BACKGROUND: Because no validated "gold standard" for measuring asthma outcomes exists, asthma interventions are often evaluated using a large number of disease status measures. Some of these measures may be redundant, whereas others may be complementary. Use of multiple outcomes may lead to ambiguous results, increased type I error rates, and be an inefficient use of resources including caregiver and patient/participant time and effort. Understanding the relationship between these measures may facilitate more parsimonious and valid evaluation strategies without loss of information. OBJECTIVE: To assess the relationships between multiple measures of asthma disease status over time. DESIGN/ METHODS: We used data from a randomized, controlled trial of a comprehensive disease management program involving 119 disadvantaged inner-city children aged 5 to 12 years with moderate to severe asthma. Spearman correlations were calculated between the following asthma disease status measures: parent-reported disease symptoms, parent-reported health care utilization, functional health status using the American Academy of Pediatrics' validated Child Health Survey for Asthma (CHSA), diary data (symptom scores, night wakings, and bronchodilator use), and pulmonary function tests at baseline, 32 weeks, 52 weeks, and changes from baseline to 52 weeks. RESULTS: Ninety-four (79%) of randomized patients participated at baseline and 52 weeks. Completion rates for outcome measures ranged from 79% (CHSA, spirometry data) to 64% (diary data). At baseline, asthma symptoms, health care utilization, and individual domains from the CHSA were significantly correlated (r = 0.21-0.53). These correlations were stable over the 52-week follow-up. Forced expiratory volume in 1 second and diary data did not correlate to any other measures at baseline, and these measures correlated only inconsistently with other measures at 32 weeks and 52 weeks. Baseline to 52-week changes in asthma symptoms, utilization, and the CHSA domains were significantly correlated (0.22-0.56), as were baseline to 52-week changes in symptom days, night wakings, and the CHSA domains (r = 0.24-0.64). Baseline to 52-week changes in forced expiratory volume in 1 second and diary data did not correlate with other measures. CONCLUSIONS: These results suggest that asthma status and change in asthma status over time after introduction of a disease management intervention are best characterized by parent-reported symptoms, parent-reported utilization, and functional health status measures. Asthma diaries and pulmonary function tests did not seem to provide additional benefit, although they may play an important role in individual patient management. Our findings suggest a parsimonious evaluation strategy would include collection of key data elements regarding symptoms, utilization, and functional health status only, without loss of vital response information.
RCT Entities:
BACKGROUND: Because no validated "gold standard" for measuring asthma outcomes exists, asthma interventions are often evaluated using a large number of disease status measures. Some of these measures may be redundant, whereas others may be complementary. Use of multiple outcomes may lead to ambiguous results, increased type I error rates, and be an inefficient use of resources including caregiver and patient/participant time and effort. Understanding the relationship between these measures may facilitate more parsimonious and valid evaluation strategies without loss of information. OBJECTIVE: To assess the relationships between multiple measures of asthma disease status over time. DESIGN/ METHODS: We used data from a randomized, controlled trial of a comprehensive disease management program involving 119 disadvantaged inner-city children aged 5 to 12 years with moderate to severe asthma. Spearman correlations were calculated between the following asthma disease status measures: parent-reported disease symptoms, parent-reported health care utilization, functional health status using the American Academy of Pediatrics' validated Child Health Survey for Asthma (CHSA), diary data (symptom scores, night wakings, and bronchodilator use), and pulmonary function tests at baseline, 32 weeks, 52 weeks, and changes from baseline to 52 weeks. RESULTS: Ninety-four (79%) of randomized patients participated at baseline and 52 weeks. Completion rates for outcome measures ranged from 79% (CHSA, spirometry data) to 64% (diary data). At baseline, asthma symptoms, health care utilization, and individual domains from the CHSA were significantly correlated (r = 0.21-0.53). These correlations were stable over the 52-week follow-up. Forced expiratory volume in 1 second and diary data did not correlate to any other measures at baseline, and these measures correlated only inconsistently with other measures at 32 weeks and 52 weeks. Baseline to 52-week changes in asthma symptoms, utilization, and the CHSA domains were significantly correlated (0.22-0.56), as were baseline to 52-week changes in symptom days, night wakings, and the CHSA domains (r = 0.24-0.64). Baseline to 52-week changes in forced expiratory volume in 1 second and diary data did not correlate with other measures. CONCLUSIONS: These results suggest that asthma status and change in asthma status over time after introduction of a disease management intervention are best characterized by parent-reported symptoms, parent-reported utilization, and functional health status measures. Asthma diaries and pulmonary function tests did not seem to provide additional benefit, although they may play an important role in individual patient management. Our findings suggest a parsimonious evaluation strategy would include collection of key data elements regarding symptoms, utilization, and functional health status only, without loss of vital response information.
Authors: Anne M Fitzpatrick; W Gerald Teague; Deborah A Meyers; Stephen P Peters; Xingnan Li; Huashi Li; Sally E Wenzel; Shean Aujla; Mario Castro; Leonard B Bacharier; Benjamin M Gaston; Eugene R Bleecker; Wendy C Moore Journal: J Allergy Clin Immunol Date: 2010-12-31 Impact factor: 10.793
Authors: Sande O Okelo; Michelle N Eakin; Cecilia M Patino; Alvin P Teodoro; Andrew L Bilderback; Darcy A Thompson; Antonio Loiaza-Martinez; Cynthia S Rand; Shannon Thyne; Gregory B Diette; Kristin A Riekert Journal: J Allergy Clin Immunol Date: 2013-02-21 Impact factor: 10.793
Authors: Jerry A Krishnan; Robert F Lemanske; Glorisa J Canino; Kurtis S Elward; Meyer Kattan; Elizabeth C Matsui; Herman Mitchell; E Rand Sutherland; Michael Minnicozzi Journal: J Allergy Clin Immunol Date: 2012-03 Impact factor: 10.793
Authors: Sandra R Wilson; Cynthia S Rand; Michael D Cabana; Michael B Foggs; Jill S Halterman; Lynn Olson; William M Vollmer; Rosalind J Wright; Virginia Taggart Journal: J Allergy Clin Immunol Date: 2012-03 Impact factor: 10.793
Authors: Jonathan M Feldman; Alexander N Ortega; Daphne Koinis-Mitchell; Alice A Kuo; Glorisa Canino Journal: J Nerv Ment Dis Date: 2010-04 Impact factor: 2.254
Authors: Jonathan M Feldman; Elizabeth L McQuaid; Robert B Klein; Sheryl J Kopel; Jack H Nassau; Daphne Koinis Mitchell; Marianne Z Wamboldt; Gregory K Fritz Journal: Pediatr Pulmonol Date: 2007-04
Authors: Kimberly Yolton; Yingying Xu; Jane Khoury; Paul Succop; Bruce Lanphear; Dean W Beebe; Judith Owens Journal: Pediatrics Date: 2010-01-18 Impact factor: 7.124
Authors: Elizabeth W Holt; Earl Francis Cook; Ronina A Covar; Joseph Spahn; Anne L Fuhlbrigge Journal: J Allergy Clin Immunol Date: 2008-05 Impact factor: 10.793