Using biological indicators of inflammation, in addition to established predictors of COPD mortality, may improve COPD mortality prediction. Improving the mortality prediction will give the patient a more accurate time line of survival, which is important for treatment purposes and for the quality of life for the COPD sufferer.
"Ask your doctor about risk factors associated with COPD."
The study was led by Bartolome Celli, M.D., from the Harvard Medical School and member of the Pulmonary and Critical Care Division of Brigham and Women's Hospital in Boston. Researchers examined data from 1,843 COPD sufferers who were a part of Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints (ECLIPSE) study. Inflammation is common in COPD, and adding this symptom to a predictive model to determine COPD mortality significantly improved predictions.
The ECLIPSE study was funded by GlaxoSmithKline, and was a three year study to examine the ways COPD develops in humans. This included mechanisms for COPD development and identifying risk factors related to disease progression.
COPD mortality predictions are based on age, hospitalizations due to COPD within the calendar year, and the BODE (Body-Mass Index, Airflow Obstruction, Dyspnea, and Exercise Capacity) index. Measuring the level of interleukin-6 (IL-6), a protein linked to the body's inflammatory response, significantly improved the COPD mortality prediction. Researchers further improved the predictive accuracy by adding white blood cell counts and other indicators of inflammation such as C-reactive protein (CRP), interleukin-8 (IL-8), fibrinogen, chemokine (C-C-motif) ligand 18 (CCL-18), and surfactant protein D (SP-D) to the model.
Of the 1,843 COPD patients that were a part of the ECLIPSE study, 168 had died within three years. IL-6 along with white blood cells and the other inflammatory indicators were significantly higher in the COPD patients that had died. After adjusting for other factors related to COPD mortality prediction, IL-6 and the other indicators were also associated with COPD mortality.
Some limitations of the study included the inability to specify the cause of death within the 168 COPD patients. Certain biological indicators that researchers believe are important to how COPD develops were not included in this predictive model and their addition could further improve the model's accuracy. Future studies can also include an additional group of COPD patients to validate the accuracy of this proposed predictive model.
Having an accurate model to predict COPD mortality can affect what treatments are needed for the patient. Improved accuracy will also let COPD patients better understand the disease and its progression.
No funding information was provided.
This study was published in the March edition of the American Journal of Respiratory and Critical Care Medicine.