Abstract
Introduction: The COPD Assessment Test (CAT) and the Clinical COPD Questionnaire (CCQ) are both clinically useful health status instruments. The main objective was to compare CAT and CCQ measurement instruments. Methods: CAT and CCQ forms were completed by 432 randomly selected primary and secondary care patients with a COPD diagnosis. Correlation and linear regression analyses of CAT and CCQ were performed. Standardised scores were created for the CAT and CCQ scores, and separate multiple linear regression analyses for CAT and CCQ examined associations with sex, age (≤ 60, 61–70 and >70 years), exacerbations (≥1 vs 0 in the previous year), body mass index (BMI), heart disease, anxiety/depression and lung function (subgroup with n = 246). Results: CAT and CCQ correlated well (r = 0.88, p < 0.0001), as did CAT ≥ 10 and CCQ ≥ 1 (r = 0.78, p < 0.0001). CCQ 1.0 corresponded to CAT 9.93 and CAT 10 to CCQ 1.29. Both instruments were associated with BMI < 20 (standardised adjusted regression coefficient (95%CI) for CAT 0.56 (0.18 to 0.93) and CCQ 0.56 (0.20 to 0.92)), exacerbations (CAT 0.77 (0.58 to 0.95) and CCQ 0.94 (0.76 to 1.12)), heart disease (CAT 0.38 (0.17 to 0.59) and CCQ 0.23 (0.03 to 0.43)), anxiety/depression (CAT 0.35 (0.15 to 0.56) and CCQ 0.41 (0.21 to 0.60)) and COPD stage (CAT 0.19 (0.05 to 0.34) and CCQ 0.22 (0.07 to 0.36)). Conclusions: CAT and CCQ correlate well with each other. Heart disease, anxiety/depression, underweight, exacerbations, and low lung function are associated with worse health status assessed by both instruments.
Introduction
Assessment of disease severity in chronic obstructive pulmonary disease (COPD) patients should include lung function, exacerbation frequency and health status (Citation1). An alternative to health status is the modified Medical Research Council (mMRC) dyspnoea scale, but using health status instruments, which include several symptoms and other items results in a more comprehensive assessment. The COPD Assessment Test (CAT) (Citation2) and the Clinical COPD Questionnaire (CCQ) (Citation3) are both short, validated instruments developed to measure health status. Both instruments correlate well with the Gold Standard Health Status Instrument in COPD; St Georges Respiratory Questionnaire (SGRQ) (Citation2, Citation3). According to the updated Global Initiative for Chronic Obstructive Lung Disease (GOLD) recommendations, CAT is the suggested option but CCQ is described as an equivalent alternative (Citation1). In the International Primary Care Respiratory Group (IPCRG) “User's Guide to COPD Wellness tools,” CCQ and CAT are both described as clinically suitable instruments (Citation4) with a slight preference for CCQ.
Some earlier studies have compared the two instruments. Tsiligianni et al studied COPD patients stage I-IV and found a statistically significant correlation (r = 0.64) between the instruments. Internal consistency was high in both CAT and CCQ, and both instruments demonstrated a high level of reproducibility (Citation5). Ringbaek et al. studied CAT and CCQ in pulmonary rehabilitation patients with severe COPD, and confirmed a statistically significant correlation of CAT with CCQ (r = 0.77). The average time for completing the form was 107 seconds for CAT and 134 seconds for CCQ, while the number of participants who required assistance to complete the form was 53.9% for CAT and 36.0% for CCQ (Citation6). Dodd et al. (Citation7) and Kon et al. (Citation8) have compared the response to pulmonary rehabilitation for CAT and CCQ, and both concluded that the effect size for change in scores was slightly higher for CCQ.
Age, exacerbations, lower level educational attainment and lung function are known to influence CAT (Citation9–Citation19) and CCQ (Citation14, Citation20–Citation23). In a study by Jones et al., a higher number of co-morbidities was significantly associated with higher CAT score (Citation10). Specifically, Miyazaki found that gastro-esophageal reflux disease, arrhythmia, depression, and anxiety were associated with CAT (Citation15). However, several studies failed to show associations of co-morbidity in terms of heart failure, ischemic heart disease, hypertension, obstructive sleep apnea syndrome, obesity/BMI and renal failure with higher CAT scores (Citation11, Citation15, Citation19). On the other hand, a previous study of the cohort in the present study showed significant associations of heart disease, depression, and underweight with low health status assessed by CCQ (Citation23). Thus, the question of how co-morbidity and body mass index (BMI) are associated with CAT is still understudied, and there are no direct comparisons of how factors other than response to pulmonary rehabilitation influence CAT and CCQ. It is of great interest to establish whether there actually is a difference in how co-morbidity, BMI and other variables are associated with these two instruments.
The main objective of the study was to compare the CAT and CCQ instruments in a multicentre population of clinical COPD patients from both primary and secondary care settings in Sweden. This was achieved by examining associations with the two instruments for sex, age, level of education, smoking status, BMI, lung function, exacerbation rate and co-morbidity. We also assessed differences in response rates for the two questionnaires, and described how their different scoring systems can be used to define stable health status. Finally, we examined the correlation between the two instruments.
Methods
Data collection
In 2005, the PRAXIS study cohort was created, with primary and secondary care COPD patients from seven county councils in central Sweden (Citation23–Citation29). Each county council was represented by the department of respiratory medicine in their central hospital, the department of internal medicine from one randomly selected district hospital and eight randomly selected primary health care centres (PHCCs), in total 14 hospitals and 56 PHCCs. A list of all patients aged 18–74 years with a COPD diagnosis (ICD-10 code J44) in the medical records during the period of 2000-2003 was compiled for every participating centre.
A random selection recruited 1548 patients, including 1084 in primary care and 464 in hospital clinics. Data were collected through patient questionnaires and record reviews, completed for totally 1111 COPD patients. The questionnaires were sent by mail to the patients, and returned in a prepaid envelope. They included several questions about patient characteristics, co-morbid conditions and current medication, and in addition, the Swedish version of CCQ. In 2012 a similar follow-up questionnaire was sent to the remaining 786 patients. At this time, Swedish versions of both CAT and CCQ were available and included in the questionnaire. Inside the questionnaire, the CCQ appeared first and the CAT immediately afterwards. A total number of 561 patients returned the questionnaire, and 432 of those had complete answers to all items in both the CAT and the CCQ forms (Figure ).
Figure 1. Data collection flow chart.
Patient characteristics
Information on age, sex, smoking status, level of education, number of exacerbations previous year, height, weight, hypertension, heart disease, cerebrovascular disease, diabetes or anxiety/depression was provided by the patient questionnaires. Exacerbations were defined as emergency visits last 12 months due to deterioration in the lung disease, stated in the questionnaires. Information on lung function was obtained from the review of records performed in 2005.
The COPD Assessment Test (CAT)
CAT includes eight items describing the presence or absence of cough, mucus production, chest tightness, effort dyspnoea, limitation of activities at home, sense of confidence about leaving the home, sleep and the feeling of having lots of energy. The symptoms are assessed on a six-point scale from 0 to 5. The main outcome measure is the total score, where 0 indicates the absence of any negative influence of disease and 40 the worst imaginable health status (Citation2).
The Clinical COPD Questionnaire (CCQ)
CCQ consists of 10 questions distributed in three domains: symptoms, mental state and functional state. Observed symptoms are dyspnoea, cough and phlegm; mental state includes questions about feeling depressed and concerns about breathing; and functional state describes limitations in different activities of daily life due to the lung disease. The questions are assessed by a 7-point scale from 0 to 6. There are two versions of the CCQ, one where the questions apply to the previous week and one to the previous 24 hours. This study used the version referring to the previous week. The main outcome measure of HRQL is the mean CCQ value (Citation3), with separate scores for each domain, and a higher value indicates lower health status.
Interpretation of CAT and CCQ scores
In assessment of COPD, a CAT value of < 10 or a CCQ value of <1 is suggested as stable health status (Citation1). The minimal clinical important difference (MCID) for CCQ is established to be 0.4 units (Citation8, Citation20). As for CAT, the MCID value has been debated but 2.0 units is suggested (Citation30).
Statistical analysis
The analyses were performed using SPSS version 22.0 (SPSS Inc, Chicago). Respond rates and frequency of fully completed CAT and CCQ forms were noted. Cross-tabulations and chi2 test were used to examine statistical differences between patients completing the CAT and CCQ forms. Total CAT scores, total mean CCQ scores and CCQ mean domain scores were calculated. Correlation analysis of CAT and CCQ was performed in the entire sample and stratified for the groups considered to have stable (CAT < 10 and CCQ < 1) or unstable (CAT ≥ 10 and CCQ ≥ 1) health status. In addition, correlation analysis of CAT and the three separate CCQ domains was performed. Correlations were classified as low (r < 0.45), moderate (r = 0.45 to 0.70) or high (r > 0.70) as defined by Cohen's proposal (Citation31). Linear regression was used to describe the association between mean CAT and CCQ. Data were also examined graphically using a LOESS curve, to explore the possibility of a nonlinear association. Total CAT and mean CCQ scores were used as dependent variables in linear regression. Age, sex, level of education, smoking habits, exacerbations, heart disease, diabetes, anxiety/depression, obesity, overweight and underweight were modelled as independent variables.
Age was categorised as ≤ 60, 61–70 and > 70 years. A dichotomous educational variable identified the most highly educated group as those who had continued in full-time education for at least two years beyond the Swedish compulsory school period of nine years. Smoking history was categorised into current smoking, ex-smoking, occasional smoking and never smoking. Obesity was defined as body mass index (BMI) ≥ 30, overweight as BMI < 30 and ≥ 25, and underweight as BMI below 20. The number of exacerbations in the preceding 12-month period was classified as 0 or ≥ 1. In patients where spirometry data were available (n = 246), their disease was graded based on forced expiratory volume in one second (FEV1) (Citation1) expressed as percentage of the European Community for Steel and Coal reference values (FEV1%pred) (Citation32).
Age, smoking habits and BMI were modelled as series of binary dummy variables. In multivariate analysis, sex, age and variables with statistically significant associations in the univariate analyses were included. Subsequently, separate analyses for CAT and CCQ examined associations with sex, age, exacerbations, BMI, heart disease, anxiety/depression and, in subgroup analyses, with lung function. Separate multiple linear regression analyses for CAT and respectively CCQ were performed in order to examine raw scores for comparison with associations in other studies. To allow comparison of magnitude of the associations for different factors with the scores in each instrument, standardised standard deviation unit scores were created for the CAT and CCQ scores. The multiple linear regression analyses were repeated using the standardised scores as dependent variables. Stratification and interaction analyses were used to investigate potential effect modification by sex. The interaction analyses adjusted for the main effects, using interaction terms for sex with each relevant variable and with further adjustment for the same factors as in the multiple regression analysis.
Results
Patient characteristics
Patient characteristics distributed by level of care are described in Table . CAT and CCQ mean scores were both statistically significantly higher indicating worse health status among secondary care patients, but otherwise no notable differences were found.
Table 1. Patient characteristics by level of care
Completion rates of the questionnaires
Of the originally 1111 patients with data from a patient questionnaire and record review in 2005, 786 patients received the follow-up questionnaire in 2012. The questionnaire was responded by 561 patients (response frequency 71.4%) (Figure ). In these 561 questionnaires, there were 560 CAT forms and 545 CCQ forms where at least one item was completed, but only 528 CAT and 450 CCQ forms with all items completed (Figure ). Thus, the frequency of completely fulfilled CAT forms of the returned questionnaires was 94% for CAT and 82% for CCQ (p < 0.0001). Further analysis of all returned forms, to see if there were differences in proportion of completed items and item-specific missingness between the two instruments, showed that 13 patients did not write anything at all in the CAT form, although otherwise the number of competed items were evenly distributed between 1 and 8. In the CCQ form, all patients completed at least one of the items. Item nr 1 (dyspnoea at rest) and item nr 7 (functional limitations in effort situations) were completed in a lower frequency than the remaining questions (data not shown).
Correlation and regression analyses of CAT and CCQ
CAT and CCQ showed a high magnitude correlation (r =0.88, p < 0.0001), as did CAT ≥ 10 and CCQ ≥1 (n = 308, r = 0.78, p < 0.0001). CAT <10 and CCQ <1 (n = 80) correlated moderately, (r = 0.55, p < 0.0001). Only 31 patients had CAT score <10 and CCQ ≥ 1, and 13 patients had CAT score ≥ 10 and CCQ < 1. For the CCQ domains, CAT showed a high magnitude correlation with the CCQ symptoms domain (r = 0.83, p < 0.0001 and the functional domain (r = 0.81, p < 0.0001), and a moderate correlation with the mental domain (r = 0.67, p < 0.0001). The association between the two instruments is shown in Figure . CCQ 1.0 corresponded to CAT 9.93 and CAT 10.0 to CCQ 1.29. LOESS plots indicated that there was no notable deviation from a linear association (data not shown).
Figure 2. Correlation between CAT and CCQ scores. The regression equation describes the linear association between CAT total score and CCQ total mean score.
In univariate analyses; low level of education, one or more exacerbations compared with no exacerbations, BMI < 20 compared with normal weight, and presence of heart disease and anxiety/depression were statistically significantly associated with lower health status measured by both CAT and CCQ, respectively (Table ). In multivariate analyses; exacerbations, BMI < 20, heart disease and anxiety/depression were associated with both higher CAT and CCQ scores, and higher level of education with lower CCQ (Table ).
Table 2. Factors influencing health status assessed by CAT and CCQ
Both instruments also showed a statistically significant low magnitude correlation with FEV1%pred (CAT: r = -0.28, p < 0.0001; CCQ: r = -0.32, p < 0.0001). After further adjustment with FEV1%pred in the subgroup with available lung function data (n = 246), lower health status assessed by both instruments were associated with exacerbations (adjusted regression coefficient (95%CI) CAT 6.96 (4.76 to 9.16), CCQ 1.27 (0.93 to 1.60); heart disease (CAT 4.30 (1.97 to 6.64), CCQ 0.48 (0.13 to 0.83)) and anxiety/depression (CAT 3.87 (1.56 to 6.19), CCQ 0.59 (0.24 to 0.94)), while BMI <20 was not statistically significantly associated with either of the instruments.
Comparison of CAT and CCQ
The results of multiple linear regression with standardised scores are presented in Table and in Figure . Statistically significant associations for heart disease, anxiety/depression, underweight and exacerbations with health status were found for both CAT and CCQ.
Table 3. Comparison of factors influencing CAT and CCQ
Figure 3. Comparison CAT and CCQ. Adjusted regression coefficients (95%CI) for variables associated with health status in multiple linear regression with standardised CAT and CCQ scores.
In female patients, the main multiple regression analysis with standardised scores showed that both instruments were associated with BMI < 20, and exacerbations (Table ). In male patients, BMI ≥ 25 and < 30 was associated with better health status, while exacerbations were associated with worse health status (Table ). Interaction analyses with adjustment for main effects showed significant effect modification by sex for underweight with CCQ, for exacerbations with CCQ and for overweight with CAT (Table ).
Table 4. Stratification and interaction analyses by sex
Discussion
The primary finding of this multi-centre study of COPD patients from both primary and secondary care is that heart disease, anxiety/depression, underweight and exacerbations are independently associated with worse health status using both CAT and CCQ. In addition, overweight was associated with better health status in male patients as measured by both instruments. The results confirm the findings from previous studies (Citation9–Citation18, Citation20–Citation23), but adds the important information that heart disease and BMI influence CAT scores. To our knowledge, this has not been documented before. Previous studies have shown that all the described factors influence health status measured by SGRQ (Citation33–41), but we demonstrate that the much shorter instruments, CAT and CCQ, also identify these associations. The identification of co-morbid conditions influencing health status in COPD can help us focus on factors of importance in clinical management of COPD patients. The fact that we demonstrate that CAT and CCQ can identify these associations is of clinical interest, as these shorter instruments are much suitable for routine clinical practice.
The second important finding is that, when comparing CAT and CCQ, the factors associated with health status were the same for both instruments. We find it interesting that both the main analysis and the stratified analyses showed that CAT score seem to be more influenced by heart disease while CCQ score was more influenced by exacerbations and anxiety/depression. The more notable association for anxiety/depression with CCQ may be due to the fact that this instrument has a specific mental state domain. The finding is consistent with a previous study where depression and anxiety also were reported to be associated with health status as measured by CCQ (Citation42) and with a meta-analysis where CCQ had the most notable correlations with the Hospital Anxiety and Depression Scale (HADS) compared with a number of other health status instruments although not including CAT (Citation5). However, the associations were generally very similar. Both CAT and CCQ have been suggested as clinically useful tools (Citation43), although the preference has differed between guidelines (Citation1, Citation4). In our opinion, the results of our study show that the instruments seem largely to be of equal value.
A somewhat surprising finding was that a considerably higher proportion of the population managed to complete CAT compared with CCQ. Previous studies have suggested that completing CAT takes slightly shorter time (Citation6), but that CCQ is preferred by slight majority of patients (Citation5) and less frequently requires assistance for completion (Citation6). In our patient questionnaire CCQ was included before CAT, so the difference should not be explained by stopping after the first instrument. However, that could be the reason to why 13 patients did not even start with the CAT form. We speculate that the higher CAT respond frequency is due to a lower number of items and to a nice and clear layout that increases the feasibility.
The statistically significant correlation between CAT and CCQ confirms the findings in several other studies (Citation5–Citation8, Citation14). The correlation was of somewhat higher magnitude in our material (r = 0.88) than in previous studies, where the correlation coefficient varied from 0.54 to 0.78. We extended the correlation analyses to stratification for stable and unstable disease, and the fact that the association between CAT and CCQ exists in both groups, is broadly consistent with an overall linear association as shown in the graph in Figure . CAT correlated significantly with all three CCQ domains, but not surprisingly the correlation was more pronounced for the CCQ domains symptoms and functional state. The most significant difference between CAT and CCQ is that CCQ includes three domains, and the mental state domain has no obvious corresponding questions in the CAT instrument. The fact that CAT and CCQ correlate well is consistent with the fact that only 10% of the evaluated patients had low CAT and high CCQ or the reverse.
In the GOLD recommendations, stable disease is regarded as CAT < 10 or CCQ < 1.0 (Citation1). In our study, CAT 10 was equivalent to CCQ 1.29, but we agree that using the arbitrary levels is more convenient. In our opinion, our result is approximately clinically equivalent to both the present GOLD statement of CAT 10 corresponding to CCQ 1.0 (Citation1), and that CAT 10 is equivalent to CCQ 1.5, as suggested in a recent research letter (Citation44). Both CAT and CCQ were statistically significantly but rather weakly associated with lung function. This supports the GOLD recommendations that assessment of health status and exacerbation rate should be performed as a complement to spirometry.
Strengths and limitations
A major strength of this study is that the population is sampled from several primary and secondary care centres. We believe that the randomised recruitment and the fact that the study population is based on patients with a doctor’s diagnosis of COPD (identifying an unselected clinical population), ensure both a high internal and external validity. Another important quality of the study is that we have compared two instruments in a standardised manner.
A limitation could be that spirometry data were obtained in 2005, and missing in many of the patients. However, the sub group analysis on those with lung function data and with further adjustment for lung function did not change the main results considerably. The only differences from the main analysis was that the CAT score was no longer statistically significantly associated with level of education and that the association between underweight and health status was slightly attenuated and lost statistical significance for both CAT and CCQ. Repeating the main multiple linear regression analysis in the subgroup of 246 patients with and without further adjustment for lung function gave similar results. Thus, the attenuation of the association of BMI with CAT and CCQ could be explained only by loss of power and not by confounding by lung function.
Another possible limitation is that height, weight and co-morbid disease were self-reported. This method could lead to systematic misreporting thus introducing bias. In a previous COPD study with self-reported height and weight, BMI was associated with SGRQ. Hence, it is reasonable to believe that underweight is truly associated with health status in COPD patients. The associations of heart disease and depression with CAT and CCQ are consistent with the examination in 2005 of record-based co-morbid diagnoses and CCQ in the same cohort. Therefore, we believe that the fact that the diseases were self-reported in the present study should not have influenced the results substantially, as the findings are consistent with similar analysis using medical records.
Finally, the fact that the health status instruments had a fixed order in all the patient questionnaires could potentially influence accuracy of the results. However, since the CAT was completed by a higher proportion of patients, even though it came after the CCQ in the questionnaire, we speculate that the fixed order should not have influenced the results substantially.
Conclusions
CAT and CCQ correlate well with each other. Heart disease, anxiety/depression, underweight, exacerbations and lung function are similarly associated with worse health status assessed by both CAT and CCQ. We suggest that, for an overall assessment of health status in COPD, they can largely be used interchangeably, although CCQ may be more difficult to complete.
Ethics
The study was approved by the Regional Ethical Review Board of Uppsala (Dnr 2010/090). Written consent was obtained for all participating patients.
Declaration of Interest Statement
The authors have no financial or other conflicts of interest related to the material of the present study. The authors alone are responsible for the content and writing of the paper.
Acknowledgments
Thanks to Ulrike Spetz-Nyström and Eva Manell for reviewing the patient records, and to all participating centres.
Funding
The PRAXIS study group has received grants from the county councils of the Uppsala-Örebro Health Care region, the Swedish Heart and Lung Association, the Swedish Asthma and Allergy Association and the Bror Hjerpstedt Foundation, Uppsala.
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