Identification and management of adults with asthma prone to exacerbations: can we do better?

Severity of adult-onset asthma - a matter of blood neutrophils and severe obesity

BACKGROUND

Adult-onset asthma is associated with a poor treatment response. The aim was to study associations between clinical characteristics, asthma control and treatment in adult-onset asthma.

METHODS

Previous participants within the population-based Obstructive Lung Disease in Northern Sweden studies (OLIN) were in 2019-2020 invited to clinical examinations including structured interviews, spirometry, fractional exhaled nitric oxide (FeNO), skin prick test and blood sampling. In total, n = 251 individuals with adult-onset asthma (debut >15 years of age) were identified. Uncontrolled asthma was defined according to ERS/ATS and treatment step according to GINA (2019).

RESULTS

Among individuals with uncontrolled asthma (34%), severe obesity (16.3% vs 7.9%, p = 0.041) and elevated levels of blood neutrophils, both regarding mean level of blood neutrophils (4.25*109/L vs 3.67*109/L, p = 0.003), and proportions with ≥4*109/L (49.4% vs 33.3%, p = 0.017) and ≥5*109/L (32.1% vs 13.7%, p < 0.001) were more common than among those with controlled asthma. Adding the dimension of GINA treatment step 1-5, individuals with uncontrolled asthma on step 4-5 treatment had the highest proportions of blood neutrophils ≥5*109/L (45.5%), severe obesity (BMI≥35, 26.1%), dyspnea (mMRC≥2) (34.8%), and most impaired lung function in terms of FEV1%<80% of predicted (42.9%), FEV1

CONCLUSION

This study indicates that in adult-onset asthma, primarily non-type-2 characteristics such as obesity and blood neutrophils associate with poor asthma control and higher doses of inhaled corticosteroids.

Collapse

Key Words

• Body mass index
• Eosinophils
• Epidemiology
• Follow-up studies
• Neutrophils
• Sweden

Collapse

MESH Headings

• Humans
• Adult
• Neutrophils
• Obesity, Morbid/complications
• Nitric Oxide/therapeutic use
• Asthma/drug therapy
• Eosinophils
• Obesity/complications

Collapse

Grants Collapse

Affiliation(s)

Sofia Winsa-Lindmark Umeå University, Department of Public Health and Clinical Medicine, Section for Sustainable Health/The OLIN Unit, Sweden.
Caroline Stridsman Umeå University, Department of Public Health and Clinical Medicine, The OLIN Unit, Sweden
Axel Sahlin Umeå University, Department of Public Health and Clinical Medicine, Section for Sustainable Health/The OLIN Unit, Sweden
Linnea Hedman Umeå University, Department of Public Health and Clinical Medicine, Section for Sustainable Health/The OLIN Unit, Sweden
Nikolai Stenfors Umeå University, Department of Public Health and Clinical Medicine, The OLIN Unit, Sweden
Tomi Myrberg Umeå University, Department of Surgical and Perioperative Sciences, Anesthesiology and Intensive Care Medicine, Sweden
Anne Lindberg Umeå University, Department of Public Health and Clinical Medicine, The OLIN Unit, Sweden
Eva Rönmark Umeå University, Department of Public Health and Clinical Medicine, Section for Sustainable Health/The OLIN Unit, Sweden
Helena Backman Umeå University, Department of Public Health and Clinical Medicine, Section for Sustainable Health/The OLIN Unit, Sweden

Collapse

High ACT score is not sufficient to reduce the risk of asthma exacerbations in asthma with low lung function

BACKGROUND

Low forced expiratory volume in 1 s (FEV₁) is a risk factor for asthma exacerbations (AEs). We aimed to determine if asthma control could reduce the future risk of AEs in patients with low FEV₁. This study was conducted to evaluate the future risks of AEs within six months according to Asthma Control Test™ (ACT) score and FEV₁.

METHODS

A total of 565 patients with asthma were enrolled from the COREA cohort. The ACT score, lung function test, and number of AEs were assessed at baseline, three-month follow-up, and six-month follow-up with conventional asthma treatments by asthma specialists in real clinical settings.

RESULTS

Female sex, low ACT score, low FEV₁, low FVC, and AE history in the previous three months were related with increased AEs within six months. AEs during six-month follow-up occurred in 24% of patients with ACT <20 and FEV₁ < 60% at baseline. Among patients with an ACT score ≥20, 3.4% of patients with an FEV₁ < 2.16 L and 9.8% of patients with FEV₁ ≥ 2.16 L had experienced AEs (P = 0.01), although no differences were observed in the presence of AEs within six months according to the predicted FEV₁ (FEV₁ ≥ 60% vs. FEV₁ < 60%, 5.66% vs. 8.51%, P = 0.65).

CONCLUSION

Patient with low FEV₁ seemed to show higher risk of AEs than those with near-normal FEV₁ despite ACT score ≥20 and asthma treatments. Therefore, treatment strategies that prevent AEs are needed in high-risk asthmatic patients.

Pathogenesis of COPD and Asthma

Asthma and COPD remain two diseases of the respiratory tract with unmet medical needs. This review considers the current state of play with respect to what is known about the underlying pathogenesis of these two chronic inflammatory diseases of the lung. The review highlights why they are different conditions requiring different approaches to treatment and provides a backdrop for the subsequent chapters in this volume discussing recent advances in the pharmacology and treatment of asthma and COPD.

Machine learning approaches to personalize early prediction of asthma exacerbations

Patient telemonitoring results in an aggregation of significant amounts of information about patient disease trajectory. However, the potential use of this information for early prediction of exacerbations in adult asthma patients has not been systematically evaluated. The aim of this study was to explore the utility of telemonitoring data for building machine learning algorithms that predict asthma exacerbations before they occur. The study dataset comprised daily self-monitoring reports consisting of 7001 records submitted by adult asthma patients during home telemonitoring. Predictive modeling included preparation of stratified training datasets, predictive feature selection, and evaluation of resulting classifiers. Using a 7-day window, a naive Bayesian classifier, adaptive Bayesian network, and support vector machines were able to predict asthma exacerbation occurring on day 8, with sensitivity of 0.80, 1.00, and 0.84; specificity of 0.77, 1.00, and 0.80; and accuracy of 0.77, 1.00, and 0.80, respectively. Our study demonstrated that machine learning techniques have significant potential in developing personalized decision support for chronic disease telemonitoring systems. Future studies may benefit from a comprehensive predictive framework that combines telemonitoring data with other factors affecting the likelihood of developing acute exacerbation. Approaches implemented for advanced asthma exacerbation prediction may be extended to prediction of exacerbations in patients with other chronic health conditions.

Identifying patients at risk for severe exacerbations of asthma: development and external validation of a multivariable prediction model

BACKGROUND

Preventing exacerbations of asthma is a major goal in current guidelines. We aimed to develop a prediction model enabling practitioners to identify patients at risk of severe exacerbations who could potentially benefit from a change in management.

METHODS

We used data from a 12-month primary care pragmatic trial; candidate predictors were identified from GINA 2014 and selected with a multivariable bootstrapping procedure. Three models were constructed, based on: (1) history, (2) history+spirometry and (3) history+spirometry+FeNO. Final models were corrected for overoptimism by shrinking the regression coefficients; predictive performance was assessed by the area under the receiver operating characteristic curve (AUROC) and Hosmer-Lemeshow test. Models were externally validated in a data set including patients with severe asthma (Unbiased BIOmarkers in PREDiction of respiratory disease outcomes).

RESULTS

80/611 (13.1%) participants experienced ≥1 severe exacerbation. Five predictors (Asthma Control Questionnaire score, current smoking, chronic sinusitis, previous hospital admission for asthma and ≥1 severe exacerbation in the previous year) were retained in the history model (AUROC 0.77 (95% CI 0.75 to 0.80); Hosmer-Lemeshow p value 0.35). Adding spirometry and FeNO subsequently improved discrimination slightly (AUROC 0.79 (95% CI 0.77 to 0.81) and 0.80 (95% CI 0.78 to 0.81), respectively). External validation yielded AUROCs of 0.69 (95% CI 0.63 to 0.75; 0.63 to 0.75 and 0.63 to 0.75) for the three models, respectively; calibration was best for the spirometry ­model.

CONCLUSIONS

A simple history-based model extended with spirometry identifies patients who are prone to asthma exacerbations. The additional value of FeNO is modest. These models merit an implementation study in clinical practice to assess their utility.

TRIAL REGISTRATION NUMBER

NTR 1756.

Predicting frequent asthma exacerbations using blood eosinophil count and other patient data routinely available in clinical practice

PURPOSE

Acute, severe asthma exacerbations can be difficult to predict and thus prevent. Patients who have frequent exacerbations are of particular concern. Practical exacerbation predictors are needed for these patients in the primary-care setting.

PATIENTS AND METHODS

Medical records of 130,547 asthma patients aged 12-80 years from the UK Optimum Patient Care Research Database and Clinical Practice Research Datalink, 1990-2013, were examined for 1 year before (baseline) and 1 year after (outcome) their most recent blood eosinophil count. Baseline variables predictive (P<0.05) of exacerbation in the outcome year were compared between patients who had two or more exacerbations and those who had no exacerbation or only one exacerbation, using uni- and multivariable logistic regression models. Exacerbation was defined as asthma-related hospital attendance/admission (emergency or inpatient) or acute oral corticosteroid (OCS) course.

RESULTS

Blood eosinophil count >400/µL (versus ≤400/µL) increased the likelihood of two or more exacerbations >1.4-fold (odds ratio [OR]: 1.48 (95% confidence interval [CI]: 1.39, 1.58); P<0.001). Variables that significantly increased the odds by up to 1.4-fold included increasing age (per year), female gender (versus male), being overweight or obese (versus normal body mass index), being a smoker (versus nonsmoker), having anxiety/depression, diabetes, eczema, gastroesophageal reflux disease, or rhinitis, and prescription for acetaminophen or nonsteroidal anti-inflammatory drugs. Compared with treatment at British Thoracic Society step 2 (daily controller ± reliever), treatment at step 0 (none) or 1 (as-needed reliever) increased the odds by 1.2- and 1.6-fold, respectively, and treatment at step 3, 4, or 5 increased the odds by 1.3-, 1.9-, or 3.1-fold, respectively (all P<0.05). Acute OCS use was the single best predictor of two or more exacerbations. Even one course increased the odds by more than threefold (OR: 3.75 [95% CI: 3.50, 4.01]; P<0.001), and three or more courses increased the odds by >25-fold (OR: 25.7 [95% CI: 23.9, 27.6]; P<0.001).

CONCLUSION

Blood eosinophil count and several other variables routinely available in patient records may be used to predict frequent asthma exacerbations.

The Clinical and Health Economic Value of Clinical Laboratory Diagnostics

The ultimate goal of diagnostic testing is to guide disease management in order to improve patient outcomes and patient well-being. Patient populations are rarely homogenous and accurate diagnostic tests can dissect the patient population and identify those patients with similar symptoms but very different underlying pathophysiology that will respond differently to different treatments. This stratification of patients can direct patients to appropriate treatment and is likely to result in clinical benefits for patients and economic benefits for the healthcare system. In this article we look at the clinical and economic benefits afforded by clinical laboratory diagnostics in three disease areas that represent substantial clinical and healthcare burdens to society; heart failure, Alzheimer's disease and asthma.

Clinical burden and predictors of asthma exacerbations in patients on guideline-based steps 4-6 asthma therapy in the TENOR cohort

BACKGROUND

Patients with severe or difficult-to-treat asthma on guideline-recommended Steps 4/5/6 therapy have not previously been described.

OBJECTIVE

To characterize patients with severe or difficult-to-treat asthma on Steps 4/5/6 therapy and assess predictors of future asthma exacerbations.

METHODS

Patients ages ≥12 years with baseline and month 12 medication data were assigned to Steps 4/5/6 care levels from the 2007 National Heart, Lung, and Blood Institute guidelines. Demographic, atopic, and clinical characteristics at baseline and month 12 were assessed by using descriptive statistics. Asthma-related quality of life was assessed by using the Mini Asthma Quality of Life Questionnaire, and work and activity impairment was assessed by the Work Productivity and Activity Impairment Questionnaire-Asthma. Odds ratios (OR) and 95% CI for asthma exacerbation risk at month 12 were generated by using multivariable logistic regression.

RESULTS

A total of 1186 patients were included. More than two-thirds of the patients (67.4%) were on ≥3 long-term controllers, and 55.1% were considered difficult to treat due to frequent exacerbations. Patients reported low asthma-related quality of life scores and considerable impairment in overall work and daily activity (21.4% and 32.1%, respectively). After adjustment for covariates, exacerbation history (hospitalization, OR 6.27 [95% CI, 3.61-10.88]; emergency department visit, OR 3.84 [95% CI, 2.50-5.91]; corticosteroid burst, OR 2.89 [95% CI, 2.18-3.82]) and very poorly controlled asthma (OR 1.95 [95% CI, 1.41-2.71] vs not well controlled) were independently associated with risk of a future exacerbation (all P < .001).

CONCLUSION

Despite multiple long-term controller medications, patients with severe or difficult-to-treat asthma on Steps 4/5/6 therapy present with significant clinical burden and risk of future asthma exacerbations.

[Asthma: treatment of exacerbations]

INTRODUCTION

Exacerbations remain, in both adults and children, a common reason for emergency consultation. The management of the asthmatic patient with an acute exacerbation is well defined.

BACKGROUND

The initial evaluation, based on the background risk factors and the clinical examination, will determine the choice of treatment and management. Treatment is based on bronchodilators and corticosteroids in the majority of cases.

VIEWPOINTS

An episode of exacerbation may be the opportunity to establish contact with the patient (an educational approach) to improve the adherence to long-term treatment with inhaled corticosteroids, which remain the best way of preventing future exacerbations.

CONCLUSION

Early and appropriate management of exacerbations of asthma should reduce asthma morbidity and mortality. It could also reduce the socioeconomic costs of these episodes and the number and duration of hospital admissions.

Asthma phenotypes in adults and clinical implications

It is becoming increasingly recognized that asthma is a heterogeneous disease, whether based on clinical factors, including the patient's age at diagnosis, symptom spectrum and treatment response, triggering factors, or the level and type of inflammation. Attempts to analyze the importance of these characteristics to the clinical presentation of asthma have led to the appreciation of numerous separate and overlapping asthma phenotypes. However, these approaches are 'biased' and based on the clinician/scientist's own experience. Recently, unbiased approaches have also been attempted using both molecular and statistical tools. Early results from these approaches have supported and expanded on the clinician's concepts. However, until specific biologic markers are identified for any of these proposed phenotypes, the definitive nature of any phenotype will remain speculative.

Measuring exacerbations in obstructive lung disease

PURPOSE

Using hospitalization always has been seen as a solid measurement for exacerbation in pharmacoepidemiology, but might lead to an underestimation of disease exacerbation because of a trend towards outpatient care. The aim of this study was to quantify the incidence of different exacerbation markers in obstructive lung disease and to identify predictors for these exacerbation markers.

METHODS

We conducted a cohort study using the PHARMO record linkage system, including demographic details and complete medication histories of more than two million community-dwelling residents in the Netherlands from 1985 onwards. Eligible patients were adult users of inhaled corticosteroids (ICS). Outcome parameters were hospitalization and short courses of systemic corticosteroids. Patients were allowed to have multiple exacerbations during follow-up.

RESULTS

We identified 5327 patients. During follow-up, 8635 exacerbations occurred in 2332 patients with a trend in time towards treating exacerbations out of the hospital (p-value 0.003). Of all patients with exacerbations, 73% was not hospitalized during follow-up. Exacerbations were associated with high-dose ICS use (adjusted RR 1.4; 95% CI 1.2-1.7) and chronic systemic corticosteroid use (adjusted RR 1.9; 95%CI 1.6-2.2).

CONCLUSIONS

Using hospitalization only as exacerbation marker leads to underestimating the exacerbation rate, because of exacerbation treatment out of the hospital. Patients with obstructive lung disease using chronic systemic corticosteroids or high-dose ICS use are more prone to exacerbations. This implies that these patients should be monitored carefully to prevent recurrent exacerbations which are detrimental for their prognosis and quality of life.

Medication changes prior to hospitalization for obstructive lung disease: a case-crossover study

BACKGROUND

Hospitalizations have always been seen as a solid outcome parameter in pharmacoepidemiology. However, the period leading to hospitalization and prehospital management of the patient are equally important.

OBJECTIVE

To evaluate medication changes in the period prior to hospitalization for obstructive lung disease and to quantify the association between medication use and the risk of hospitalization.

METHODS

We conducted a case-crossover study using the PHARMO record linkage system, which contains drug dispensing data from community pharmacies and hospital admission data. Patients included in the study were adults hospitalized for obstructive lung disease between 2005 and 2007. The index date of the case period was the date of hospitalization, and control moments were set at 3, 6, 9, and 12 months before admission. For each patient, all prescriptions prior to the date of hospitalization were identified. Medication use was ascertained in a 90-day time window prior to each case or control moment.

RESULTS

We identified 1481 patients who were hospitalized for obstructive lung disease. It appeared that respiratory medication use increased in the 90 days prior to hospitalization. Hospitalization was associated with the use of 3 or more respiratory drugs (OR 2.2; 95% CI 1.8 to 2.8), systemic glucocorticoids (OR 4.5; 95% CI 3.8 to 5.4), and antibiotics (OR 3.1; 95% CI 2.7 to 3.6).

CONCLUSIONS

The use of systemic glucocorticoids, antibiotics, and other respiratory drugs increased prior to hospitalization for obstructive lung disease. These results could be indicative of the development and/or treatment of an exacerbation. There is a need for markers to detect exacerbations in an early phase in order to start treatment as early as possible and possibly prevent hospitalizations for obstructive lung disease.