ORCID Profile
0000-0002-7403-3871
Current Organisation
University of Leeds
Does something not look right? The information on this page has been harvested from data sources that may not be up to date. We continue to work with information providers to improve coverage and quality. To report an issue, use the Feedback Form.
Publisher: Oxford University Press (OUP)
Date: 06-2018
Publisher: Wiley
Date: 13-06-2022
DOI: 10.1111/ALL.15371
Abstract: Different treatments exist for allergic rhinitis (AR), including pharmacotherapy and allergen immunotherapy (AIT), but they have not been compared using direct patient data (i.e., “real‐world data”). We aimed to compare AR pharmacological treatments on (i) daily symptoms, (ii) frequency of use in co‐medication, (iii) visual analogue scales (VASs) on allergy symptom control considering the minimal important difference (MID) and (iv) the effect of AIT. We assessed the MASK‐air® app data (May 2015–December 2020) by users self‐reporting AR (16–90 years). We compared eight AR medication schemes on reported VAS of allergy symptoms, clustering data by the patient and controlling for confounding factors. We compared (i) allergy symptoms between patients with and without AIT and (ii) different drug classes used in co‐medication. We analysed 269,837 days from 10,860 users. Most days (52.7%) involved medication use. Median VAS levels were significantly higher in co‐medication than in monotherapy (including the fixed combination azelastine‐fluticasone) schemes. In adjusted models, azelastine‐fluticasone was associated with lower average VAS global allergy symptoms than all other medication schemes, while the contrary was observed for oral corticosteroids. AIT was associated with a decrease in allergy symptoms in some medication schemes. A difference larger than the MID compared to no treatment was observed for oral steroids. Azelastine‐fluticasone was the drug class with the lowest chance of being used in co‐medication (adjusted OR = 0.75 95% CI = 0.71–0.80). Median VAS levels were higher in co‐medication than in monotherapy. Patients with more severe symptoms report a higher treatment, which is currently not reflected in guidelines.
Publisher: Wiley
Date: 21-09-2021
DOI: 10.1111/ALL.14471
Publisher: Wiley
Date: 30-06-2023
DOI: 10.1111/ALL.15740
Abstract: Biomarkers for the diagnosis, treatment and follow‐up of patients with rhinitis and/or asthma are urgently needed. Although some biologic biomarkers exist in specialist care for asthma, they cannot be largely used in primary care. There are no validated biomarkers in rhinitis or allergen immunotherapy (AIT) that can be used in clinical practice. The digital transformation of health and health care (including mHealth) places the patient at the center of the health system and is likely to optimize the practice of allergy. Allergic Rhinitis and its Impact on Asthma (ARIA) and EAACI (European Academy of Allergy and Clinical Immunology) developed a Task Force aimed at proposing patient‐reported outcome measures (PROMs) as digital biomarkers that can be easily used for different purposes in rhinitis and asthma. It first defined control digital biomarkers that should make a bridge between clinical practice, randomized controlled trials, observational real‐life studies and allergen challenges. Using the MASK‐air app as a model, a daily electronic combined symptom‐medication score for allergic diseases (CSMS) or for asthma (e‐DASTHMA), combined with a monthly control questionnaire, was embedded in a strategy similar to the diabetes approach for disease control. To mimic real‐life, it secondly proposed quality‐of‐life digital biomarkers including daily EQ‐5D visual analogue scales and the bi‐weekly RhinAsthma Patient Perspective (RAAP). The potential implications for the management of allergic respiratory diseases were proposed.
Publisher: Wiley
Date: 15-01-2022
DOI: 10.1111/ALL.15199
Abstract: Validated combined symptom‐medication scores (CSMSs) are needed to investigate the effects of allergic rhinitis treatments. This study aimed to use real‐life data from the MASK‐air ® app to generate and validate hypothesis‐ and data‐driven CSMSs. We used MASK‐air ® data to assess the concurrent validity, test‐retest reliability and responsiveness of one hypothesis‐driven CSMS (modified CSMS: mCSMS), one mixed hypothesis‐ and data‐driven score (mixed score), and several data‐driven CSMSs. The latter were generated with MASK‐air ® data following cluster analysis and regression models or factor analysis. These CSMSs were compared with scales measuring (i) the impact of rhinitis on work productivity (visual analogue scale [VAS] of work of MASK‐air ® , and Work Productivity and Activity Impairment: Allergy Specific [WPAI‐AS]), (ii) quality‐of‐life (EQ‐5D VAS) and (iii) control of allergic diseases (Control of Allergic Rhinitis and Asthma Test [CARAT]). We assessed 317,176 days of MASK‐air ® use from 17,780 users aged 16‐90 years, in 25 countries. The mCSMS and the factor analyses‐based CSMSs displayed poorer validity and responsiveness compared to the remaining CSMSs. The latter displayed moderate‐to‐strong correlations with the tested comparators, high test‐retest reliability and moderate‐to‐large responsiveness. Among data‐driven CSMSs, a better performance was observed for cluster analyses‐based CSMSs. High accuracy (capacity of discriminating different levels of rhinitis control) was observed for the latter (AUC‐ROC = 0.904) and for the mixed CSMS (AUC‐ROC = 0.820). The mixed CSMS and the cluster‐based CSMSs presented medium‐high validity, reliability and accuracy, rendering them as candidates for primary endpoints in future rhinitis trials.
Publisher: Wiley
Date: 20-11-2023
DOI: 10.1111/ALL.15574
Abstract: Data from mHealth apps can provide valuable information on rhinitis control and treatment patterns. However, in MASK‐air®, these data have only been analyzed cross‐sectionally, without considering the changes of symptoms over time. We analyzed data from MASK‐air® longitudinally, clustering weeks according to reported rhinitis symptoms. We analyzed MASK‐air® data, assessing the weeks for which patients had answered a rhinitis daily questionnaire on all 7 days. We firstly used k‐means clustering algorithms for longitudinal data to define clusters of weeks according to the trajectories of reported daily rhinitis symptoms. Clustering was applied separately for weeks when medication was reported or not. We compared obtained clusters on symptoms and rhinitis medication patterns. We then used the latent class mixture model to assess the robustness of results. We analyzed 113,239 days (16,177 complete weeks) from 2590 patients (mean age ± SD = 39.1 ± 13.7 years). The first clustering algorithm identified ten clusters among weeks with medication use: seven with low variability in rhinitis control during the week and three with highly‐variable control. Clusters with poorly‐controlled rhinitis displayed a higher frequency of rhinitis co‐medication, a more frequent change of medication schemes and more pronounced seasonal patterns. Six clusters were identified in weeks when no rhinitis medication was used, displaying similar control patterns. The second clustering method provided similar results. Moreover, patients displayed consistent levels of rhinitis control, reporting several weeks with similar levels of control. We identified 16 patterns of weekly rhinitis control. Co‐medication and medication change schemes were common in uncontrolled weeks, reinforcing the hypothesis that patients treat themselves according to their symptoms.
Publisher: Wiley
Date: 03-2021
DOI: 10.1111/ALL.14453
Publisher: Wiley
Date: 10-2020
DOI: 10.1111/ALL.14302
Publisher: Elsevier BV
Date: 07-2022
DOI: 10.1016/J.PULMOE.2022.10.005
Abstract: The self-reporting of asthma frequently leads to patient misidentification in epidemiological studies. Strategies combining the triangulation of data sources may help to improve the identification of people with asthma. We aimed to combine information from the self-reporting of asthma, medication use and symptoms to identify asthma patterns in the users of an mHealth app. We studied MASK-air® users who reported their daily asthma symptoms (assessed by a 0-100 visual analogue scale - "VAS Asthma") at least three times (either in three different months or in any period). K-means cluster analysis methods were applied to identify asthma patterns based on: (i) whether the user self-reported asthma (ii) whether the user reported asthma medication use and (iii) VAS asthma. Clusters were compared by the number of medications used, VAS asthma levels and Control of Asthma and Allergic Rhinitis Test (CARAT) levels. We assessed a total of 8,075 MASK-air® users. The main clustering approach resulted in the identification of seven groups. These groups were interpreted as probable: (i) severe/uncontrolled asthma despite treatment (11.9-16.1% of MASK-air® users) (ii) treated and partly-controlled asthma (6.3-9.7%) (iii) treated and controlled asthma (4.6-5.5%) (iv) untreated uncontrolled asthma (18.2-20.5%) (v) untreated partly-controlled asthma (10.1-10.7%) (vi) untreated controlled asthma (6.7-8.5%) and (vii) no evidence of asthma (33.0-40.2%). This classification was validated in a study of 192 patients enrolled by physicians. We identified seven profiles based on the probability of having asthma and on its level of control. mHealth tools are hypothesis-generating and complement classical epidemiological approaches in identifying patients with asthma.
Publisher: Wiley
Date: 10-04-2023
DOI: 10.1111/ALL.15679
Abstract: Asthma, rhinitis, and atopic dermatitis (AD) are interrelated clinical phenotypes that partly overlap in the human interactome. The concept of “one‐airway‐one‐disease,” coined over 20 years ago, is a simplistic approach of the links between upper‐ and lower‐airway allergic diseases. With new data, it is time to reassess the concept. This article reviews (i) the clinical observations that led to Allergic Rhinitis and its Impact on Asthma (ARIA), (ii) new insights into polysensitization and multimorbidity, (iii) advances in mHealth for novel phenotype definitions, (iv) confirmation in canonical epidemiologic studies, (v) genomic findings, (vi) treatment approaches, and (vii) novel concepts on the onset of rhinitis and multimorbidity. One recent concept, bringing together upper‐ and lower‐airway allergic diseases with skin, gut, and neuropsychiatric multimorbidities, is the “Epithelial Barrier Hypothesis.” This review determined that the “one‐airway‐one‐disease” concept does not always hold true and that several phenotypes of disease can be defined. These phenotypes include an extreme “allergic” (asthma) phenotype combining asthma, rhinitis, and conjunctivitis. Rhinitis alone and rhinitis and asthma multimorbidity represent two distinct diseases with the following differences: (i) genomic and transcriptomic background (Toll‐Like Receptors and IL‐17 for rhinitis alone as a local disease IL‐33 and IL‐5 for allergic and non‐allergic multimorbidity as a systemic disease), (ii) allergen sensitization patterns (mono‐ or pauci‐sensitization versus polysensitization), (iii) severity of symptoms, and (iv) treatment response. In conclusion, rhinitis alone (local disease) and rhinitis with asthma multimorbidity (systemic disease) should be considered as two distinct diseases, possibly modulated by the microbiome, and may be a model for understanding the epidemics of chronic and autoimmune diseases.
Publisher: Wiley
Date: 23-10-2021
DOI: 10.1111/ALL.14422
Abstract: Digital anamorphosis is used to define a distorted image of health and care that may be viewed correctly using digital tools and strategies. MASK digital anamorphosis represents the process used by MASK to develop the digital transformation of health and care in rhinitis. It strengthens the ARIA change management strategy in the prevention and management of airway disease. The MASK strategy is based on validated digital tools. Using the MASK digital tool and the CARAT online enhanced clinical framework, solutions for practical steps of digital enhancement of care are proposed.
Publisher: Wiley
Date: 07-2020
DOI: 10.1111/ALL.14336
Publisher: Wiley
Date: 22-03-2020
DOI: 10.1111/ALL.14204
Abstract: In allergic rhinitis, a relevant outcome providing information on the effectiveness of interventions is needed. In MASK‐air (Mobile Airways Sentinel Network), a visual analogue scale (VAS) for work is used as a relevant outcome. This study aimed to assess the performance of the work VAS work by comparing VAS work with other VAS measurements and symptom‐medication scores obtained concurrently. All consecutive MASK‐air users in 23 countries from 1 June 2016 to 31 October 2018 were included (14 189 users 205 904 days). Geolocalized users self‐assessed daily symptom control using the touchscreen functionality on their smart phone to click on VAS scores (ranging from 0 to 100) for overall symptoms (global), nose, eyes, asthma and work. Two symptom‐medication scores were used: the modified EAACI CSMS score and the MASK control score for rhinitis. To assess data quality, the intra‐in idual response variability (IRV) index was calculated. A strong correlation was observed between VAS work and other VAS. The highest levels for correlation with VAS work and variance explained in VAS work were found with VAS global, followed by VAS nose, eye and asthma. In comparison with VAS global, the mCSMS and MASK control score showed a lower correlation with VAS work. Results are unlikely to be explained by a low quality of data arising from repeated VAS measures. VAS work correlates with other outcomes (VAS global, nose, eye and asthma) but less well with a symptom‐medication score. VAS work should be considered as a potentially useful AR outcome in intervention studies.
Publisher: Wiley
Date: 30-09-2021
DOI: 10.1111/ALL.14838
Abstract: Older adults, especially men and/or those with diabetes, hypertension, and/or obesity, are prone to severe COVID‐19. In some countries, older adults, particularly those residing in nursing homes, have been prioritized to receive COVID‐19 vaccines due to high risk of death. In very rare instances, the COVID‐19 vaccines can induce anaphylaxis, and the management of anaphylaxis in older people should be considered carefully. An ARIA‐EAACI‐EuGMS (Allergic Rhinitis and its Impact on Asthma, European Academy of Allergy and Clinical Immunology, and European Geriatric Medicine Society) Working Group has proposed some recommendations for older adults receiving the COVID‐19 vaccines. Anaphylaxis to COVID‐19 vaccines is extremely rare (from 1 per 100,000 to 5 per million injections). Symptoms are similar in younger and older adults but they tend to be more severe in the older patients. Adrenaline is the mainstay treatment and should be readily available. A flowchart is proposed to manage anaphylaxis in the older patients.
Publisher: Elsevier BV
Date: 2020
DOI: 10.1016/J.RMED.2019.105817
Abstract: Asthma prevalence is 339 million globally. 'Severe asthma' (SA) comprises subjects with uncontrolled asthma despite proper management. To compare asthma from erse ethnicities and environments. A cross-sectional analysis of two adult cohorts, a Brazilian (ProAR) and a European (U-BIOPRED). U-BIOPRED comprised of 311 non-smoking with Severe Asthma (SAn), 110 smokers or ex-smokers with SA (SAs) and 88 mild to moderate asthmatics (MMA) while ProAR included 544 SA and 452 MMA. Although these projects were independent, there were similarities in objectives and methodology, with ProAR adopting operating procedures of U-BIOPRED. Among SA subjects, age, weight, proportion of former smokers and FEV ProAR and U-BIOPRED cohorts, with varying severity, ethnicity and environment have similarities, which provide the basis for global external validation of asthma phenotypes. This should stimulate collaboration between asthma consortia with the aim of understanding SA, which will lead to better management.
Location: United Kingdom of Great Britain and Northern Ireland
Location: United Kingdom of Great Britain and Northern Ireland
Location: United Kingdom of Great Britain and Northern Ireland
Location: United Kingdom of Great Britain and Northern Ireland
Location: United Kingdom of Great Britain and Northern Ireland
Location: United Kingdom of Great Britain and Northern Ireland
No related grants have been discovered for Alvaro Cruz.