Abstract
RATIONALE: Loss of lung function in patients with cystic fibrosis (CF) is associated with increased mortality and varies between individuals and over time. Predicting this decline could improve patient management. OBJECTIVES: To develop simple pulmonary outcome prediction (POP) tools to estimate lung function at age 6 in patients aged 2-5 years (POP(2-5)) and lung function change over a 4-year period in patients aged 6-17 years (POP(6-17)). METHODS: Analyses were conducted using patients from the Epidemiologic Study of CF (ESCF). To be included in any analysis, patients had to have 1 year of clinical history recorded in ESCF prior to a clinically stable routine Index Clinic Visit (ICV). In addition to this criterion, for the POP(2-5) tool patients had to be between 2 and 5 years old at ICV and have a second clinically stable visit with spirometric measures at age 6. For the POP(6-17) tool, patients had to be between the ages of 6 and 17 years old at an ICV that included spirometric measures and had to have a second clinically stable visit with spirometric measures from 3 to 5 years after ICV. All patients enrolled in ESCF who met these inclusion criteria were studied. POP(2-5) and POP(6-17) populations were further divided into development groups (with ICV before January 1, 1998) and validation groups (with ICV after that date). Development groups were used to model forced expiratory volume in 1 sec (FEV(1)) percent predicted at age 6 years (for POP(2-5)) and annualized FEV(1) % predicted change from ICV to the second visit (for POP(6-17)) by multivariable linear regression using age, sex, weight-for-age percentile, cough, sputum production, clubbing, crackles, wheeze, sinusitis, number of exacerbations requiring intravenous antibiotics in the past year, elevated liver enzymes, pancreatic enzyme use, and respiratory tract culture status, plus height-for-age percentile (POP(2-5)) and index FEV(1) (POP(6-17)). Integer-based POP(2-5) and POP(6-17) tools created from selected variables were evaluated by Pearson correlation and then prospectively validated with separate data collected later from ESCF patients with ICV after January 1, 1998. MAIN RESULTS: POP(2-5) and POP(6-17) development groups included 2,709 and 6,113 patients and validation groups included 3,458 and 7,086 patients, respectively. Variables retained were weight-for-age percentile, clubbing, crackles, wheeze, number of exacerbations, and Pseudomonas aeruginosa culture status (both tools), daily cough (POP(2-5)), and age, sex, and index FEV(1) % predicted (POP(6-17)). Correlation coefficients for POP(2-5) and POP(6-17) tools prospectively applied to validation groups were +0.32 and +0.37, respectively. CONCLUSIONS: These simple integer-based POP algorithms employ variables available at clinic visits and can be used to predict the probability of different future pulmonary outcomes for individual patients and patient populations.