D006801:Humans; D006976:Hypertension, Pulmonary / Q000503:physiopathology*; D008297:Male; D008875:Middle Aged; D016016:Proportional Hazards Models; D011446:Prospective Studies; D012042:Registries; D012129:Respiratory Function Tests; D012306:Risk; D018570:Risk Assessment / Q000379:methods*; D016019:Survival Analysis