A MULTIVARIATE MODEL FOR PREDICTING RESPIRATORY STATUS IN PATIENTS WITH CHRONIC-OBSTRUCTIVE-PULMONARY-DISEASE

OBJECTIVE: To develop and validate a multivariate model far predicting respiratory status in patients with advanced chronic obstructive pulm onary disease (COPD). DESIGN: prospective, double-blind study of peak flow monitoring, SETTING:Albuquerque Veterans Affairs Medical Center. PATIENTS: Male veterans with an irreversible component of airflow obst ruction on baseline pulmonary function tests. MEASUREMENTS: This study was conducted between January 1995 and May 1998. At entry, subjects w ere instructed in the use of the modified Medical Research Council Dys pnea Scale and a mini-Wright peak Plow meter equipped with electronic storage. For the next 6 months, they recorded their dyspnea scores onc e daily and peak expiratory flow rates twice daily, before and after t he use of bronchodilators. Patients were blinded to their peak expirat ory now rates, and medical care was provided in the customary manner. Readings were aggregated into 7-day sampling intervals, and interval m eans were calculated for dyspnea scope and peak expiratory flow rate p arameters. Intervals from all subjects were then pooled and randomized tea separate groups for model development (training set) and validati on (test set). En the training set, logistic regression was used to id entify variables that predicted future respiratory status. The depende nt variable was the log odds that the subject would attain his highest Bevel of dyspnea in the next 7 days. The final model was used to stra tify the test set into ''high-risk'' and ''low-risk'' categories. The analysis was repeated for 3-day intervals, MAIN RESULTS: Of the 40 pat ients considered eligible for study, 8 declined to participate, 4 coul d not master the technique of peak flow monitoring, and 6 had no fluct uations in their dyspnea level. The remaining 22 subjects form the bas is of this report. Fourteen (64%) of the latter completed the 6-month protocol. Data from the 8 who were dropped or died were included up to the point of withdrawal. For 7-day forecasts, mean dyspnea score and mean daily prebronchodilator peak expiratory flow rate were identified as predictor variables. The adjusted odds ratio (OR) for mean dyspnea score was 2.71 (95% confidence interval [CI] 1.79, 4.12) per unit. Fo r mean prebronchodilator peak expiratory flow rate, it was 1.05 (95% C I I.ol, 1.09) per percentage predicted. For 3-day forecasts, the model was composed of mean dyspnea scare and mean daily bronchodilator resp onse. The ORs for these terms were 2.66 (95% CI 2.06, 3.44) per unit a nd 0.980 (95% CI 0.962, 0.998) per percentage of improvement over base line, respectively. For a given level of dyspnea, higher prebronchodil ator peak expiratory now rate and lower bronchodilator response were p oor prognostic findings. When the models were applied to the Lest sets , ''high-risk'' intervals were 4 times more likely to be followed by m aximal symptoms than ''low-risk'' intervals. CONCLUSIONS: Dyspnea scor es and certain peak expiratory flow rate parameters are independent pr edictors of respiratory status in patients with COPD. However, our res ults suggest that monitoring is of little benefit except in patients w ith the most advanced form of this disease, and its contribution to th eir management is modest at best.