OBJECTIVE: To develop and evaluate a set of questionnaire-based screening tools to identify risk for 1-year adverse outcomes in adults with moderate to severe asthma. STUDY DESIGN: Prospective cohort study in 16 managed care organizations in the United States. PATIENTS AND METHODS: Patients (n = 4888) with moderate-to-severe asthma completed baseline and 1-year questionnaires (response rate, 79%). Adverse outcomes included hospitalization in the past year; emergency department (ED) visit in the past year; days of lost activity in the past month; a composite measure combining hospitalization, ED use, and lost days; and severe symptoms. Risk models were constructed for each of these 5 outcomes. Candidate predictors included baseline demographic characteristics, prior asthma healthcare use, access to care, symptoms, and treatment. Outcome variables were dichotomized, and logistic regression analysis was used to estimate the probability of 1-year outcomes. RESULTS: The patients' mean age was 45 years; 69% were female, and 83% were white. At 1-year follow-up, 9% had been hospitalized in the past year, 35% had used the ED, and 36% had reduced activity in the past month; 54% reported at least 1 of these, and 53% reported severe symptoms. Twenty-one items were retained for the 5 final risk models. Overall, the strongest predictors were comorbid illnesses and prior ED use. Model discrimination using receiver operating characteristic area ranged from 0.67 to 0.78 for predicting hospitalization, ED use, lost days, any one of these outcomes, and symptoms. CONCLUSIONS: The questionnaire-based risk models identified with good discrimination asthmatics at increased risk for a range of adverse outcomes. Risk models based on patient-reported data could be used to target individuals for intervention.
OBJECTIVE: To develop and evaluate a set of questionnaire-based screening tools to identify risk for 1-year adverse outcomes in adults with moderate to severe asthma. STUDY DESIGN: Prospective cohort study in 16 managed care organizations in the United States. PATIENTS AND METHODS: Patients (n = 4888) with moderate-to-severe asthma completed baseline and 1-year questionnaires (response rate, 79%). Adverse outcomes included hospitalization in the past year; emergency department (ED) visit in the past year; days of lost activity in the past month; a composite measure combining hospitalization, ED use, and lost days; and severe symptoms. Risk models were constructed for each of these 5 outcomes. Candidate predictors included baseline demographic characteristics, prior asthma healthcare use, access to care, symptoms, and treatment. Outcome variables were dichotomized, and logistic regression analysis was used to estimate the probability of 1-year outcomes. RESULTS: The patients' mean age was 45 years; 69% were female, and 83% were white. At 1-year follow-up, 9% had been hospitalized in the past year, 35% had used the ED, and 36% had reduced activity in the past month; 54% reported at least 1 of these, and 53% reported severe symptoms. Twenty-one items were retained for the 5 final risk models. Overall, the strongest predictors were comorbid illnesses and prior ED use. Model discrimination using receiver operating characteristic area ranged from 0.67 to 0.78 for predicting hospitalization, ED use, lost days, any one of these outcomes, and symptoms. CONCLUSIONS: The questionnaire-based risk models identified with good discrimination asthmatics at increased risk for a range of adverse outcomes. Risk models based on patient-reported data could be used to target individuals for intervention.
Authors: Gene Colice; Alison Chisholm; Alexandra L Dima; Helen K Reddel; Annie Burden; Richard J Martin; Guy Brusselle; Todor A Popov; Julie von Ziegenweidt; David B Price Journal: Pragmat Obs Res Date: 2018-08-10