Comparison of Long-term Response and Remission to Omalizumab and Anti-IL-5/IL-5R Using Different Criteria in a Real-life Cohort of Severe Asthma Patients

Background: Evaluation of biologic therapy response is vital to monitor its effectiveness. Authors have proposed various response criteria including good responder, super-responder, non-responder, and clinical remission.ObjectivesTo ascertain the prevalence of response and clinical remission after long-term treatment (>6 months) of anti-IgE and anti-IL-5/IL-5Rα biologics, compare these results with existing criteria, and identify predictors for non-responders and clinical remission.MethodsA multicenter, real-life study involving severe asthma patients in Spain. Various outcomes were assessed to gauge response and clinical remission against established criteria.ResultsThe study included 429 patients, 209 (48.7%) omalizumab, 112 (26.1%) mepolizumab, 19 (4.4%) reslizumab and 89 (20.7%) benralizumab, with a mean treatment duration of 55.3±38.8 months. In the final year of treatment, 218 (50.8%) were super-responders, 173 (40.3%) responders, 38 (8.9%) non-responders, and clinical remission in 116 (27%), without differences among biologics. The short-term non-responders (<6 months) were 25/545 (4.6%). Substantial variations in response and clinical remission were observed when applying different published criteria. Predictors of non-response included higher BMI (OR:1.14; 95% CI:1.06–1.23; p<0.001), admissions at ICU (2.69; 1.30–5.56; p=0.01), high count of SAE (1.21; 1.03–1.42; p=0.02) before biologic treatment. High FEV1% (0.96; 0.95–0.98; p<0.001), a high ACT score (0.93; 0.88–0.99; p=0.01) before biologic treatment or NSAID-ERD (0.52; 0.29–0.91; p=0.02) showed strong associations with achieving clinical remission.ConclusionA substantial proportion of severe asthma patients treated long-term with omalizumab or anti-IL5/IL-5Rα achieved a good response. Differences in response criteria highlight the need for harmonization in defining response and clinical remission in biologic therapy to enable meaningful cross-study comparisons. (AU)

Comparison of Long-term Response and Remission to Omalizumab and Anti-IL-5/IL-5R Using Different Criteria in a Real-life Cohort of Severe Asthma Patients.

BACKGROUND: Evaluation of biologic therapy response is vital to monitor its effectiveness. Authors have proposed various response criteria including good responder, super-responder, non-responder, and clinical remission. OBJECTIVES: To ascertain the prevalence of response and clinical remission after long-term treatment (>6 months) of anti-IgE and anti-IL-5/IL-5Rα biologics, compare these results with existing criteria, and identify predictors for non-responders and clinical remission. METHODS: A multicenter, real-life study involving severe asthma patients in Spain. Various outcomes were assessed to gauge response and clinical remission against established criteria. RESULTS: The study included 429 patients, 209 (48.7%) omalizumab, 112 (26.1%) mepolizumab, 19 (4.4%) reslizumab and 89 (20.7%) benralizumab, with a mean treatment duration of 55.3±38.8 months. In the final year of treatment, 218 (50.8%) were super-responders, 173 (40.3%) responders, 38 (8.9%) non-responders, and clinical remission in 116 (27%), without differences among biologics. The short-term non-responders (<6 months) were 25/545 (4.6%). Substantial variations in response and clinical remission were observed when applying different published criteria. Predictors of non-response included higher BMI (OR:1.14; 95% CI:1.06-1.23; p<0.001), admissions at ICU (2.69; 1.30-5.56; p=0.01), high count of SAE (1.21; 1.03-1.42; p=0.02) before biologic treatment. High FEV1% (0.96; 0.95-0.98; p<0.001), a high ACT score (0.93; 0.88-0.99; p=0.01) before biologic treatment or NSAID-ERD (0.52; 0.29-0.91; p=0.02) showed strong associations with achieving clinical remission. CONCLUSION: A substantial proportion of severe asthma patients treated long-term with omalizumab or anti-IL5/IL-5Rα achieved a good response. Differences in response criteria highlight the need for harmonization in defining response and clinical remission in biologic therapy to enable meaningful cross-study comparisons.

Effect of Obesity on the Expression of Genes Associated with Severe Asthma-A Pilot Study.

Asthma is a complex condition resulting from the interaction of genes and environment. Obesity is a risk factor to develop asthma and contributes to poor response to asthma therapy and severity. The aim of the study was to evaluate the effect of obesity on the expression levels of genes previously associated with severe asthma. Three groups of subjects were studied: non-obese asthmatics (NOA), obese asthma patients (OA), and non-asthmatic obese subjects (O). Previously reported overexpressed (IL-10, MSR1, PHLDA1, SERPINB2, and CD86) and underexpressed genes (CHI3L1, CPA3, IL-8, and PI3) in severe asthma were analyzed by RT-qPCR in peripheral blood mononuclear cells (PBMCs). In the overexpressed genes, obesity significantly decreased the expression of MSR1 and PHLDA1 and had no effects on CD86, IL-10, and SERPINB2. In underexpressed genes, obesity did not affect PI3, CHI3L1, and IL-8 and significantly reduced CPA3 expression. The results of this study show that obesity should be included among the known factors that can contribute toward modifying the expression of genes associated with asthma and, in particular, severe asthma.

Disposition of Work-Related Asthma in a Spanish Asthma Cohort: Comparison of Asthma Severity Between Employed and Retired Workers.

BACKGROUND: Exposure to certain agents in the workplace can trigger occupational asthma or work-exacerbated asthma, both of which come under the heading of work-related asthma (WRA). Understanding the burden that WRA represents can help in the management of these patients. OBJECTIVE: To assess the influence of occupation on asthma in real life and analyze the characteristics of patients with WRA included in an asthma cohort. METHODS: This was a prospective multicenter study of a cohort of consecutive patients with asthma. A standardized clinical history was completed. Patients were classified as having WRA or non-WRA. All patients underwent respiratory function tests, FeNO test, and methacholine challenge (methacholine concentration that causes a 20% drop in FEV1) at the beginning of the study. They were classified into two groups, depending on their employment status: employed (group 1) or unemployed (group 2). RESULTS: Of the 480 patients included in the cohort, 82 (17%) received the diagnosis of WRA. Fifty-seven patients (70%) were still working. Mean age (SD) was 46 (10.69) years in group 1 and 57 (9.91) years in group 2 (P < .0001). Significant differences were observed in adherence to treatment (64.9% in group 1 vs 88% in group 2; P = .0354) and in severe asthma exacerbations (35.7% in group 1 vs 0% in group 2; P = .0172). No significant differences were observed in the rest of the variables analyzed. CONCLUSIONS: The burden of WRA in specialized asthma units is not negligible. The absence of differences in the severity of asthma, the treatment administered, alterations in lung function, and the number of exacerbations in those working versus not working may support the idea that advice regarding changing jobs should be customized for individual patients.

Characteristics and Management of Patients with Refractory or Unexplained Chronic Cough in Outpatient Hospital Clinics in Spain: A Retrospective Multicenter Study.

PURPOSE: Chronic cough (cough that persists for ≥ 8 weeks) can cause a range of physical symptoms and psychosocial effects that significantly impair patients' quality of life. Refractory chronic cough (RCC) and unexplained chronic cough (UCC) are challenging to diagnose and manage, with substantial economic implications for healthcare systems. METHODS: This retrospective multicenter non-interventional study aimed to characterize the profile and health resource consumption of patients with RCC or UCC who attended outpatient clinics at Spanish hospitals. Data were collected from medical records of patients with RCC or UCC for up to 3 years before study inclusion. RESULTS: The patient cohort (n = 196) was representative of the chronic cough population (77.6% female, mean age 58.5 years). Two-thirds of patients (n = 126) had RCC. The most frequently visited doctors were pulmonologists (93.4% of patients) and primary care physicians (78.6%), with a mean of 5 visits per patient over three years' observation. The most common diagnostic tests were chest x-ray (83.7%) and spirometry with bronchodilation (77.0%). The most commonly prescribed treatments were proton pump inhibitors (79.6%) and respiratory medications (87.8%). Antibiotics were prescribed empirically to 56 (28.6%) patients. Differences between RCC or UCC groups related mainly to approaches used to manage cough-associated conditions (gastroesophageal reflux disease, asthma) in patients with RCC. CONCLUSION: RCC and UCC are responsible for high health resource utilization in Spanish hospitals. Specific treatments targeting the pathological processes driving chronic cough may provide opportunities to reduce the associated burden for patients and healthcare systems.

Identification of Asthma Phenotypes in the Spanish MEGA Cohort Study Using Cluster Analysis

Introduction: The definition of asthma phenotypes has not been fully established, neither there are cluster studies showing homogeneous results to solidly establish clear phenotypes. The purpose of this study was to develop a classification algorithm based on unsupervised cluster analysis, identifying clusters that represent clinically relevant asthma phenotypes that may share asthma-related outcomes. Methods: We performed a multicentre prospective cohort study, including adult patients with asthma (N=512) from the MEGA study (Mechanisms underlying the Genesis and evolution of Asthma). A standardised clinical history was completed for each patient. Cluster analysis was performed using the kernel k-groups algorithm. Results: Four clusters were identified. Cluster 1 (31.5% of subjects) includes adult-onset atopic patients with better lung function, lower BMI, good asthma control, low ICS dose, and few exacerbations. Cluster 2 (23.6%) is made of adolescent-onset atopic asthma patients with normal lung function, but low adherence to treatment (59% well-controlled) and smokers (48%). Cluster 3 (17.1%) includes adult-onset patients, mostly severe non-atopic, with overweight, the worse lung function and asthma control, and receiving combination of treatments. Cluster 4 (26.7%) consists of the elderly-onset patients, mostly female, atopic (64%), with high BMI and normal lung function, prevalence of smokers and comorbidities. Conclusion: We defined four phenotypes of asthma using unsupervised cluster analysis. These clusters are clinically relevant and differ from each other as regards FEV1, age of onset, age, BMI, atopy, asthma severity, exacerbations, control, social class, smoking and nasal polyps. (AU)

Identification of Asthma Phenotypes in the Spanish MEGA Cohort Study Using Cluster Analysis.

INTRODUCTION: The definition of asthma phenotypes has not been fully established, neither there are cluster studies showing homogeneous results to solidly establish clear phenotypes. The purpose of this study was to develop a classification algorithm based on unsupervised cluster analysis, identifying clusters that represent clinically relevant asthma phenotypes that may share asthma-related outcomes. METHODS: We performed a multicentre prospective cohort study, including adult patients with asthma (N=512) from the MEGA study (Mechanisms underlying the Genesis and evolution of Asthma). A standardised clinical history was completed for each patient. Cluster analysis was performed using the kernel k-groups algorithm. RESULTS: Four clusters were identified. Cluster 1 (31.5% of subjects) includes adult-onset atopic patients with better lung function, lower BMI, good asthma control, low ICS dose, and few exacerbations. Cluster 2 (23.6%) is made of adolescent-onset atopic asthma patients with normal lung function, but low adherence to treatment (59% well-controlled) and smokers (48%). Cluster 3 (17.1%) includes adult-onset patients, mostly severe non-atopic, with overweight, the worse lung function and asthma control, and receiving combination of treatments. Cluster 4 (26.7%) consists of the elderly-onset patients, mostly female, atopic (64%), with high BMI and normal lung function, prevalence of smokers and comorbidities. CONCLUSION: We defined four phenotypes of asthma using unsupervised cluster analysis. These clusters are clinically relevant and differ from each other as regards FEV1, age of onset, age, BMI, atopy, asthma severity, exacerbations, control, social class, smoking and nasal polyps.

Analysis of Differentially Expressed MicroRNAs in Serum and Lung Tissues from Individuals with Severe Asthma Treated with Oral Glucocorticoids.

Nowadays, microRNAs (miRNAs) are increasingly used as biomarkers due to their potential contribution to the diagnosis and targeted treatment of a range of diseases. The aim of the study was to analyze the miRNA expression profiles in serum and lung tissue from patients with severe asthma treated with oral corticosteroids (OCS) and those without OCS treatment. For this purpose, serum and lung tissue miRNAs of OCS and non-OCS asthmatic individuals were evaluated by miRNAs-Seq, and subsequently miRNA validation was performed using RT-qPCR. Additionally, pathway enrichment analysis of deregulated miRNAs was conducted. We observed altered expression by the next-generation sequencing (NGS) of 11 miRNAs in serum, of which five (hsa-miR-148b-3p, hsa-miR-221-5p, hsa-miR-618, hsa-miR-941, and hsa-miR-769-5p) were validated by RT-qPCR, and three miRNAs in lung tissue (hsa-miR-144-3p, hsa-miR-144-5p, and hsa-miR-451a). The best multivariate logistic regression model to differentiate individuals with severe asthma, treated and untreated with OCS, was to combine the serum miRNAs hsa-miR-221-5p and hsa-miR-769-5p. Expression of hsa-miR-148b-3p and hsa-miR-221-5p correlated with FEV1/FVC (%) and these altered miRNAs act in key signaling pathways for asthma disease and the regulated expression of some genes (FOXO3, PTEN, and MAPK3) involved in these pathways. In conclusion, there are miRNA profiles differentially expressed in OCS-treated individuals with asthma and could be used as biomarkers of OCS treatment.

How reliably can algorithms identify eosinophilic asthma phenotypes using non-invasive biomarkers?

Background and Aims: Asthma is a heterogeneous respiratory disease that encompasses different inflammatory and functional endophenotypes. Many non-invasive biomarkers has been investigated to its pathobiology. Heany et al proposed a clinical algorithm that classifies severe asthmatic patients into likely-eosinophilic phenotypes, based on accessible biomarkers: PBE, current treatment, FeNO, presence of nasal polyps (NP) and age of onset. Materials and Methods: We assessed the concordance between the algorithm proposed by Heany et al. with sputum examination, the gold standard, in 145 asthmatic patients of the MEGA cohort with varying grades of severity. Results: No correlation was found between both classifications 0.025 (CI = 0.013-0.037). Moreover, no relationship was found between sputum eosinophilia and peripheral blood eosinophilia count in the total studied population. Discussion and Conclusion: In conclusion, our results suggest that grouping the biomarkers proposed by Heany et al. are insufficient to diagnose eosinophilic phenotypes in asthmatic patients. Sputum analysis remains the gold standard to assess airway inflammation.

Differences in Inflammatory Cytokine Profile in Obesity-Associated Asthma: Effects of Weight Loss.

Obesity and asthma are associated with systemic inflammation maintained by mediators released by adipose tissue and lung. This study investigated the inflammatory serum mediator profile in obese subjects (O) (n = 35), non-obese asthma (NOA) patients (n = 14), obese asthmatics (OA) (n = 21) and healthy controls (HC) (n = 33). The effect of weight loss after bariatric surgery (BS) was examined in 10 OA and 31 O subjects. We analyzed serum markers including leptin, adiponectin, TGF-ß1, TNFR2, MCP-1, ezrin, YKL-40, ST2, IL-5, IL-9, and IL-18. Compared with HC subjects, the O group showed increased levels of leptin, TGF-ß1, TNFR2, MCP-1, ezrin, YKL-40, and ST2; the OA group presented increased levels of MCP-1, ezrin, YKL-40, and IL-18, and the NOA group had increased levels of ezrin, YKL-40, IL-5, and IL-18. The higher adiponectin/leptin ratio in NOA with respect to OA subjects was the only significant difference between the two groups. IL-9 was the only cytokine with significantly higher levels in OA with respect to O subjects. TNFR2, ezrin, MCP-1, and IL-18 concentrations significantly decreased in O subjects after BS. O, OA, and NOA showed distinct patterns of systemic inflammation. Leptin and adiponectin are regulated in asthma by obesity-dependent and -independent mechanisms. Combination of asthma and obesity does not result in significant additive effects on circulating cytokine levels.

Reference Gene Validation for RT-qPCR in PBMCs from Asthmatic Patients with or without Obesity.

Obesity is known to impair the efficacy of glucocorticoid medications for asthma control. Glucocorticoid-induced gene expression studies may be useful to discriminate those obese asthmatic patients who present a poor response to glucocorticoids. The expression of genes of interest is normalized with respect to reference genes (RGs). Ideally, RGs have a stable expression in different samples and are not affected by experimental conditions. The objective of this work was to analyze suitable RGs to study the role of glucocorticoid-induced genes in obese asthmatic patients in further research. The gene expression of eight potential RGs (GUSB, B2M, POLR2A, PPIA, ACTB, GAPDH, HPRT1, and TBP) was assessed with reverse transcription-quantitative polymerase chain reaction in peripheral blood mononuclear cells (PBMCs) from asthmatic, obese asthmatic, and healthy individuals. Their stability was analyzed using four different algorithms-BestKeeper, ΔCt, geNorm, and NormFinder. geNorm analysis recommended the use of a minimum of three genes for normalization. Moreover, intergroup variation due to the treatment was calculated by NormFinder, which found that B2M was the gene that was least affected by different treatments. Comprehensive rankings indicated GUSB and HPRT1 as the best RGs for qPCR in PBMCs from healthy and asthmatic subjects, while B2M and PPIA were the best for obese asthmatic subjects. Finally, our results demonstrated that B2M and HPRT1 were the most stable RGs among all groups, whereas ACTB, TBP, and GAPDH were the worst shared ones.

A New and More Sensitive Method to Integrate the Desaturation Distance Ratio During a 6-Minute Walking Test in Chronic Respiratory Diseases: Physiological Correlates / Un método nuevo y más sensible para integrar la relación entre distancia y desaturación durante la prueba de la marcha de seis minutos en las enfermedades respiratorias crónicas: correlaciones fisiológicas

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Challenges for asthma units in response to COVID-19: a qualitative group dynamics analysis.

OBJECTIVE: To develop a set of recommendations for the management of severe asthma during COVID-19 pandemic. METHODS: Eleven pneumologists and allergologists who were staff members of officially accredited asthma units in Catalonia (Spain) participated in a cross-section study based on three 2-hour virtual workshops (first: brainstorming, second: identification of impacts and challenges summarized in 10 topics, third: establishment of final recommendations by consensus). RESULTS: Impacts and challenges identified were improvement of referral protocols between different levels of care; assessment of the minimum number of function tests to be performed and promote the performance of spirometry in primary care; implementation of videoconferencing, mobile apps, telephone calls, or integral virtual platforms for the follow-up of patients, and definition of the model of care (face-to-face, telematics, mixed) according to the patient's individual needs; self-administration of biologics for domiciliary treatment; and empowerment of the role of nursing and hospital pharmacy in particular for follow-up and self-administration of biologics. The main recommendations included coordination between primary care and specialized care consultation, optimization of lung function testing, implementation of telemedicine, and the role of nursing and hospital pharmacy. CONCLUSION: The specific proposals in response to the effect of COVID-19 pandemic focused on four areas of interest (coordination between primary care and specialized care, optimization of lung function testing, implementation of telemedicine, and empowerment of the role of nursing and hospital pharmacy) may be generalized to other health care settings, and help to introduce new ways of caring asthma patients in the COVID-19 context.