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01.12.2014 | Research | Ausgabe 1/2014 Open Access

Respiratory Research 1/2014

Derivation of normative data for the COPD assessment test (CAT)

Zeitschrift:
Respiratory Research > Ausgabe 1/2014
Autoren:
Lancelot M Pinto, Nisha Gupta, Wan Tan, Pei Z Li, Andrea Benedetti, Paul W Jones, Jean Bourbeau, For the CanCOLD study group
Wichtige Hinweise

Electronic supplementary material

The online version of this article (doi:10.​1186/​1465-9921-15-68) contains supplementary material, which is available to authorized users.

Competing interests

The authors declare that they have no competing interests.

Authors’ contributions

LP - planned and created the protocol, analyzed the data, wrote and reviewed the article. NG - reviewed the article WT - reviewed the article and critiqued the methodology PL - assessed the quality of the statistical analysis and reviewed the article AB - assessed the quality of the statistical analysis and reviewed the article PJ - reviewed the article and critiqued the methodology JB-planned and created the protocol, wrote and reviewed the article. All authors read and approved the final manuscript.

Abstract

Background

The tradition classification of the severity of COPD, based on spirometry, fails to encompass the heterogeneity of the disease. The COPD assessment test (CAT), a multi-dimensional, patient-filled questionnaire, assesses the overall health status of patients, and is recommended as part of the assessment of individuals with COPD. However, information regarding the range of values for the test in a non-COPD population (normative values) is limited, and consequently, knowledge regarding the optimal cut-off, and the minimum clinically important difference (MCID) for the test remain largely empirical.

Methods

CanCOLD is a population-based multi-center cohort study conducted across Canada, the methodology of which is based on the international BOLD initiative. The study includes subjects with COPD, at-risk individuals who smoke, and healthy control subjects. CAT questionnaires were administered at baseline to all subjects. Among non-COPD subjects, normative values for the CAT questionnaire, and psychometric properties of the test were characterized. Predictors of high CAT scores were identified using multivariable logistic regression.

Results

Of the 525 non-COPD subjects enrolled, 500 were included in the analysis. Mean FEV1/FVC ratio among the 500 included subjects was 0.77 (SD 0.49); the mean predicted FEV1 was 99.38% (SD 16.88%). The overall mean CAT score was 6 (SD 5.09); scores were higher among females (6.43, SD 5.59), and subjects over 80 years of age (mean 7.58, SD 6.82). Cronbach alpha for the CAT was 0.79, suggesting a high internal consistency for the test. A score of 16 was the 95th percentile for the population, and 27 subjects (5.4%) were found to have a CAT score > =16. Current smoking (aOR 3.41, 95% CI 1.05, 11.02), subject-reported physician-diagnosed asthma (aOR 7.59, 95% CI 2.71, 21.25) and musculoskeletal disease (aOR 4.09, 95% CI 1.72, 9.71) were found to be significantly associated with a score ≥16.

Conclusions

The characterization of CAT scores in the general population will be useful for norm-based comparisons. Longitudinal follow-up of these subjects will help in the optimization of cut-offs for the test.
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