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(Chest. 2006;129:1516-1522.)
© 2006 American College of Chest Physicians

Use of Peak Oxygen Consumption in Predicting Physical Function and Quality of Life in COPD Patients*

Michael J. Berry, PhD; Norman E. Adair, MD and W. Jack Rejeski, PhD

* From the Department of Health and Exercise Science, and Section on Pulmonary and Critical Care Medicine, Department of Medicine, Wake Forest University, Winston-Salem, NC.

Correspondence to: Michael J. Berry, PhD, Department of Health and Exercise Science, PO Box 7868, Wake Forest University, Winston-Salem, NC 27109-7868; e-mail: berry{at}wfu.edu

Abstract

Objective: To determine whether peak oxygen consumption (VO2peak) adds to the power of FEV1 in predicting physical function and quality of life in COPD patients.

Design: Single-center cross-sectional study.

Methods: Subjects included 291 COPD patients who completed pulmonary function testing, a graded exercise test, a 6-min walk, and stair climb test to assess physical function; a questionnaire assessing self-reported physical function; and a disease-specific, health-related quality-of-life questionnaire. Hierarchical multiple regression analysis was used to determine the contribution of VO2peak in predicting physical function and quality of life after accounting for FEV1.

Results: After accounting for FEV1, VO2peak added significantly to the prediction of 6-min walk distance (R2 increased by 0.395 [p < 0.005]); stair climb time (R2 increased by 0.262 [p < 0.005]); self-reported function (R2 increased by 0.109 [p < 0.005]); and health-related quality-of-life domain of mastery (R2 increased by 0.044 [p < 0.005]). Only VO2peak was found to significantly predict the health-related quality-of-life domain of fatigue (R2 = 0.094 [p < 0.005]).

Conclusion: After controlling for FEV1, VO2peak adds significantly to the prediction of physical function and health-related quality-of-life domain of mastery in COPD patients. These results provide additional support for the use of VO2peak in the multidimensional assessment of COPD patients.

Key Words: exercise tests • peak oxygen consumption • pulmonary function tests • quality of life

The staging and classification of COPD relies on FEV1. Using this measure as a surrogate for the disease status provides an estimate of impairment (the loss of lung function); however, controversy exists over whether or not FEV1 provides useful information on the level of physical functioning and/or health-related quality of life. The staging criteria proposed by both the American Thoracic Society (ATS) and the Global Initiative for Chronic Obstructive Lung Disease (GOLD) workshop suggest that the level of lung impairment is associated with physical function and quality of life.12 There is, however, only modest evidence supporting the notion that the FEV1 can accurately predict physical function34567 or quality of life5789 and, as such, its use to stage COPD patients has been criticized.1011 The inability of FEV1 to predict physical function or quality of life is not surprising. The FEV1 only evaluates the degree of lung impairment and not derangements of other bodily systems that could affect physical function and quality of life. Since many COPD patients present with additional diseases (comorbidities)12 and the presence of comorbidities has been shown to be associated with decreased physical function and a reduced quality of life,131415 a more comprehensive measure of physiologic impairment is needed.

Both the ATS and American College of Chest Physicians have recommended the use of exercise testing and the determination of peak oxygen consumption (VO2peak) to stage patients with COPD, since it provides a global assessment of the integrative responses of a number of physiologic systems that cannot be adequately evaluated by measuring the function of a single organ system.16 There are, however, few reports showing VO2peak to be predictive of physical function or quality of life in COPD patients,917 and there are no reports examining whether VO2peak can add to the power of FEV1 in predicting physical function or quality of life. Therefore, the primary aim of this investigation was to determine whether VO2peak could add to the power of FEV1 in predicting physical function and quality of life in COPD patients.

Materials and Methods

Patients
This study included 291 patients with COPD. Inclusion into the study was based on pulmonary function tests showing an expiratory airflow limitation such that the FEV1/FVC was ≤ 70% and the FEV1 was ≥ 20% of predicted. Recruitment of patients for this investigation occurred between January 1996 and May 2005. Patients were recruited via community-based advertising in the local media and physician referral. No financial remuneration was offered to patients for their participation, and all patients were informed they had the option to drop out of the study at any time with no adverse effects on their treatment. Patients had to report difficulty in performing at least one of the following activities due to dyspnea: walking a city block, grocery shopping, doing household chores, lifting objects chest height or higher, walking up stairs, and getting out of a chair. Patients had to be free of severe cardiovascular or peripheral vascular disease, not undergoing active treatment for cancer, and free from uncontrolled hypertension or diabetes.

Protocol
Patients for this study completed testing over 3 days. During the first day, all participants read and signed an informed consent approved by the university Institutional Review Board and then completed pulmonary function tests. Patients eligible to participate in the study based on results of the pulmonary function tests then completed a disease-specific, health-related quality-of-life questionnaire. During the second visit, the patients completed a graded exercise test on a motor-driven treadmill for the determination of VO2peak. During the third visit, patients completed a set of physical function tests and a questionnaire assessing self-reported physical function.

Pulmonary Function Tests
Pulmonary function tests and lung volume determinations were performed according to ATS guidelines using a plethysmograph (model 1085D; Medical Graphics Corporation; St. Paul, MN).1819

Health-Related Quality of Life
Health-related quality of life was assessed using the 20-item Chronic Respiratory Disease Questionnaire (CRQ) designed to evaluate the dimensions of dyspnea, fatigue, emotional function, and mastery (the patient’s feeling of control over the disease).20

VO2peak
VO2peak was determined during a graded exercise test performed the morning prior to the use of any bronchodilators. Each patient performed a modified Naughton protocol on a treadmill (Q-4000; Quinton Cardiology Systems; Bothell, WA) in which the grade and/or belt speed was increased by a specified amount at 2-minute stages.21 Exercise termination criteria were as follows: (1) participants requested to stop due to dyspnea, leg fatigue, chest pain, and/or dizziness; (2) ECG abnormalities (ST-segment changes, frequent ectopic beats); (3) excessive rise in BP; (4) desaturation to 88% or lower via pulse oximetry. Oxygen consumption was measured using a metabolic cart (CPX-D; Medical Graphics Corporation). All values were collected during a 60-s period and reported as minute values. The highest oxygen consumption value measured for a complete 60-s period represented the VO2peak. Calibration of the system occurred prior to every test according to manufacturer specifications. All calibration gases were certified standard gases verified via Haldane analysis.

Physical Function
Self-reported physical function was determined using the Fitness Arthritis and Seniors Trial2223 functional performance inventory. This 23-item instrument assesses difficulty in performing activities of daily living by asking patients to subjectively rate on a 1 (usually did with no difficulty) to 5 (unable to do) scale how much difficulty they have had in the past month performing specific tasks. Based on the current sample, the 23 items had a Cronbach {alpha} of 0.92. Additionally, function was determined by having patients perform two physical performance tests, a 6-min walk and a timed stair climb. The 6-min walk test was administered in a dedicated gymnasium (70 feet by 88 feet) according to ATS standards.24 The stair climb task consisted of a timed ascent up two flights of steps, with 10 steps in each flight. The rise and run of each step were 7.5 inches and 11.5 inches, respectively. Patients were allowed to use the handrail while ascending the steps and were instructed to climb the steps as quickly as possible. Once the patient began the stair climb, no verbal encouragement or feedback was given.

Data Analysis
The relationships between VO2peak and FEV1 percentage of predicted and measures of physical function and health-related quality of life were analyzed using Pearson product-moment correlations. Hierarchical multiple regression analyses were used to determine the contribution of FEV1 and VO2peak in predicting the various measures of physical function and health-related quality of life. The FEV1 was first entered in the model followed by VO2peak to determine the following: (1) if FEV1 was a significant predictor, and (2) whether VO2peak would add significantly to the model once FEV1 had been forced into the model. Significance was set at a p value < 0.05 for all analyses. Because of the number of related statistical tests, Bonferroni corrections were applied to the results from the correlation analyses and the regression analyses. More specifically, since there were a total of 14 correlations reported, significance for the correlations was set at p < 0.0035 (0.05/14). Results from the correlational analysis revealed that five of the dependent variables were correlated with FEV1 and VO2peak. Since two models, FEV1 alone and FEV1 and VO2peak, were tested for each of the five variables found to be correlated, the Bonferroni correction resulted in a p value of 0.005 (0.05/[5 x 2]) needed for significance in those analyses.

Results

Descriptive characteristics for the 291 patients enrolled in this study are shown in Table 1 . Of these, 26 patients (8.9%) were staged as mildly impaired, 149 patients (51.2%) were staged as moderately impaired, 100 patients (34.4%) were staged as severely impaired, and 16 patients (5.5%) were staged as very severely impaired according to GOLD criteria.2


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  		Table 1. Patient Characteristics*

 
Pearson product-moment correlations among the FEV1, VO2peak, 6-min walk distance, stair climb time, self-reported disability, and the various domains of health-related quality of life are shown in Table 2 . The correlations between FEV1 and the measures of physical function and the correlations between VO2peak and the measures of physical function were all statistically significant (p < 0.0035).The correlation between FEV1 and the CRQ domain mastery was significant (p < 0.0035), whereas the correlations between FEV1 and the CRQ domains dyspnea, emotion, and fatigue were not. The correlation between VO2peak and the CRQ domains of mastery and fatigue were significant (p < 0.0035), whereas the correlations between VO2peak and the CRQ domains dyspnea and emotion were not.


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  		Table 2. Correlation Coefficients Among Dependent and Independent Variables

 
Since both FEV1 and VO2peak were significantly correlated with 6-min walk distance, stair climb time, self-reported physical function, and the CRQ domain mastery, regression analyses were performed with these variables. Results of the regression analyses are shown in Tables 34567 . FEV1 was found to be a significant predictor of 6-min walk distance, stair climb time, self-reported function, and mastery. Additionally, VO2peak added significantly to the prediction of these variables after taking into account the effect of FEV1. More specifically, after accounting for FEV1, VO2peak added significantly to the prediction of 6-min walk distance (R2 increased by 0.395 [p < 0.005]); stair climb time (R2 increased by 0.262 [p < 0.005]); self-reported function (R2 increased by 0.109 [p < 0.005]); and health-related quality-of-life domain of mastery (R2 increased by 0.044 [p < 0.005]). Only VO2 peak was found to significantly predict the health-related quality-of-life domain of fatigue (R2 = 0.094 [p < 0.005]).


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  		Table 3. Regression Analysis Results With 6-min Walk Distance

 

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  		Table 4. Regression Analysis Results With Stair Climb Time

 

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  		Table 5. Regression Analysis Results With Self-Reported Function

 

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  		Table 6. Regression Analysis Results With CRQ Dimension of Mastery

 

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  		Table 7. Regression Analysis Results With CRQ Dimension of Fatigue

 
Discussion

Previous studies have shown FEV1 to be of limited value in predicting factors that are important to COPD patients, such as symptoms,25 quality of life,26 and exercise capacity.27 In fact, the National Emphysema Treatment Trial28 used maximal exercise capacity as a primary outcome as it was believed to be a better measure of physical performance and functional status as compared to measures of pulmonary function. In the current investigation, we examined the power of VO2peak, when combined with FEV1, to predict physical function and health-related quality of life in COPD patients. To this end, we first forced FEV1 into the model and then entered VO2peak to determine any additional contributions it would add to the predictive power of FEV1. Our results demonstrated that VO2peak does add to the power of FEV1 in predicting 6-min walk distance, stair climb time, self-reported physical function, and the health-related quality-of-life domains of fatigue and mastery in COPD patients.

The added contribution that VO2peak makes to the prediction of 6-min walk distance and stair climb time beyond FEV1 is most likely attributable to the fact that successful completion of physical performance tasks requires an integration of the cardiovascular, respiratory, and musculoskeletal systems. VO2peak is a function of blood flow and oxygen extraction and can be influenced by a number of factors affecting any or all of these systems.16 In contrast, FEV1 is a surrogate for impairment of only the respiratory system. Given cigarette smoking is a common cause of COPD and has additional adverse effects on both the respiratory and cardiovascular systems, the added contribution of VO2peak in predicting physical function is not surprising. These results add support to the belief that cardiopulmonary exercise tests should be included when evaluating physical function in COPD patients.1629

We did find statistically significant, albeit modest, correlations between FEV1 and self-reported physical function. These results are in agreement with those of Mannino et al,3 who reported that severe and moderate airflow obstruction, based on a modification of the GOLD criteria, were associated with a higher odds ratio of self-reported functional limitations. Surprisingly, Mannino et al3 also reported that a high percentage of subjects with lung function impairment did not report functional limitations; these same authors suggest that people may underreport functional limitations. It seems that despite the statistically significant correlations, FEV1 is not a good predictor of functional limitations. If it were the case that FEV1 was a good predictor of functional limitations and the reason patients with airflow limitation did not report functional limitations was due to an underreporting, then we would have expected to see higher correlations between FEV1 and the measures of performance. However, as our results demonstrate, this was not the case.

Previous studies9303132 have found weak or nonsignificant correlations between FEV1 and the various domains of health-related quality of life assessed with the CRQ. Our finding of a weak, but significant, correlation between FEV1 and only the domain of mastery support these previous findings. Quality-of-life questionnaires are designed to elicit patients’ perceptions about disease-related problems in areas of daily living and well-being that are important to them. The low correlations between FEV1 and health-related quality of life suggest that the FEV1 cannot accurately classify patients with respect to these areas of functioning.

Studies that have examined the correlations between the various domains of the CRQ and exercise capacity have shown mixed results. Wijkstra et al32 found no correlation between exercise capacity, as determined by 6-min walk distance or maximal cycle ergometry workload, and the dimensions of fatigue, emotion, and mastery; they did not report the correlation between dyspnea and exercise capacity. In contrast, Hajiro et al9 found moderate correlations between dyspnea, fatigue, emotion, and exercise capacity, as determined from VO2peak (r = 0.25 to 0.48). We found moderate correlations between VO2peak and the domains of mastery and fatigue (r = 0.277 and r = 0.314, respectively). It is unclear why there is so much variation in the correlations reported between the different domains of the CRQ and exercise capacity. Possible reasons may relate to the numbers of subjects in the different investigations, severity of patient disease, and/or the type of exercise test employed (treadmill vs cycle ergometer).

In addition to predicting function and quality of life, other indications for cardiopulmonary exercise testing include the evaluation of undiagnosed exercise intolerance, the evaluation of patients with cardiovascular disease, and clinical applications such as preoperative evaluations and exercise prescription.16 Additionally, Oga and colleagues33 found VO2peak to be more strongly correlated with mortality as compared to age and FEV1. Based on the results of previous studies162933 and those of this investigation, exercise testing should be included as part of a multidimensional evaluation of patients presenting with pulmonary disease, particularly in those with comorbidities.

This study does have several limitations. First, due to the cross-sectional nature of the study and analytical techniques used, it is not possible to determine if lung function impairments or lower VO2peak levels directly resulted in the lower levels of physical functioning. Additionally, patients with significant comorbidities such as unstable cardiovascular disease and those undergoing treatment for cancer and/or untreated hypertension of diabetes were excluded.

In conclusion, VO2peak adds significantly to FEV1 in predicting physical function in COPD patients. Spirometric measures of airflow obstruction, such as FEV1, are technically simple and inexpensive, and spirometry is recognized as key to defining COPD. However, due to the heterogeneous nature of COPD and frequent comorbid conditions, FEV1 is limited in its ability to explain symptoms and functional impairments. We found that VO2peak added to the predictive power of FEV1 for both objective and subjective measures of physical function. VO2peak has a stronger correlation with mortality than FEV1 in COPD,33 and measures of exercise capacity have utility in the multidimensional staging schemes in COPD.34 Treatment and interventional studies of COPD should continue to investigate VO2peak as an important outcome measure.

Footnotes

Abbreviations: ATS = American Thoracic Society; CRQ = Chronic Respiratory Disease Questionnaire; GOLD = Global Initiative for Chronic Obstructive Lung Disease; VO2peak = peak oxygen consumption

Support for this study was provided by grants HL 53755 and AG 21332 from the National Institutes of Health.

Received for publication August 10, 2005. Accepted for publication December 10, 2005.

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