Abstract
Rationale: Depression is prevalent in patients with chronic obstructive pulmonary disease (COPD); however, its etiology and relationship to the clinical features of COPD are not well understood.
Objectives: Using data from a large cohort, we explored prevalence and determinants of depression in subjects with COPD.
Methods: The Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints study is an observational 3-year multicenter study that enrolled smokers with and without COPD and nonsmoker controls. At baseline, several patient-reported outcomes were measured including the Center for Epidemiologic Studies of Depression Scale. For the purposes of this analysis, depression was defined as a score of 16 and higher on this scale, which reflects a high load of depressive symptoms and has a good correspondence with a clinical diagnosis of major depression.
Measurements and Main Results: The study cohort consisted of 2,118 subjects with COPD; 335 smokers without COPD (smokers); and 243 nonsmokers without COPD (nonsmokers). A total of 26%, 12%, and 7% of COPD, smokers, and nonsmokers, respectively, suffered from depression. In subjects with COPD, higher depression prevalence was seen in females, current smokers, and those with severe disease (Global Initiative for Obstructive Lung Disease [GOLD]-defined). Multivariate modeling of depression determinants in subjects with COPD revealed that increased fatigue, higher St. George's Respiratory Questionnaire for COPD patients score, younger age, female sex, history of cardiovascular disease, and current smoking status were all significantly associated with depression; physiologic and biologic measures were weak or nonsignificant descriptors.
Conclusions: Depression is more prevalent in subjects with COPD compared with smokers and nonsmokers without COPD. Clinical and biologic measures were less important determinants of depression in COPD than disease symptoms and quality-of-life.
Clinical trial registered with www.clinicaltrials.gov (NCT 00292552).
The course of chronic obstructive pulmonary disease (COPD) is complicated by multiple comorbidities. Depression is more prevalent in COPD than in the comparable general population. Within the population with COPD, depression is more common in severe disease stages. Furthermore, subjects with COPD with comorbid depression experience worse outcomes than those without depression.
This prospectively designed study investigated the prevalence and determinants of depression in a phenotypically well-characterized cohort with COPD. Subjective measures, represented by quality of life and symptoms, were stronger determinants of depression than objective measures, such as lung function and biologic and physiologic markers.
Although growing evidence suggests that certain interventions, such as pulmonary rehabilitation, antidepressants, and counseling, may improve health outcomes, the diagnosis of depression in COPD continues to be overlooked (3, 8). It is also estimated that only one-third of patients with COPD who suffer from depressive symptoms receive proper treatment for their condition (16). Unfortunately, evidence-based guidelines for COPD do not provide a detailed outline for a comprehensive approach to screening, diagnosing, and treating depression (17). Practical screening instruments for depression, such as the Hospital Anxiety and Depression Scale and Primary Care Evaluation of Mental Disorders, were validated in patients with COPD, exhibit good positive predictive value, and can be used in the primary care setting (18). More detailed questionnaires, such as the Becks Depression Inventory II, Symptom Checklist 90–Revised, and Center for Epidemiologic Studies of Depression (CES-D), are also useful for screening of possible depression (3). Although these screening tools are widely available, none have been widely used in the primary care setting or by pulmonary specialists.
Many biologic aspects of depression in patients with COPD remain unknown, even though few studies have attempted to identify determinants of depression in that patient population (19–23). Further, an association between COPD disease symptoms and depression had been recognized (13, 22, 24, 25). Such studies have usually been of smaller size (study size usually ranging between 50 and 200 COPD participants with a maximum of 1,300 subjects), and some were retrospective or have included poorly characterized patient populations (3).
The Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints (ECLIPSE) study is a large, multinational, 3-year prospective study that included subjects with COPD, smoker, and nonsmoker control populations. This study is unique in that it comprehensively examines associations of depression with biologic, clinical, and physiologic descriptors in one setting. We therefore used data from ECLIPSE to further explore (1) the prevalence of current depression defined as a high load of depressive symptoms in a population with wide spectrum of COPD severity, (2) the association of depression with COPD burden, and (3) the potential determinants of depression symptoms in COPD to aid clinicians to better identify patients at risk for depression and to enhance the opportunity to implement early intervention.
Some data from this study were previously presented in the form of an abstract (26).
The ECLIPSE study is a noninterventional observational prospective 3-year multicenter study. The study design has been extensively described elsewhere (27). ECLIPSE was conducted in 46 centers from 12 countries in accordance with the Declaration of Helsinki and good clinical practice guidelines, and was approved by all participating centers' ethics and review boards. A list of countries and the number of subjects in this analysis per country are provided in the online supplement (see Table E1).
Baseline data from subjects with COPD aged 40–75 years, with post-bronchodilator FEV1 of less than 80% of predicted normal, post-bronchodilator FEV1/FVC less than or equal to 0.7, and smoking history greater than or equal to 10 pack-years were used for this analysis. Further, data from two control cohorts, smokers and nonsmokers without COPD, were used for a comparison of depression prevalence. Controls were selected from a population aged 40–75 years without significant disease. “Smokers” were required to have at least 10 pack-years history of smoking; “nonsmokers” were subjects with less than 1 pack-year history of smoking. In both control cohorts, COPD was excluded by spirometry (baseline post-bronchodilator FEV1 >85% of predicted normal and FEV1/FVC ratio >70%). Additional detail on the subjects' selection criteria is provided in the online supplement.
On enrolment in the study, subjects responded to a questionnaire about their health, including questions about COPD exacerbations in the preceding 12 months and the course of their disease. Lung function tests, 6-minute walk distance (6MWD), computerized chest scan (computerized tomography), body composition by bioimpedance, and blood withdrawals were performed. In addition, patient-reported outcomes were measured, including assessment of dyspnea (modified Medical Research Council [MRC] Dyspnea scale); fatigue (Functional Assessment of Chronic Illness Therapy-Fatigue questionnaire [FACIT-F]); depression (CES-D); and quality of life (St. George's Respiratory Questionnaire for COPD patients [SGRQ-C]) (28–31). Respiratory symptoms were also collected using the well-established American Thoracic Society–Division of Lung Diseases (ATS-DLD) questionnaire, which was updated for the purpose of this study (32). For all the questionnaires, except for the adapted ATS-DLD questionnaire, available cross-culturally validated versions were used. Where such a validated instrument was missing, further work was dedicated to translation, retranslation, and piloting a questionnaire in the local population. Additional details on study assessments and measurement of baseline serum biomarkers are provided in the online supplement.
The CES-D, a self-administered questionnaire composed of 20 items, was used to measure the presence and severity of depressive symptoms experienced during the preceding week (31). Each item is rated on a four-point scale ranging from “rarely or none of the time” to “most or all of the time.” CES-D score can be used as a continuous measure, where higher scores are indicative of presence of depressive symptoms, or as a binary indicator of a possible depression using a cut-off point. In this analysis, presence of current depression was defined as a CES-D score of 16 and higher, which indicates a high load of depressive symptoms and has a reasonable validity for major depression with sensitivity around 80% and specificity around 70% (26).
All descriptors were assessed from measures collected at the baseline visit. Means and standard deviations were computed for the continuous variables, with frequencies calculated for categorical variables. Spearman correlation coefficients were calculated between the CES-D total score and descriptor variables. For tests between cohorts or depression categories, an analysis of variance for continuous variables or a chi-square test for categorical variables was used. Because of the skewed distribution of biomarker variables, medians and interquartile ranges were calculated, and the distribution of values across depression categories was compared using a Kruskal-Wallis test. Based on the outcomes of descriptive and correlation analyses, descriptors of interest were assessed using multivariate logistic regression. The combined analysis of symptom-based and clinically based descriptors was assessed using a stepwise logistic regression model (P value for entry into the model was < 0.1 and P value to retain in the model was < 0.1). Odds ratio estimates and 95% Wald confidence limits were calculated for each covariate in the model.
In total, data from 2,118 patients with COPD, 335 smokers, and 243 nonsmokers without COPD were available for this analysis. Baseline demographics and clinical characteristics of study cohorts are listed in Table 1. COPD subjects were older and more often males. Therefore, to assess an impact of these differences on depression prevalence, we matched COPD and non-COPD cohorts on sex and age. The resulting estimates were comparable to those seen in the total cohort, and hence we present the total cohort estimates. Data from the matched cohort analysis are presented in the online supplement (Tables E2, E3a, and E3b).
Variable | COPD (n = 2,118) | Smokers without COPD (n = 335) | Nonsmokers (n = 243) |
|---|---|---|---|
| Age, mean (SD) | 63 (7) | 55 (9) | 54 (9) |
| Female sex, % | 35 | 44 | 63 |
| Current smoker, % | 36 | 60 | n/a |
| Post-bronchodilator FEV1% predicted, mean (SD) | 48 (16) | 109 (12) | 115 (14) |
| CES-D score, mean (SD) | 11 (9) | 7 (8) | 6 (7) |
| Depression, %* | 26 | 12 | 7 |
| Antidepressant use, %† | 13 | 9 | 9 |
| History of depression, %‡ | 16 | 15 | 14 |
Prevalence of depression defined as a CES-D score of 16 and higher was observed in 26% of subjects with COPD compared with 12% of smokers without COPD and 7% of nonsmokers. Further, subjects with COPD were more often prescribed antidepressant medications than the other two cohorts.
The prevalence of depression in certain subsets of subjects with COPD is shown in Figure 1. Depression symptoms were more prevalent in subjects with more severe disease (Global Initiative for Obstructive Lung Disease [GOLD] stages III and IV compared with GOLD stage II) (P < 0.003); women (P < 0.001); younger subjects with COPD (younger than 60; P < 0.001); and current smokers (P = 0.012).
Figure 1. Depression prevalence (Center for Epidemiologic Studies of Depression Scale score ≥ 16) in subjects with chronic obstructive pulmonary disease (COPD) (n = 2,118) stratified by age, sex, smoking status, and GOLD stage.
[More] [Minimize]Table 2 lists baseline characteristics of subjects with COPD stratified by presence of depression (CES-D score ≥ 16). Subjects with COPD and depression were more likely to be female, to be current smokers, to have a history of cardiovascular disease, and to report symptoms of chronic bronchitis, including chronic cough and chronic sputum production, than those subjects with COPD without depression. Further, subjects with COPD and depression were more likely to have had a moderate to severe exacerbation and been hospitalized because of an exacerbation in the preceding year.
Demographic and Disease-related Descriptors | CES-D ≥ 16 (n = 557) | CES-D <16 (n = 1,561) | P Value |
|---|---|---|---|
| Age, yr | 62 (7) | 64 (7) | <0.001 |
| Female, % | 43 | 32 | <0.001 |
| Body mass index, kg/m2 | 27 (6) | 27 (6) | 0.431 |
| Fat-free mass, kg (SD) | 50 (14) | 52 (13) | 0.011 |
| Current smoker, % | 41 | 35 | 0.012 |
| Pack-year history | 49 (27) | 49 (27) | 0.618 |
| BODE Index | 3.9 (2.2) | 2.9 (2) | <0.001 |
| Exacerbation rate, prior year (PPPY)* | 1.09 | 0.78 | <0.001 |
| Hospitalized for exacerbation in prior year, % | 20 | 14 | <0.001 |
| ≥ 3 exacerbation in prior year, % | 14 | 8 | <0.001 |
| ≥ 3 concurrent COPD medications, % | 76 | 71 | 0.020 |
| Chronic cough, % | 57 | 47 | <0.001 |
| Chronic phlegm, % | 58 | 49 | <0.001 |
| Cardiovascular history (includes hypertension), % | 60 | 55 | 0.039 |
| Asthma history, % | 24 | 22 | 0.472 |
| Diabetes history, % | 9 | 11 | 0.203 |
| Reflux or peptic ulcer history, % | 39 | 27 | <0.001 |
| Osteoporosis history, % | 17 | 12 | 0.001 |
| Antidepressant use, %† | 22 | 10 | <0.001 |
| History of depression, %‡ | 35 | 10 | <0.001 |
Indices of lung function including FEV1 and slow vital capacity were lower in subjects with COPD and depression, although the clinical significance of such differences is questionable (Table 3). Furthermore, subjects with COPD and depression had a significantly lower 6MWD compared with those without depression (331 m versus 382 m; P < 0.001). Quality of life–related outcomes (SGRQ-C, total score and domains scores), fatigue, and dyspnea were also significantly worse in subjects with COPD and depression (Table 3).
Mean (SD) | CES-D ≥ 16 (n = 554) | CES-D <16 (n = 1553) | P Value |
|---|---|---|---|
| FEV1% predicted* | 46 (16) | 49 (16) | 0.002 |
| IC % predicted* | 84 (24) | 86 (20) | 0.188 |
| Slow vital capacity % predicted* | 88 (22) | 95 (20) | 0.002 |
| Emphysema (−950 HU) | 17 (12) | 18 (12) | 0.425 |
| 6MWD, m | 331 (119) | 382 (120) | <0.001 |
| Blood oxygen, % | 94.1 (3.1) | 94.7 (2.9) | <0.001 |
| Fatigue, FACIT-F score | 26 (10) | 38 (9) | <0.001 |
| MRC Dyspnoea Score (≥ 2), % | 69 | 48 | <0.001 |
| SGRQ-C total score | 64 (17) | 45 (19) | <0.001 |
| SGRQ-C symptoms score | 70 (20) | 57 (21) | <0.001 |
| SGRQ-C impacts score | 55 (19) | 33 (20) | <0.001 |
| SGRQ-C activities score | 77 (20) | 59 (25) | <0.001 |
Plasma and serum biomarkers levels did not show any significant difference between those with or without depression (Table 4).
Median (interquartile ranges) | CES-D ≥ 16 (n = 554) | CES-D <16 (n = 1,553) | P Value |
|---|---|---|---|
| Fibrinogen, mg/dl | 453 (390–516) | 443 (386–511) | 0.306 |
| hsCRP, mg/L | 3.5 (1.6–7.9) | 3.1 (1.6–6.9) | 0.134 |
| SP-D, ng/ml | 115 (80–174) | 120 (85–170) | 0.489 |
| CCL-18, ng/ml | 104 (81–139) | 105 (82–134) | 0.834 |
| IL-6, pg/ml | 2.1 (0.6–5) | 2.1 (0.6–4.6) | 0.760 |
| IL-8, pg/ml | 7.6 (3.6–14.9) | 7 (3.4–12.8) | 0.114 |
| TNF-α, ng/ml | BQL (BQL–5.7) | BQL (BQL–13.5) | 0.145 |
| CC-16, ng/ml | 4.5 (3.2–6.6) | 5.1 (3.5–7.1) | 0.001 |
Correlation analysis revealed significant relationships between the CES-D score and patient-reported outcomes; increase in depressive symptoms correlated with increased fatigue (FACIT-F rho = −0.63), worse quality of life (SGRQ-C score, rho = 0.50), and increased dyspnea (mMRC Dyspnea scale, score 2 or higher versus (0 or 1, rho = 0.30). Physiologic measures showed weaker correlations with an increase in depressive symptoms: 6MWD decreased (rho = −0.22) as well as oxygen saturation (Po2) (rho = −0.13). Furthermore, with increase in symptoms of depression, body mass index, airflow obstruction, exercise, and dyspnea (BODE) score (rho = 0.26) and exacerbation frequency in the preceding year (rho = 0.12) increased. Other tested variables with a correlation coefficient of less than 0.10 were not considered as having a meaningful correlation with depressive symptoms, including age, body mass index, fat-free mass, education status, concurrent respiratory medication use, pack-years of smoking, smoking status, radiologically defined extent of emphysema (−950 HU), inspiratory capacity, bronchodilator reversibility, FEV1 percent predicted, FEV1 reversibility and FEV1/FVC ratio, and further serum or plasma biomarkers (C-reactive protein, fibrinogen, IL-8, IL-6, tumor necrosis factor-α, Clara cell protein-16, and chemokine ligand 18).
Two separate multivariate models testing determinants of depression were explored: one included symptoms and patient-reported outcomes (SGRQ-C, fatigue score, sputum and phlegm production) and the other investigated physiology and clinical measures (6MWD, FEV1 in liters, blood oxygen, computed tomography–defined emphysema, COPD exacerbations history in preceding 12 mo, history of cardiovascular comorbidity, pack-years of smoking, and respiratory treatment). Each model was further adjusted for age, sex, smoking status, and country of origin. The final, combination model, was fitted with markers significant in either of the initial models (Table 5). Although the overall predictive capability of the model was very weak (generalized R2 = 0.22), quality of life indicators, especially SGRQ-C total score, were the strongest predictors in the final model. Addition of clinical measurements (e.g., extent of emphysema, 6-MWD, and exacerbation history) did not significantly alter the overall predictive value of the model.
Parameter | Reference | OR | 95% CI | P Value |
|---|---|---|---|---|
| SGRQ-C total score | 4pt increase | 1.30 | (1.26–1.34) | <0.001 |
| Sex | Female vs. male | 1.76 | (1.38–2.25) | <0.001 |
| Country | United States as reference | * | <0.001 | |
| Cardiovascular history | Yes vs. no | 1.40 | (1.10–1.78) | 0.006 |
| Smoking status | Current vs. former | 1.41 | (1.10–1.82) | 0.008 |
| Age | 1-yr increase | 0.81 | (0.68–0.96) | 0.015 |
| GOLD stage† | GOLD III vs. GOLD II | 0.71 | (0.55–0.92) | 0.018 |
| GOLD IV vs. GOLD II | 0.67 | (0.47–0.96) | ||
| Chronic cough† | Yes vs. no | 0.75 | (0.58–0.97) | 0.027 |
The data from this large, well-characterized cohort confirm that depressive symptoms are substantially more prevalent in subjects with COPD compared with smokers or nonsmokers without COPD (two- to three-fold difference between groups). This difference in depression prevalence, 26% of subjects with COPD compared with 12% of smokers without COPD and 7% of nonsmokers, suggests that depression is more related to the COPD disease itself rather than simply to habits associated with smoking. High depressive symptoms significantly correlated with poor patient-reported outcomes (SGRQ-C, fatigue score, dyspnea score) and increased health care use (moderate-severe COPD exacerbations) in subjects with COPD. Weak correlations were observed between physiologic measures and exercise and CES-D score. Surprisingly, little or no correlation was observed among CES-D score and serum biomarkers representing mainly inflammation, emphysema as measured by chest tomography, and most of the lung function tests. Multivariate analyses confirmed the results of the correlation analysis and revealed that clinical and physiologic measures were less important determinants of depression in COPD than disease symptoms and quality-of-life measures.
Various studies have reported increased prevalence of depression in COPD and other chronic medical conditions (3, 33–37). Compared with prior studies, our cohort was well characterized and included smokers with and without COPD and nonsmoker controls. Moreover, for the COPD cohort, a broad population of moderate-to-severe COPD, current and former smokers, females and males, and younger and older subjects was recruited. This recruitment strategy enhanced the ability to assess prevalence of depression and its descriptors in populations often underrepresented in prior studies (i.e., moderate COPD, females, and younger patients). Previous studies used various screening instruments to evaluate the presence of depressive symptoms and less often used Diagnostic and Statistical Manual-IV criteria to establish the medical diagnosis of depression. Our choice of the CES-D instrument to measure depressive symptomatology and as a screener for depression was pragmatic. CES-D is a versatile, short instrument, well-established in epidemiologic studies (38). It covers several domains of mental health relevant to depression symptoms: depressed mood, feelings of guilt and worthlessness, feelings of helplessness and hopelessness, loss of appetite, sleep disturbance, and psychomotor retardation. The total score can be categorized into two categories referring to populations with currently low (score <16) or high probability of suffering with major depression (score ≥16). It has also been found to be valid and reliable in identification of depression in older individuals (39–43). However, the CES-D is not without limitations; it cannot be used to differentiate between persons with a primary diagnosis versus a secondary diagnosis of depression, and it was not designed as a diagnostic tool and thus should not be used in lieu of a comprehensive psychiatric evaluation.
Other options for depression screening questionnaires in COPD include the Patient Health Questionnaire-9, the 15-item Geriatric Depression Scale, and the Hospital Anxiety and Depression Scale. These three questionnaires were recently validated after the initiation of the currently presented study in subjects with COPD and have reasonable screening properties for depression diagnosis (44–46).
In the COPD cohort (n = 2,118), depression prevalence was higher in females and younger subjects. Higher depression prevalence in middle-aged compared with older populations has been described in the literature, as has preponderance of depression in women in the general population and in patients with COPD (21, 47, 48). Although there was no difference in sex and disease severity (GOLD stage) distribution between younger and older subjects with COPD, younger subjects were more often current smokers. Higher rates of current smoking could have contributed to an increased prevalence of depression in the younger age group. However, this finding may also be related to the fact that older individuals have higher threshold to depression having lived with their disease longer. The clinical severity and burden of COPD in our subjects with COPD with depression was remarkably worse than those without depression. Health care use as measured by moderate-to-severe and severe COPD exacerbations in the preceding year was significantly higher in subjects who were depressed compared with subjects who were not depressed.
A hypothesis of an increased depression occurrence in COPD and other chronic disease based on shared inflammatory pathways has been compelling. Evidence for an inflammatory pathogenesis has been extensively documented in COPD and to a lesser degree in depression (49–52). However, we have not observed any correlation between inflammatory biomarkers (C-reactive protein, fibrinogen, IL-8, IL-6, tumor necrosis factor-α, surfactant protein-D, Clara cell protein-16, and chemokine ligand 18) and CES-D score in our cohort. Previously, Quint and colleagues (12) reported that serum C-reactive protein and IL-6 do not have a relationship to CES-D score in a small, but well-characterized population of patients with COPD (n = 170). Therefore, depression in COPD may not be related to the inflammatory and physiologic changes related to this disease as much as to the disease's clinical presentation and impact on everyday life.
In our large cohort of subjects with COPD, we attempted to identify potential determinants of depression. We have demonstrated that in a multivariate environment, clinical or physiologic measures are less important determinants of depression in COPD than disease symptoms and quality-of-life measures. These findings seem to confirm earlier, mostly small-scale studies (sample size usually between 50 and 200 subjects), which concluded that symptoms, including depression, are more significantly related to the subjective health status of patients with COPD than to physiologic variables or physical function (12, 22, 23, 53). However, it is important to point out that the overall explanatory value of our final multivariate regression model was weak. Therefore, even though we have tested an extensive range of potential determinants, none of them explained well the presence of depression in patients with COPD, with the exception of the contribution of the SGRQ-C total score. This is suggestive that depression may in fact be an independent marker of COPD. Based on these results, we can hypothesize that in COPD, depression is primarily driven by a patient's perception of a serious chronic disease comprising burdensome symptoms and limitations to daily activities rather than driven by the extent of the underlying inflammatory pathology related to COPD.
There are several limitations to our study. First, because of its multicountry character and focus on usually underrepresented populations, our population with COPD may not be an accurate representative of any national population with COPD. Further, we observed a difference in sex and age distribution between the COPD and non-COPD cohorts. However, the differences between subjects with COPD and without COPD were corrected using matching methods, and the matched results are provided in the online supplement. Second, in the absence of a comparative instrument in the study, we are not able to establish psychometric properties of the CES-D questionnaire in the population with COPD and hence, we have to rely on reports of CES-D use in other diseases (e.g., cancer [54]). Furthermore, our definition of depression was based on a score of a well-validated instrument (CES-D) and we did not seek an objective, physician-based diagnosis of depression. Even though this study attempted to thoroughly describe patients with COPD, some further information would perhaps help to characterize the subjects, including more detailed comorbidity information. Subjects for this study were selected based on predefined criteria, and therefore may not accurately represent the general population of subjects with COPD. For example, only subjects younger than 75 years of age were allowed to join the cohort and subjects with a prior cancer diagnosis were excluded. Lastly, because of a cross-sectional nature of this analysis, we could not assess with certainty any possible etiologic or causal links between COPD and depression.
We believe that our study has several implications. The findings suggest that depression in COPD is associated with worse quality of life measures and increased perception of symptoms, which suggests that targeting depression may improve overall subjective health status. However, it should be emphasized that it is still unclear if treating depression would necessarily improve COPD prognosis because this requires a longitudinal interventional study. Furthermore, because of the multicomponent character of chronic diseases, such as COPD, it may be difficult to improve patients' prognosis with a single intervention. Although this question was not intensively studied in COPD (8), it has been studied in other areas. In a large trial of 2,481 patients with a history of myocardial infarction, long-term depression treatment (cognitive behavioral treatment ± selective serotonin reuptake inhibitors) did not significantly modify patients' heart failure prognosis despite improvement of their depression and social isolation (55). A retrospective cohort study of United States veterans showed a 30% decrease in mortality in subjects with COPD with depression accessing specialist mental health clinics compared with those whose depression was not treated using standard protocol (16).
In summary, depression is more prevalent in subjects with COPD than in smokers and nonsmokers without COPD. The presence of depressive symptoms is associated with worse functional and health status. Health-related quality of life and symptom measures are more predictive of depression than physiologic and biologic measures of the disease. Targeting depression in this population may improve health status and subjective outcomes but this requires further evaluation in future prospective studies.
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