Suboptimally controlled asthma in patients treated with inhaled ICS/LABA: prevalence, risk factors, and outcomes

Predictive parameters of uncontrolled asthma in the real world: a prospective study

BACKGROUND

The ultimate goal of asthma management is to have complete control of the condition, yet the number of patients with uncontrolled asthma continues to rise. This study aims to determine the prevalence of uncontrolled asthma, identify predictive parameters, and compare MART and non-MART treatment regimes.

METHODS

A prospective questionnaire was administered to 495 patients who signed the consent form. According to the scores obtained from the Asthma control test (ACT), patients were grouped into Group 1 (ACT score ≤ 19): Uncontrolled Asthma and Group 2 (ACT score > 19): Well-Controlled Asthma. Treatment adherence was evaluated by using the Morisky Medication Adherence Scale (MMAS).

RESULTS

The proportion of patients with uncontrolled asthma was found to be 54.9%. Effective predictors of uncontrolled asthma were female gender (OR = 1.7, 95% CI 1.1-2.7, p = 0.023), FEV1/FVC%<93% (OR = 2.5, 95% CI 1.5-4.1, p < 0.001), a history of visits to the emergency department during the previous year (OR = 2.7, 95% CI 1.7-4.3, p < 0.001), and receiving non-MART treatment (OR = 2.0, 95% CI 1.3-3.1, p = 0.001). MMAS was found to be higher, and medication adherence lower, in uncontrolled asthma patients (p = 0.040). The MART treatment regimen was preferred in 36% of cases. In the MART treatment group, as compared to the non-MART treatment group, uncontrolled asthma (43.8% vs. 61.2%) was observed according to ACT (p < 0.001).

CONCLUSION

The risk of uncontrolled asthma was found to be higher in female patients, or those who had visited the emergency department, had been hospitalized within the past year, had poor pulmonary function test results or low treatment compliance, and who were on non-MART treatment regimens.

Real-life effectiveness of once-daily single-inhaler triple therapy (FF-UMEC-VI) after switching from dual therapy (ICS-LABA) in patients with symptomatic asthma: trelegy ellipta for real asthma control study

Introduction

A well-designed, protocol-driven randomized controlled trial (RCT) has demonstrated the efficacy of fluticasone furoate-umeclidinium-vilanterol (FF-UMEC-VI) in patients with asthma, but there is a lack of real-world data that can be used to translate the results of the RCT into clinical practice. This study evaluated the efficacy of switching the therapy from inhaled corticosteroid-long-acting β2-agonists (ICS-LABAs) to FF-UMEC-VI at the equivalent corticosteroid dose in a real-world setting.

Methods

A prospective, three-month, open-label, parallel-group, switching therapy trial was performed in patients with symptomatic asthma under routine management. Patients receiving low-to-medium doses of ICS-LABAs were switched to FF-UMEC-VI (100-62.5-25 µg, once daily) (T100 group), and patients receiving a high dose of ICS-LABAs were switched to FF-UMEC-VI (200-62.5-25 µg, once daily) (T200 group). The primary outcome was the change from baseline in forced expiratory volume in 1 s (ΔFEV1) at week 12, and the secondary outcomes were the improvement in fractional exhaled nitric oxide (FeNO), the asthma symptoms evaluated using the asthma control test (ACT), and the cough severity evaluated using the visual analog scale (VAS).

Results

Thirty-five patients were switched to T100, and thirty patients were switched to T200. The ΔFEV1 was improved by more than 100 ml at 8 weeks after switching in both groups (T100, 110.4 ± 39.8 ml; T200, 117.1 ± 39.8 ml) (p < 0.05) but slightly decreased at 12 weeks. ACT also improved by more than 3 points at 8 weeks after switching and was maintained to 12 weeks in both groups (p < 0.05). Patients with ACT scores of <20 (i.e., poor control) before switching showed a greater improvement in the symptoms during T100 therapy, and 92% had reached an ACT score of >20 (i.e., good control). FeNO in the T100 group was decreased at 4 weeks (p < 0.05). Cough VAS also significantly decreased but did not reach a minimal clinically important difference.

Conclusions

In patients with symptomatic asthma showing insufficient control, an improvement in the asthma symptoms was observed after switching to FF-UMEC-VI at the equivalent corticosteroid dose, accompanied by an improvement in FEV1.

Medicare Advantage Population in the United States: Outcomes of Patients with Asthma Treated with ICS/LABA Before and After Initiation with Fluticasone Furoate/Umeclidinium/Vilanterol (FF/UMEC/VI)

INTRODUCTION

The clinical benefits of fluticasone furoate/umeclidinium/vilanterol (FF/UMEC/VI) have been demonstrated in clinical trials. There is limited evidence regarding the effectiveness and economic outcomes associated with FF/UMEC/VI use in US clinical practice. This real-world study assessed asthma-related exacerbations, healthcare resource utilization (HRU), and healthcare costs among a Medicare Advantage-insured population before and after initiation of FF/UMEC/VI in patients with asthma previously treated with an inhaled corticosteroid/long-acting β2-agonist (ICS/LABA).

METHODS

De-identified data were obtained from the Komodo Health database (01/01/2016-12/31/2023) for adults with asthma who received prior ICS/LABA treatment and had ≥ 12 months of continuous Medicare Advantage coverage both pre- and post-FF/UMEC/VI initiation (index date). Rates of asthma-related exacerbations and HRU were compared using rate ratios (RR) from Poisson regressions. Healthcare costs were calculated per patient per year (PPPY) and compared using mean cost differences from generalized linear models.

RESULTS

In total, 2598 Medicare Advantage-insured patients who initiated FF/UMEC/VI for asthma were included. The mean ± SD age was 67.9 ± 12.3 years; 75.5% were female. The rate of overall asthma-related exacerbations was 31% lower in the post- versus pre-initiation period (RR 0.69; 95% CI 0.65, 0.73; p < 0.001) and included a 24% lower rate of inpatient/emergency department (IP/ED)-defined exacerbations (RR 0.76; 95% CI 0.68, 0.85; p < 0.001) and a 34% lower rate of systemic corticosteroid (SCS)-defined exacerbations (RR 0.66; 95% CI 0.61, 0.71; p < 0.001). Asthma-related ED visits (RR 0.69; 95% CI 0.60, 0.80; p < 0.001) and asthma-related outpatient (OP) visits (RR 0.77; 95% CI 0.71, 0.84; p < 0.001) were both lower, and the mean reduction in cost was $411 PPPY (95% CI $575, $248; p < 0.001), after FF/UMEC/VI initiation.

CONCLUSIONS

Initiation of FF/UMEC/VI after ICS/LABA treatment among Medicare Advantage-insured patients with asthma was associated with reduced rates of asthma-related exacerbations, ED and OP visits, and healthcare costs, highlighting the benefits of therapy escalation among this patient population.

The need for implementing a standardized, evidence-based emergency department discharge plan for optimizing adult asthma patient outcomes in the UAE, expert meeting report

BACKGROUND

Asthma is a common chronic respiratory inflammatory disease that adversely affects patients' quality of life (QoL) and overall well-being. When asthma is not adequately controlled, there is a higher risk of exacerbations and hospitalizations, thereby increasing the direct and indirect costs associated with the treatment and productivity loss. Overreliance on SABA and underutilization of ICS in the management of asthma can result in suboptimal treatment and poor asthma control. Patients who visit the emergency department are more likely to have poorly controlled asthma. Ensuring that these patients are provided with an evidence-based treatment plan during discharge can help reduce the risk of future exacerbations and consequently reduce the burden on the UAE healthcare system.

METHODS

A joint task force comprising experts from the Emirates Society of Emergency Medicine (ESEM) and Emirates Thoracic Society (ETS) reviewed published evidence and updated guidelines in asthma management to optimize the post-discharge recommendations.

RESULTS

The ESEM-ETS experts' joint task force has developed a step-by-step plan for emergency department/hospital discharge, which is based on the GINA 2023 guideline recommendations and the medications available in the UAE. By adhering to this structured plan, emergency department physicians can play a crucial role in improving asthma care, long-term patient outcomes, and the utilization of healthcare resources.

CONCLUSIONS

Prioritizing patient education and ensuring patients are equipped with the best-suited asthma treatment plans prior to discharge can help ED physicians improve patient outcomes and reduce healthcare resource utilization in UAE hospitals.

A Roadmap for Using Causal Inference and Machine Learning to Personalize Asthma Medication Selection

Inhaled corticosteroid (ICS) is a mainstay treatment for controlling asthma and preventing exacerbations in patients with persistent asthma. Many types of ICS drugs are used, either alone or in combination with other controller medications. Despite the widespread use of ICSs, asthma control remains suboptimal in many people with asthma. Suboptimal control leads to recurrent exacerbations, causes frequent ER visits and inpatient stays, and is due to multiple factors. One such factor is the inappropriate ICS choice for the patient. While many interventions targeting other factors exist, less attention is given to inappropriate ICS choice. Asthma is a heterogeneous disease with variable underlying inflammations and biomarkers. Up to 50% of people with asthma exhibit some degree of resistance or insensitivity to certain ICSs due to genetic variations in ICS metabolizing enzymes, leading to variable responses to ICSs. Yet, ICS choice, especially in the primary care setting, is often not tailored to the patient's characteristics. Instead, ICS choice is largely by trial and error and often dictated by insurance reimbursement, organizational prescribing policies, or cost, leading to a one-size-fits-all approach with many patients not achieving optimal control. There is a pressing need for a decision support tool that can predict an effective ICS at the point of care and guide providers to select the ICS that will most likely and quickly ease patient symptoms and improve asthma control. To date, no such tool exists. Predicting which patient will respond well to which ICS is the first step toward developing such a tool. However, no study has predicted ICS response, forming a gap. While the biologic heterogeneity of asthma is vast, few, if any, biomarkers and genotypes can be used to systematically profile all patients with asthma and predict ICS response. As endotyping or genotyping all patients is infeasible, readily available electronic health record data collected during clinical care offer a low-cost, reliable, and more holistic way to profile all patients. In this paper, we point out the need for developing a decision support tool to guide ICS selection and the gap in fulfilling the need. Then we outline an approach to close this gap via creating a machine learning model and applying causal inference to predict a patient's ICS response in the next year based on the patient's characteristics. The model uses electronic health record data to characterize all patients and extract patterns that could mirror endotype or genotype. This paper supplies a roadmap for future research, with the eventual goal of shifting asthma care from one-size-fits-all to personalized care, improve outcomes, and save health care resources.