Identifying COPD patients at increased risk of mortality: predictive value of clinical study baseline data

Identifying chronic obstructive pulmonary disease (COPD) patients at increased risk of mortality is an important component of effective disease management.

A pooled analysis of patients with severe COPD, from two well-controlled 1-year studies, was conducted using Cox regression and spline analysis to evaluate predictability of baseline demographic data and in-study variables for mortality risk, and to evaluate the effect of treatment allocation to budesonide and formoterol, versus their respective control groups, on these outcomes.

In the pooled analysis, a Cox regression model reported a higher baseline St George's Respiratory Questionnaire (SGRQ) total score as a significant predictor of mortality (hazard ratio 1.037 [95% confidence interval 1.021-1.054]; p<0.0001). The 36-item short-form health survey (SF-36) mental and physical component scores were also predictive of an increased mortality risk (p<0.05). Age, forced expiratory volume in 1 s (FEV(1)), body mass index and smoking status were not significant predictors. Spline analysis of baseline variables revealed a linear association between SGRQ total score and mortality risk over 1 year (logarithmic scale). Other baseline variables, including FEV(1), showed different bimodal patterns in the spline analysis. There was no difference in mortality in the formoterol versus the non-formoterol treatment group while budesonide-containing treatment was associated with reduced 1-year, all-cause, in-study mortality compared with non-budesonide therapy.

Health status measured by SGRQ and SF-36 may be important for predicting COPD patients at increased mortality risk, with SGRQ total score emerging as the strongest predictor compared with other baseline covariates.