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.
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.
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.
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.