|Year : 2020 | Volume
| Issue : 1 | Page : 6-13
Prognostic assessment in COPD patients: BODE index and the health-related quality of life
Kapil Sharma1, Avinash Jain2, Rajendra Takhar3, DPS Sudan2, Vipin Goyal1, Nikhil Goel4, Vikram Singh5
1 Department of Chest and Tuberculosis, SHKM Govt. Medical College, Mewat, India
2 Department of Pulmonary Medicine, SGT Medical College, Gurgaon, Haryana, India
3 Department of Respiratory Medicine, Government Medical College, Kota, Rajasthan, India
4 Department of Psychiatry, SHKM Govt. Medical College, Mewat, Haryana, India
5 Department of Medicine, SHKM Govt. Medical College, Mewat, Haryana, India
|Date of Submission||26-Jun-2019|
|Date of Acceptance||07-Sep-2019|
|Date of Web Publication||11-Feb-2020|
Dr. Kapil Sharma
Dept. of Chest and TB, Room no. 701, B 1 Block, Medical Campus, SHKM Govt. Medical College, Nalhar, Nuh, Mewat, Haryana, PIN-122107
Source of Support: None, Conflict of Interest: None
Background: Chronic obstructive pulmonary disease (COPD) is a spreading epidemic of a debilitating disease impairing the health-related quality of life (HRQoL) of the patients. This study was conducted to identify the relationship between BODE (body mass index, obstruction, dyspnea, exercise capacity) index and the St George’s Respiratory Questionnaire (SGRQ) and to test the predictive value of both tools against survival. Methods: Open cohort study of 120 COPD patients were followed up to 1 year. At the time of the inclusion, clinical data, forced spirometry, 6-minute walking distance, BODE index, and SGRQ were determined. Vital status and cause of death were documented at the end of follow-up. Results: The cohort’s mean score of age, SGRQ Total (SGRQ_Tot), and BODE index was 57.82 ± 7.58, 44.77 ± 13.81, and 3.04 ± 2.06, respectively. The correlation between SGRQ_Tot and BODE index was good (r = 0.611, P < 0.001). Regression analysis determined age, BODE, comorbidity index, and activity component of SGRQ (SGRQ_A) as predictors of mortality. The area under the curve for the BODE index was 0.801 vs. 0.692 for the SGRQ_A score indicating BODE score as best predictor of mortality. The best cut-off value for predicting mortality was 4.5 for BODE index and 62.5 for SGRQ_A score. Conclusion: Evaluation of HRQoL is an important entity for improving overall disease outcome of COPD.
Keywords: BODE index, COPD, mortality, quality of life
|How to cite this article:|
Sharma K, Jain A, Takhar R, Sudan D, Goyal V, Goel N, Singh V. Prognostic assessment in COPD patients: BODE index and the health-related quality of life. J Assoc Chest Physicians 2020;8:6-13
|How to cite this URL:|
Sharma K, Jain A, Takhar R, Sudan D, Goyal V, Goel N, Singh V. Prognostic assessment in COPD patients: BODE index and the health-related quality of life. J Assoc Chest Physicians [serial online] 2020 [cited 2020 Sep 29];8:6-13. Available from: http://www.jacpjournal.org/text.asp?2020/8/1/6/278121
| Introduction|| |
Chronic obstructive pulmonary disease (COPD) is worldwide the fourth leading cause of morbidity and is expected to be the third leading cause of mortality by 2020. The disease often impairs the health-related quality of life (HRQoL) of the patients. Previous studies states that the BODE [body mass index (BMI), obstruction, dyspnea, exercise capacity] index is a multidimensional and important tool predicting mortality, and number of hospitalizations, and is sensitive enough to change with the interventions like pulmonary rehabilitation and surgical procedures like lung volume reduction surgery (LVRS). We also know that HRQoL is an important patient-reported health outcome and even a modest change in airflow limitation leads to the impairment in HRQoL in COPD patients.,
HRQoL, as measured by the disease (COPD)-specific St George’s Respiratory Questionnaire (SGRQ) and SF-36 generic HRQoL scale, is linked to both respiratory and all-cause mortality.,, Usually, it includes the domains of illness related to the physical, social, and psychological impact. Previous studies have proved that the interventions like pulmonary rehabilitation and surgical procedures like LVRS bring improvements in HRQoL., We know that exacerbations significantly contribute to worsening of COPD disease severity as measured by the BODE index and HRQoL. So, it is quite possible that changes in the BODE index would translate in better or worse HRQoL for patients with COPD.
Some studies suggest a relationship between BODE index and SGRQ, but the studies have included a limited number of patients with short follow-up. Also, there is scarcity of data that has explored the relative value of either test to predict survival., Therefore, it is crucial to identify and appropriately develop treatment strategies for COPD patients in improving their quality of life and thus reducing their healthcare utilization. Therefore, we conducted a study to explore the possible correlation between COPD severity as measured by the BODE index and HRQoL as measured by the SGRQ in COPD patients. In addition, we aimed to determine thresholds of critical value for both the BODE index and the SGRQ in relation to COPD mortality, and to compare the two instruments in their capacity to predict survival in this disease.
| Materials and Methods|| |
It was a cross-sectional type of analytical study conducted in SHKM Govt. Medical College Nalhar Hospital, Haryana, for 15 months’ duration from January 2018 to April 2019. Consecutive outpatients attending the Chest Outpatient Clinic aged between 40 and 80 years and diagnosed of COPD, who met the inclusion criteria, were sequentially recruited for the study. The diagnosis of COPD was established based on complete medical history, symptoms, signs, and available pulmonary function tests, as per the standard definitions provided by GOLD (Global Initiative for Chronic Obstructive Lung Disease, 2018) guidelines. Since the forced expiratory volume in 1 second (FEV1) value decreases more quickly with age than the Forced Vital Capacity (FVC), the GOLD definition tends to overdiagnose COPD in the elderly and underdiagnose in young population. Therefore, sampling population was included from age group of 40 to 80 years in this study.
The study was conducted adhering to the guidelines of the Declaration of Helsinki as well as approval was sought by the Institutional Ethical Committee (Letter no. SHKM/IEC/2018/8). Also, written informed consent was obtained from all patients participating in the study.
Inclusion and exclusion criteria
Inclusion criteria were postbronchodilator (400 µg salbutamol) ratio of FEV1/FVC <0.70; stable conditions, that is, absence of exacerbation (patients could be recruited during exacerbations but were investigated after a stable period of at least 2 months); and ability to perform a 6-minute walk test (6MWT). A COPD patient is considered to have acute exacerbation if there is acute deterioration in symptoms of chronic dyspnea, sputum production, or sputum purulence.
Exclusion criteria were coexisting acute pulmonary tuberculosis, pulmonary fibrosis, bronchiectasis, and pneumothorax; inability to perform spirometry or being physically ill or mentally incapacitate to participate; receiving corticosteroids or immune-suppressive medications; unstable coronary artery disease; neurological disease; and absence of informed consent.
The crude prevalence of COPD in India in 2016 was 4.2%. Sample size required for the study was calculated using the formula Z2p(1−p)/d2. Considering prevalence of COPD as 4% and P = 0.04, Z = 1.96, d = 0.05 (assuming precision error of 5% and type 1 α error 5%), sample size calculated was 60.
Altogether 172 patients were screened, of which 158 were eligible according to the inclusion and exclusion criteria. Of these, 132 patients agreed to participate in the study and considering 12 dropouts in 1 year follow-up, 120 patients were included for study analysis. The medical records and discharge cards of all patients were manually reviewed. Demographic and clinical data were extracted. Demographic data included age, sex, marital status, and highest form of education received (low level: illiterate and primary education; high level: secondary education and graduate). Participants were asked about their smoking habits and exposure to biomass fuel. Comorbidity was measured by the Deyo’s adapted Charlson score. Severity of depression was estimated using Hamilton Depression Rating (HAM-D), and the quality of life was estimated using disease (COPD)-specific SGRQ and generic HRQoL SF-36 scale. For the purpose of this study, the SGRQ percent total scores were divided into quartiles as follows: Q1 <25, Q2 = 25–49, Q3 = 50–74, and Q4 >75.
Measurement of depression
The HAM-D is a useful way of determining a patient’s level of depression before, during, and after treatment. Although the HAM-D form lists 21 items, the scoring is based on the first 17. It generally takes 15 to 20 minutes to complete the interview and scoring the results. Eight items are scored on a 5-point scale, ranging from 0 = not present to 4 = severe. Nine are scored from 0 to 2. Depending upon the total score (range from 0 to 27), the severity of depression was classified as follows: none (0–7), mild (8–13), moderate (14–18), severe (19–22), and very severe (23–27). Patients diagnosed with depression or other psychiatric comorbidities were treated by the specialist in the Department of Psychiatry according to the standard guidelines.
Assessments of COPD
Lung function impairment
Lung function impairment was assessed by spirometry after inhalation of 400 µg salbutamol using a computerized spirometer (Model vitalograph 6800; SN.PN06011Vitalograph Ltd., Ireland). Measurements followed American Thoracic Society criteria for Spirometric standardization and procedures.,
6MWTs were performed using 25-m walk track with two attempts conducted on the same day, at least 30 minutes apart. The patient’s breathlessness was scored using modified Medical Research Council (mMRC) dyspnea scale. The mMRC Dyspnea Scale stages five categories of breathlessness: Grade 0: I only get breathless with strenuous exercise; Grade 1: I get short of breath when hurrying on level ground or walking up a slight hill; Grade 2: On level ground, I walk slower than people of the same age because of breathlessness, or I have to stop for breath when walking at my own pace on the level; Grade 3: I stop for breath after walking about 100 yards or after a few minutes on level ground; Grade 4: I am too breathless to leave the house or I am breathless when dressing. Additionally, the BODE index was calculated for classification of COPD. The score comprises BMI, postbronchodilator FEV1% predicted, grade of dyspnea (measured by the mMRC dyspnea scale), and the 6-minute walking distance. The BODE index was calculated as described: for each threshold value of FEV1% predicted, distance walked in 6 minutes, and score on the mMRC dyspnea scale, the patients received points ranging from 0 (lowest value) to 3 (maximal value):
- BODE stage 1 = BODE index 0–2; BODE stage 2 = BODE index 3–4;
- BODE stage 3 = BODE index 5–6; BODE stage 4 = BODE index 7–10.
Disease (COPD)-specific HRQoL (SGRQ)
Burden of symptoms, physical and social functional status, and impairment of quality of life were measured using the validated Hindi version of SGRQ, which is a self-administered disease-specific HRQoL measure, ranging from 0 (indicating no impairment) to 100. Higher scores indicate a worse health status. The SGRQ symptoms, impact, and activity (SGRQ_S, SGRQ_I, and SGRQ_A, respectively) questionnaire assesses the patient’s experience of symptoms, the amount of distress caused by symptoms, and the daily limitation of activities. It has been well validated for use in medical patients.
SF-36 generic HRQoL
According to Ware and Sherbourne, the SF-36 is a generic quality-of-life instrument that has two summary measures: the physical component summary (PCS) and the mental component summary (MCS). Scores range from zero (worst possible impairment) to 100 (good quality of health). The SF-36 is also well-validated to be used for hospital patients. The SF-36 has eight scaled scores; the scores are weighted sums of the questions in each section including vitality, physical functioning, bodily pain, general health perceptions, physical role functioning, emotional role functioning, social role functioning, and mental health.
The patients were followed-up for 1 year. Data for mortality was confirmed by reviewing the medical records and contacting patient’s relative.
Depending on the variable distribution, results were expressed as numbers, percentages, and mean ± standard error of mean. ANOVA was used to compare baseline characteristics for intragroup and intergroup. Pearson’s correlation coefficients were obtained between different variables and SGRQ. Kaplan-Meier survival analysis was used to assess survival by BODE and SGRQ quartiles. Logistic regression analysis using survival and COPD survival as dependent variables was used to assess the contribution of variables showing significant correlations with these outcomes. We computed the C-statistics to compare the power of the BODE and SGRQ values to predict mortality. In this analysis, the area under the receiver operating curves were quantified and compared to assess the performance of both indices. All statistical analyses were carried out using Statistical Package for Social Sciences (SSPS) (Version 21.0; IBM Corp., Chicago, IL, USA).
| Results|| |
A total of 120 patients with COPD were included for data analysis in the study. Patients were divided according to quartiles of BODE score; 27% of patients were in quartile 1 (BODE score 0–2), 23% in quartile 2 (BODE score 3–4), 29% in quartile 3 (BODE score 5–6), and 21% in quartile 4 (BODE score 7–10). The mean SGRQ % impact, symptom, activity, and total score in terms of mean ± standard deviation was 43.68 ± 17.11, 54.30 ± 21.87, 41.11 ± 19.65, and 44.77 ± 13.81, respectively. Mean age in patients in BODE quartile 4 was highest as 61.20 ± 9.14. Highest value of score in quartile 4 of COPD assessment test, BODE, HAM-D, length of stay in ward, and length of stay in ICU was 30.12 ± 3.85, 6.44 ± 1.44, 24.28 ± 2.01, 8.08 ± 2.01, and 1.52 ± 1.19, respectively. Mean scores of characteristics that were higher in quartile 1 as BMI, 6-minute walk distance, FEV1 liters, MCS SF-36, and PCS SF-36 were as follows: 23.72 ± 2.82, 345.44 ± 52.10, 2.5 ± 0.21, 75.94 ± 12.98, and 66.63 ± 12.90, respectively.
The relationship between the components of the SGRQ and the BODE index are shown in [Table 1]. The SGRQ total correlated better with BODE index than with FEV1% (r = 0.58 vs. r = −0.519, both P < 0.001). The activity domain of the SGRQ correlated best with BODE (r = 0.570, P < 0.001), and the impact and symptom domain of the SGRQ correlated best with mMRC (r = 0.343 and r = 0.434, P < 0.001).
|Table 1 Relationship between the components of the SGRQ and the BODE index|
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Overall, we found that the SGRQ scores worsened exponentially as disease severity increased by BODE quartiles. This study revealed the change in the individual components of SGRQ domains from quartile 1 to 4, were 145%, 56% and 60% respectively for the activity, impact and the symptom scores respectively. On the other hand, the difference in SGRQ total score of patients from quartile 1 to 4 exceeded 64%.
After 1 year of follow-up, 15 (12.5%) patients had died. The cause of death was documented in the case reporting proformas but was not included in the data analysis. Overall analysis of death suggests as 11 (73.3%) due to exacerbation of their baseline disease (COPD), three (20%) died of cardiovascular or cerebrovascular causes, and no cause of death was recorded for 1 patient. We found both tests (the BODE index and SGRQ total) to correlate with mortality (r = 0.421, P < 0.001 and r = 0.221, P = 0.012, respectively).
The expected median survival decreased with the increase in the BODE and the SGRQ quartiles, however the differences were statistically significant among BODE and the SGRQ_ A quartiles [Table 2]. BODE quartile was divided as discussed previously and SGRQ quartile was divided as Q1 (<25 score), Q2 (26–49 score), Q3 (50–74 score), and Q4 (75–100 score). Mortality of patients with SGRQ_A Q4 was 20% vs. BODE Q4 that was 73%. We also used Kaplan-Meier analysis and compared the survival of patients divided by SGRQ_A quartiles and BODE quartiles. Overall, BODE and SGRQ_A quartiles survival curves were different, but these differences appear better defined when the cohort was grouped in BODE than SGRQ_A quartiles (P < 0.001 vs. P = 0.10). Cox regression analysis [Table 3] with mortality as dependent variables showed age, BODE, SGRQ_A, and Deyo’s adapted Charlson comorbidity index as the elements of the model predicting mortality. The C-statistics was 0.801 (95% confidence interval, 0.664–0.937, P < 0.001) for BODE index and 0.692 (95% confidence interval, 0.534–0.85, P = 0.016) for SGRQ_A score, indicating BODE score as better predictor of mortality [Figure 1]. The best cut-off value for predicting mortality was 4.5 for BODE index and 62.5 for SGRQ_A score, which we found out with the help of taking maximal Youden’s index.
|Table 2 Relationship between the survival statistics and the different quartiles of BODE and the SGRQ components|
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|Figure 1 Comparison of area under curve of receiver operating characteristics between the St George’s Respiratory Questionnaire activity and BODE (BMI, Obstruction, Dyspnea, Exercise Capacity).|
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| Discussion|| |
There were few novel findings in our study. First, it showed that there is a better correlation between the BODE index and the SGRQ quality of life questionnaire, when compared to the gold standard FEV1 [Table 1]. Second, the BODE index is better predictor of mortality than SGRQ scores in COPD [Figure 1]. Third, out of all individual components of SGRQ, only SGRQ _A was found to be predictor of mortality [Table 2] and [Table 3]. Fourth, we have found that the SGRQ scores worsen as COPD severity increases by BODE index quartiles [Table 4]. Finally, we have confirmed prior observations made by Wijkstra et al. about the impact of comorbidity in the HRQoL of patients with COPD using the validated Charlson score.
|Table 4 Comparison of different clinical characteristics according to BODE quartiles|
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It has been proved that several of these factors are better predictors of survival than the simple degree of airflow limitation as measured by the FEV1.,, That is why present researchers focus on the global assessment of an affected patient including different aspects of the consequences of this disorder, beyond the “gold-standard” assessment of airflow limitation. The BODE index was a better predictor of outcome than the FEV1 in a large cohort of patients with COPD, and better than all the individual components of the index in patients undergoing LVRS. The disease-specific SGRQ is perhaps the most widely used and better tested of the instruments reflecting the disease-specific quality of their life of patients with COPD. It has proven to be responsive to several interventions in COPD such as pharmacological agents, pulmonary rehabilitation, and lung volume reduction. Secondary analyses of some of these studies have also suggested that the SGRQ can be useful in predicting survival, although one study using a different disease-specific questionnaire, the Chronic Respiratory Questionnaire (CRQ), failed to observe an association between the scores obtained and mortality. Our study states that BODE index and SGRQ reflect the severity of COPD according to conventional GOLD scale and show that the correlations of SGRQ and BODE were stronger than with airflow obstruction, graded with FEV1. The BODE index and SGRQ have a significant but modest correlation between themselves indicating that they do not measure the exact same dimension [Table 1]. Interestingly, the best correlations between SGRQ domains were seen with activity component and not with symptoms and impact. In contrast to the previous study done by Fan et al. in which only symptom component was poorly correlated. There is a very good correlation between mMRC and SGRQ, indicating that functional capacity is likely a very important determinant of quality of life in COPD.Cox regression analysis [Table 3] with mortality as dependent variables showed age, BODE, SGRQ_A, and DCI as the elements of the model predicting mortality. The probable explanation is because of the purpose of development of these two different tools. The present study was conducted with the motive of evaluating the similarities and differences between BODE and SGRQ. We propose that evaluation of HRQoL is an important entity for not only improving overall disease outcome but also combating the health resource utilization or even mortality. Also, our study states that the BODE index better reflects stages of COPD if mortality is considered the ultimate expression of disease severity, like previous studies wherein BODE has proven sensitive to reflect exacerbation severity, the response to surgery,, and pulmonary rehabilitation. Perhaps, future studies are required to use the strength of both tools to express the complex nature of COPD better.,
To our knowledge, this is one of the few studies performed in India that measures most of the characteristics of COPD and measuring both disease-specific (SGRQ) and generic HRQoL (SF-36), followed over 1-year period. There were some limitations to this study. First, follow-up period should be around 5 years to understand the heterogeneity of this disease. Second, we needed other instruments apart from HRQoL, such as physical activity, various comorbidities, and psychological health evaluating questionnaires to find other correlations of this disease. However, it has been shown by Hajiro et al. that all the questionnaires designed to evaluate HRQoL are highly correlated. We would expect further studies to validate our findings.
To conclude, it can be stated that evaluation of HRQoL is an important entity for improving overall disease outcome and combating the health resource utilization or even mortality. Our study shows that BODE is a slightly better predictor of mortality than the SGRQ, and therefore a better instrument to determine severity of COPD. The SGRQ on the other hand reflects patient’s physical, emotional, and social well-being interpreting the overall compromise made by the patients with this disease.
The authors would like to thank the entire staff of Pulmonary Medicine Department of SGT Hospital, Gurgaon, and SHKM Govt. Medical College, Nalhar, Haryana, for their constant support and collaboration.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
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[Table 1], [Table 2], [Table 3], [Table 4]