Design and Testing of tools to Identify individuals at high risk for COPD 73

描述（由申请人提供）：慢性阻塞性肺疾病是美国发病率的主要原因，也是第三大死亡原因

DESCRIPTION (provided by applicant): Chronic obstructive pulmonary disease is a leading cause of morbidity and the third leading cause of death in the U.S. It is characterized by variable clinical impact, manifestations, varying airflow limitation, frequency and severity of acute exacerbations (AECOPD). Despite its public health importance COPD is under-recognized and undertreated. Testing that might support the diagnosis of COPD is not routinely performed. Although spirometry is not recommended for detecting all people at risk for early COPD, screening those more likely to have disease resulting in adverse consequences will allow earlier treatment and potentially reduce morbidity and mortality. Numerous groups have developed questionnaires to enhance the appropriate application of diagnostic physiological testing, but none have been designed to identify previously undiagnosed patients at the highest risk for adverse health care consequences. We hypothesize that a simple screening methodology incorporating a simple questionnaire with a limited number of items and peak expiratory flow (PEF) measurement will identify subjects with clinically significant COPD. The purpose of this proposal is to develop a simple screening approach for use in primary care to identify subjects with 1) more than moderate airflow obstruction and/or 2) at risk for an AECOPD in whom additional evaluation, including spirometry, is indicated to diagnose COPD. We believe both risk groups can be identified through a stratified approach incorporating PEF and a limited item questionnaire. These goals will be accomplished by completing three Specific Aims: Aim 1 - Using statistical data mining methodology, identify and analyze candidate variables from multiple existing datasets that efficiently classify subjects with 1) more than moderate airflow obstruction and/or 2) at risk for an AECOPD in whom additional evaluation, including spirometry, is indicated to diagnose COPD. Aim 2 - Develop a self-reported questionnaire with multiple candidate items, with content and structure (content validity) based on quantitative predictive variables (Aim 1) and insight gained through qualitative data from high and low risk subjects. We will incorporate PEF in development of methodology to identify patients having clinically significant COPD. Aim 3 - Reduce the number of items and test the reliability, sensitivity and specificity of the final questionnaire which will then be ready for use in longitudinally followed primary care-based cohorts of patients to identify its effectiveness in primary care practices. We will independently and simultaneously analyze multiple candidate items and evaluate the marginal additional predictive power of PEF in identifying patients with clinically significant COPD. The proposed investigative team includes experts in psychometrics, respiratory disease, primary care and an innovative partnership with the COPD Foundation. We have access to large datasets which will provide important information regarding candidate items. The resulting, novel screening approach incorporating simple items and PEF measurement will enhance the ability to identify COPD patients who are most likely to benefit from available therapies.