Predicting five year outcomes in adults with cystic fibrosis: Developing a predictive scoring model

Introduction Predicting outcomes in CF is important in order to escalate therapy proportionally and refer patients appropriately for transplantation. In COPD the BODE index is used to predict outcomes, however nothing similar is currently used in CF. Here, a model has been developed to aid in predicting outcomes. Methods Data for 84 CF patients was collected, including lung function, demographics, nutritional status, infection status, and exacerbation rates. The data was compared for patients who died or were listed for transplantation in the subsequent five years (D/Tx), and those who survived. A scoring system was developed using the variables which differed significantly between D/Tx and survivors. The scoring system was validated using a second data set. Results The scoring system was developed using hierarchal regression analysis (Table 1). Scores given using the system differed significantly between survivors and D/Tx (P<0.005). A score ≥7 indicated a 46% absolute risk of D/Tx, compared to a risk of 3% with a score <7. During validation, the scoring system gave significantly different scores to survivors and D/Tx (P<0.005), with a score ≥7 indicating a 43% risk of D/Tx, and a risk of 7% if score <7. Table 1 - Scoring System 0 1 2 3 FEV1 %pred ≥75 64-74 48-63 ≤47 RV/TLC ≤0.34 0.35-0.42 0.43-0.54 ≥0.55 IV days (year prior to review) 0 1-14 15-45 ≥45 Desaturation (incremental shuttle walk) >4% ≥4% Conclusions A scoring system to predict five year outcomes in adults with CF was developed and validated. The model needs to be tested prospectively using data from a wider CF population, and should be compared to current methods used to predict outcomes in CF.