Jamuna K Krishnan1, Kayley M Ancy2, Clara Oromendia3, Katherine L Hoffman3, Imaani Easthausen3, Nancy K Leidy4, MeiLan K Han5, Russell P Bowler6, Stephanie A Christenson7, David J Couper8, Gerard J Criner9, Jeffrey L Curtis5,10, Mark T Dransfield11, Nadia N Hansel12, Anand S Iyer11, Robert Paine Iii13, Stephen P Peters14, Jadwiga A Wedzicha15, Prescott G Woodruff7, Karla V Ballman3, Fernando J Martinez1. 1. Pulmonary and Critical Care Medicine, Weill Cornell Medicine, New York, New York, United States. 2. Department of Medicine, Weill Cornell Medicine, New York, New York, United States. 3. Division of Biostatistics, Department of Population Health Sciences, Weill Cornell Medical College, New York, New York, United States. 4. Evidera, Bethesda, Maryland, United States. 5. Internal Medicine, University of Michigan Health System, Ann Arbor, Michigan, United States. 6. Department of Medicine, National Jewish Medical and Research Center, Denver, Colorado, United States. 7. Pulmonary and Critical Care, University of California San Francisco, San Francisco, California, United States. 8. University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States. 9. Pulmonary and Critical Care Medicine, Temple University Hospital, Philadelphia, Pennsylvania, United States. 10. Medical Service, VA Ann Arbor Healthcare System, Ann Arbor, Michigan, United States. 11. Pulmonary, Allergy and Critical Care, University of Alabama at Birmingham, , Birmingham, Alabama, United States. 12. Division of Pulmonary and Critical Care Medicine, Johns Hopkins University, Baltimore Maryland, United States. 13. Division of Pulmonary and Critical Care Medicine, Department of Veterans Affairs Medical Center, University of Utah, Salt Lake City, Utah, United States. 14. Section on Pulmonary, Critical Care, Allergy and Immunological Diseases, Wake Forest School of Medicine Medical Center, Winston-Salem, North Carolina, United States. 15. National Heart and Lung Institute, Imperial College London, United Kingdom.
Abstract
Rationale: It has been suggested that patients with chronic obstructive pulmonary disease (COPD) experience considerable daily respiratory symptom fluctuation. A standardized measure is needed to quantify and understand the implications of day-to-day symptom variability. Objectives: To compare standard deviation with other statistical measures of symptom variability and identify characteristics of individuals with higher symptom variability. Methods: Individuals in the SubPopulations and InteRmediate Outcome Measures In COPD Study (SPIROMICS) Exacerbations sub-study completed an Evaluating Respiratory Symptoms in COPD (E-RS) daily questionnaire. We calculated within-subject standard deviation (WS-SD) for each patient at week 0 and correlated this with measurements obtained 4 weeks later using Pearson's r and Bland Altman plots. Median WS-SD value dichotomized participants into higher versus lower variability groups. Association between WS-SD and exacerbation risk during 4 follow-up weeks was explored. Measurements and Main Results: Diary completion rates were sufficient in 140 (68%) of 205 sub-study participants. Reproducibility (r) of the WS-SD metric from baseline to week 4 was 0.32. Higher variability participants had higher St George's Respiratory Questionnaire (SGRQ) scores (47.3 ± 20.3 versus 39.6 ± 21.5, p=.04) than lower variability participants. Exploratory analyses found no relationship between symptom variability and health care resource utilization-defined exacerbations. Conclusions: WS-SD of the E-RS can be used as a measure of symptom variability in studies of patients with COPD. Patients with higher variability have worse health-related quality of life. WS-SD should be further validated as a measure to understand the implications of symptom variability. JCOPDF
Rationale: It has been suggested that patients with chronic obstructive pulmonary disease (COPD) experience considerable daily respiratory symptom fluctuation. A standardized measure is needed to quantify and understand the implications of day-to-day symptom variability. Objectives: To compare standard deviation with other statistical measures of symptom variability and identify characteristics of individuals with higher symptom variability. Methods: Individuals in the SubPopulations and InteRmediate Outcome Measures In COPD Study (SPIROMICS) Exacerbations sub-study completed an Evaluating Respiratory Symptoms in COPD (E-RS) daily questionnaire. We calculated within-subject standard deviation (WS-SD) for each patient at week 0 and correlated this with measurements obtained 4 weeks later using Pearson's r and Bland Altman plots. Median WS-SD value dichotomized participants into higher versus lower variability groups. Association between WS-SD and exacerbation risk during 4 follow-up weeks was explored. Measurements and Main Results: Diary completion rates were sufficient in 140 (68%) of 205 sub-study participants. Reproducibility (r) of the WS-SD metric from baseline to week 4 was 0.32. Higher variability participants had higher St George's Respiratory Questionnaire (SGRQ) scores (47.3 ± 20.3 versus 39.6 ± 21.5, p=.04) than lower variability participants. Exploratory analyses found no relationship between symptom variability and health care resource utilization-defined exacerbations. Conclusions: WS-SD of the E-RS can be used as a measure of symptom variability in studies of patients with COPD. Patients with higher variability have worse health-related quality of life. WS-SD should be further validated as a measure to understand the implications of symptom variability. JCOPDF
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