Main Contributory Factors on Asthma Control and Health-Related Quality of Life in Elderly Asthmatics

OBJECTIVE

To assess the main factors involved in asthma control and health-related quality of life in elderly asthmatic patients.

METHODS

We performed a retrospective case-control study nested in a historical cohort that compared patients who had partly controlled or uncontrolled asthma (Asthma Control Test [ACT] score ≤19) (cases) with patients who had well-controlled asthma (ACT ≥20) (controls). Clinical data were collected from medical records. Outcomes included ACT score and health-related quality of life (Asthma-Specific Quality of Life Questionnaire [AQLQ]). Pulmonary function was determined by spirometry.

RESULTS

We evaluated 209 asthma patients (151 women) aged ≥65 years. Mean age was 73.55 years. Most patients had persistent moderate (47.60%) or severe (47.12%) asthma. A total ACT score ≤19 was obtained in 64 (30.62%) patients. Lack of adherence to treatment and presence of severe exacerbations were risk factors for partly controlled/uncontrolled asthma (OR, 8.33 and 5.29, respectively). In addition, for each additional unit score in the AQLQ, the risk of poor control increased by 1.51. The factors influencing the AQLQ score were asthma control (ACT) and presence of comorbidities such as depression, gastroesophageal reflux disease, and osteoporosis.

CONCLUSIONS

Despite receiving antiasthma therapy, almost one-third of elderly patients had uncontrolled asthma, possibly as a result of poor adherence, exacerbations, and reduced health-related quality of life. Nonrespiratory comorbid conditions in older patients do not seem to be associated with worse control of asthma symptoms, although their effect on health-related quality of life could indirectly affect asthma control.

Plasma LTE4/PGF2α Ratio and Blood Eosinophil Count Are Increased in Elderly Asthmatics With Previous Asthma Exacerbation

The tools for asthma control assessment recommended by the current guideline are cognitive function- and effort-dependent, which is substantially impaired in the elderly. The aim of this study is to investigate objective assessment tools of asthma control status and previous asthma exacerbation (AE) in elderly subjects. Asthmatics aged >60 years who were treated with step 2 or 3 by the Global Initiative for Asthma (GINA) guideline were enrolled. During the 12-week study period, the subjects used either 400 µg of budesonide plus 10 mg of montelukast or 800 µg of inhaled budesonide. The occurrence of AE during the 4-week run-in and 12-week treatment period was monitored. After 12-week of treatment, sputum eosinophil count, peripheral eosinophil count, the plasma leukotriene E₄ (LTE₄), and prostaglandin F_2α (PGF_2α) metabolite levels were measured using the UHPLC/Q-ToF MS system. The study subjects were divided into group 1 (asthmatics who experienced AE during the study period) and group 2 (those who did not). A total of 101 patients aged 60-85 years were enrolled. Twenty-three patients (22.8%) had experienced AE. The plasma LTE₄ level, LTE₄/PGF_2α ratio, and peripheral eosinophil count were significantly higher in group 1 than in group 2 (P=0.023, P=0.010, P=0.033, respectively). The plasma LTE₄/PGF_2α ratio and peripheral eosinophil count at week 12 were significantly associated with previous AE (odds ratio [OR]=1.748, P=0.013; OR=1.256, P=0.027). Receiver operating characteristic (ROC) curves to discriminate the subjects with previous AE, including these 2 parameters, showed that the area under the curve was 0.700 (P=0.004), with 73.9% sensitivity and 47.9% specificity. In conclusion, a combination of plasma LTE₄/PGF_2α ratio and peripheral eosinophil count can be an objective assessment tool which is significantly associated with asthma control status in elderly asthmatics.

Characteristics of phenotypes of elderly patients with asthma

BACKGROUND

The characteristics of phenotypes of elderly patients with asthma are unknown. The aim of this study was to classify these phenotypes using lung function tests and images from high-resolution computed tomography (HRCT), and to identify associations between clinical characteristics and phenotypes.

METHODS

A cross-sectional study was conducted in 165 elderly patients (>65 years of age) who underwent a multidimensional assessment of clinical and functional status and comorbidity. The patients were divided into three phenotypes: (1) asthma-predominant, (2) asthma-obstructive airway disease (OAD) overlap without emphysema, and (3) asthma-OAD overlap with emphysema (asthma-emphysema overlap) based on chest HRCT. A receiver operating characteristic (ROC) curve was constructed to evaluate the cutoff for differentiating between the two OAD phenotypes. Multivariate analysis was also used to distinguish between these two phenotypes.

RESULTS

The phenotypes were asthma-predominant in 48 patients (29%), asthma-OAD without emphysema in 36 (22%), and asthma-emphysema in 81 (49%). Patients with asthma-emphysema were more frequent smokers. In multivariate analysis, smoking status (odds ratio 2.92: 95% CI 1.21-7.00, P = 0.03) and % predicted FEV1 ≤70% (odds ratio 3.18: 95% CI 1.13-8.92, P = 0.03) differed significantly between the asthma-emphysema and asthma-OAD without emphysema phenotypes.

CONCLUSIONS

Half of elderly patients with asthma are characterized by asthma-emphysema overlap. Our results showed that elderly patients with asthma who are smokers and have moderate or severe OAD are also likely to have emphysema.

Differences between asthma in young and elderly: results from the COREA study

BACKGROUND

There has been no large-scale and comprehensive study of the differences between asthma in elderly asthmatics (EA) and non-elderly (i.e. young) asthmatics (NEA).

METHODS

We performed principal component analysis (PCA) using 2067 asthmatics (434 EA and 1633 NEA) from the Korean Cohort for Reality and Evolution of adult Asthma (COREA). EA was defined as asthmatics with the chronological age of 65 or more and eleven clinical variables measured at enrollment were used for PCA; symptom score, symptom duration, number of exacerbation during previous one year, smoking pack year, number of controller medications, body mass index, predicted % of FEV1, predicted % FVC, post-bronchodilator FEV1/FVC ratio, atopy index and number of eosinophils in peripheral blood.

RESULTS

PCA of all asthmatics showed that EA and NEA were distinctly separated by the first and second principal component on the plot of individual asthmatics according to their scores. For further analysis, we divided all asthmatics into the EA and the NEA group and performed PCA again in each group. The first four principal components with eigenvalues ≥ 1.0 were identified in both groups and they explained 55.5% of the variance in the EA group and 52.4% in the NEA group respectively. Clinical variables showed distinctly different patterns of loading on the first four principal components between the EA and the NEA group.

CONCLUSION

EA and NEA have different compositional patterns underlying their clinical variables. These observations helped in understanding the differences between EA and NEA from the integrated view covering various clinical aspects.