title: The CF-ABLE score: a novel clinical prediction rule for prognosis in patients with cystic fibrosis.
abstract: BACKGROUND
  Determining prognosis and predicting outcomes in cystic fibrosis (CF) is a complex issue, and there have been very few clinically applicable models for this. The aim was to create a simple, practical outcome prediction tool for CF.
  
  
  METHODS
  Forty-nine consecutive patients with CF from a single center were studied over an 84-month period (2004-2010). All baseline clinical parameters were gathered, and FEV₁ measurements were analyzed over the study period. Using patterns of FEV₁ decline, a tipping point of 52.8% predicted was identified. Other clinical variables were analyzed and correlated with outcome. Poor outcome was defined as death or transplantation. Using age, BMI, lung function (ie, FEV₁), and number of exacerbations in the past 3 months, the CF-ABLE score was created. The score was validated for data from 370 patients from the national Cystic Fibrosis Registry of Ireland.
  
  
  RESULTS
  The ABLE score uses clinical parameters that are measured at every clinic visit and scored on a scale from 0 to 7. If FEV₁ is < 52%, then 3.5 points are added; if the number of exacerbations in the past 3 months is > 1, then 1.5 points are added; if BMI is < 20.1 kg/m² or age < 24 years, each receive 1 point.
  
  
  CONCLUSIONS
  Patients with a low score have a very low risk of death or lung transplantation within 4 years; however, as the score increases, the risk significantly increases. Patients who score > 5 points have a 26% risk of poor outcome within 4 years. This score is simple and applicable and better predicts outcome than FEV₁ alone.
authors.affiliation: Respiratory Research Division, Royal College of Surgeons in Ireland, Dublin, Ireland; Department of Respiratory Medicine, Beaumont Hospital, Dublin, Ireland. Electronic address: cmccarthy@rcsi.ie.
authors.forename: Cormac
authors.initials: C
authors.lastname: McCarthy
authors.affiliation: Department of Medicine, and Department of General Practice, Royal College of Surgeons in Ireland, Dublin, Ireland; Academic Unit of Primary Care and Population Sciences, University of Southampton, Southampton, England.
authors.forename: Borislav D
authors.initials: BD
authors.lastname: Dimitrov
authors.affiliation: Respiratory Research Division, Royal College of Surgeons in Ireland, Dublin, Ireland; Department of Respiratory Medicine, Beaumont Hospital, Dublin, Ireland.
authors.forename: Imran J
authors.initials: IJ
authors.lastname: Meurling
authors.affiliation: Respiratory Research Division, Royal College of Surgeons in Ireland, Dublin, Ireland; Department of Respiratory Medicine, Beaumont Hospital, Dublin, Ireland.
authors.forename: Cedric
authors.initials: C
authors.lastname: Gunaratnam
authors.affiliation: Respiratory Research Division, Royal College of Surgeons in Ireland, Dublin, Ireland; Department of Respiratory Medicine, Beaumont Hospital, Dublin, Ireland.
authors.forename: Noel G
authors.initials: NG
authors.lastname: McElvaney
mesh_terms: D000328:Adult; D000465:Algorithms; D015992:Body Mass Index; D003550:Cystic Fibrosis / Q000175:diagnosis* / Q000453:epidemiology / Q000503:physiopathology*; D003661:Decision Support Techniques; D005260:Female; D005500:Follow-Up Studies; D005541:Forced Expiratory Volume / Q000502:physiology; D006801:Humans; D007494:Ireland / Q000453:epidemiology; D008137:Longitudinal Studies; D008168:Lung / Q000503:physiopathology*; D008297:Male; D011237:Predictive Value of Tests; D011379:Prognosis; D012042:Registries; D015203:Reproducibility of Results; D012189:Retrospective Studies; D012720:Severity of Illness Index