A System to Classify Treatable Traits in Primary Care

Asthma Clinical Trial

— SMART  

Official title:

A System to Classify Treatable Traits in Primary Care

Clinical Trial Details — Status: Not yet recruiting

Administrative data

• NCT number: NCT05357274
• Other study ID #: RC2021/01
• Status: Not yet recruiting
• Start date: May 16, 2022
• Est. completion date: December 31, 2024

Study information

• Verified date: April 2022
• Source: Royal College of Surgeons, Ireland
• Contact: Elaine Mac Hale
• Phone: 018093730
• Email: elainemachale[@]rcsi.com
• Is FDA regulated: No
• Study type: Observational

Clinical Trial Summary

This study proposes an approach to address an urgent unmet need in clinical practice, namely a pragmatic method of establishing what is the cause of a patient's complaint and the next steps to address this problem. In this study, the investigators will compare the proposed classification with current best practice of self-report, spirometry and FeNO. The investigators will compare the two approaches with a gold standard of deep characterisation by 3 separate diagnostic tests. The investigators hypothesize that patients with symptoms of respiratory disease fall into one of four working groups based on accurate knowledge of three parameters, airflow, treatment use and the patient's symptoms.

Description:

In respiratory diseases, the presenting symptoms are often a combination of cough, dyspnoea and wheeze. These three symptoms can be present in a significant number of conditions, including airways disease, cardiac disease and lung parenchymal disease. Making an accurate and timely clinical diagnosis is a challenge. Furthermore, physical deconditioning and co-morbidities such as obesity often create further obstacles to diagnosis. Even in the context of a clinical diagnosis of airways disease, differentiating between asthma and COPD is often not a straightforward decision. It takes time to establish by evaluating a patient's symptoms and major risk factors like smoking or allergy suggesting a particular aetiology. The diagnosis is further refined by spirometry or measures of FeNO when available and, importantly, the patient's response to treatment (1). There are several practical problems that make this approach less than accurate. Symptoms do not correlate with airflow limitation because co-exiting conditions like obesity and deconditioning and complicating factors such as anxiety and poor recall make symptom-based diagnosis imperfect (2). Diagnostic testing with spirometry is impractical and only provides a snapshot of lung function. This test relies on disease activity being present at the time of testing appointment. This feature is uncommon given the intermittent nature of symptoms in asthma. It is not uncommon for clinicians trying to interpret a set of lung function to hear a patient say something like "I am fine now, but I was awful two weeks ago". This means that people are often incorrectly labelled as having or not having asthma. A landmark study showed that incorrect labelling of people as having asthma but this could not be proven objectively in over 30% of patients assessed in a national study in Canada (3). The measurement of airway inflammation with FeNO is inaccurate unless treatment use is measured concurrently (4). Because of these practical problems with testing, clinicians often have to rely on symptoms to make the diagnosis of asthma. Furthermore, in the context of an accurately established obstructive airway disease, practical issues persist. For example, differentiating between asthma and COPD, decision on referral to a secondary centre, tailoring treatment and determining if disease is controlled. Tailoring inhaled therapy to the individual patient is a further complex decision in this patient cohort. However, poor adherence to ICS/LABA treatment is common, on average it is less than 50% among patients in primary care (5-7). Therefore, the diagnosis of airways disease in primary care is inherently inaccurate. This inaccuracy means that decisions on treatment effectiveness are also inaccurate. These common but important limitations lead to overuse of corticosteroids, antibiotics and beta-agonists with poor symptom control potential medication related morbidity. It follows that diagnostic accuracy and appropriate inhaled treatment use in airways disease has real and significant implications for patient safety, adverse outcomes, cost and waste. To address these problems the INCA team have developed algorithms to classify and align lung function, treatment use and symptoms. This data is delivered via a novel CE marked platform to non-specialists with specific "suggestion scripts" (8). The classification divides patients into 4 main groups based on whether the airway function is or is not controlled if the patient took their treatment and if they remain symptomatic (9, 10). These groups are; 1. The treatment intensify group: these people have persistent airflow obstruction/wide diurnal variation with good adherence. This trait requires additional bronchodilator and/or anti-inflammatory therapy and further tests. 2. The obstructed, but poorly adherent group: These people have persistent airflow obstruction and poor adherence to treatment or poor inhaler technique. Adherence is assessed based on a novel metric time above threshold. Management/treatment is therefore focused on promoting-adherence and correct inhaler technique. 3. The co-existing other condition group: This group have respiratory symptoms but no evidence of airflow obstruction. For these people airways disease is not the predominant problem and so should be evaluated with further tests and/or treatment of co-existing conditions. 4. Controlled airflow and controlled symptoms group: this group need to continue their current inhaled treatment. This classification accounts for the common issues of poor adherence and inaccurate diagnosis in asthma, which are reported to occur as commonly as 50% and 30% respectively. The classification also accounts for some more nuanced issues that would arise if a clinician were to rely simply on assessing adherence or lung function. These include confirming that people with uncontrolled asthma have been adherent and on the other hand, even if poorly adherent, that controlled patients do not need advice on extra adherence. This classification may help a clinician to deliver a personalised, accurate and efficient consultation to people with asthma in primary care. In this proposal the investigators will test the feasibility of this approach among patients attending community general practitioners, those newly referred for assessment in secondary care and those advanced nurse practitioner respiratory clinics with a physician's clinical diagnosis of asthma, more specifically those who have chronic respiratory symptoms who their treating physician believe to be due to asthma, but who have not yet undergone laboratory lung function testing to establish the correct diagnosis of asthma. Hypothesis The investigators hypothesize that the simultaneous measurement and alignment of inhaler use and airflow can be used to organise patients with clinical diagnoses of asthma into one of four groups described above. This classification can subsequently be used as the basis for adjustments to treatment and further diagnostic testing as needed. The investigators will assess the value of this approach in primary care by comparing it with the standard approach of using point in time measures with FeNO and spirometry coupled with self-report.

Recruitment information / eligibility

• Status: Not yet recruiting
• Enrollment: 200
• Est. completion date: December 31, 2024
• Est. primary completion date: May 16, 2024
• Accepts healthy volunteers: No
• Gender: All
• Age group: 18 Years and older

Eligibility

Inclusion Criteria:

1. Capable of understanding and willing to give voluntary informed consent prior to any protocol specific procedures being performed.

2. Patients aged over 18 years.

3. Present with persisting respiratory symptoms that are suggestive of airways disease.

4. Capable of understanding and complying with the requirements of the protocol, including ability to attend for all 3 required visits.

5. Able and willing to take inhaled medication via an Ellipta. [In the opinion of the investigator suitable for use of this inhaler.]

6. Willing to use an electronic spirometer & peak flow meter.

7. Currently prescribed Inhaled Corticosteroids (ICS) either alone or in combination with long acting beta agonists (ICS/LABA)

Exclusion Criteria:

1. Have an active laboratory confirmed diagnosis of Asthma or COPD (with change to treatment within the last 8 weeks).

2. Known previous sensitivity to ICS and Beta Agonist.

3. Known significant (in the opinion of the investigator) concurrent medical disease that might mean that the patient cannot complete the full study.

4. Intercurrent respiratory tract infection requiring antibiotic treatment in the last week

5. Acute exacerbation of symptoms in the last 14 days requiring oral corticosteroid treatment

6. Currently on specific concurrent potent cytochrome P450 3A4 (CYP3A4) medications; ketoconazole and ritonavir.

7. Pregnancy

8. Have greater than a 20-Pack Year Smoking History

Related Conditions & MeSH terms

• Asthma
• Copd
• Respiration Disorders
• Respiratory Disease
• Respiratory Tract Diseases

Intervention

Diagnostic Test:
• Diagnostic testing
Data will be uploaded to a server where algorithms will be deployed that incorporate features related to treatment use and variables of airflow will allocate the care pathway into one of the 4 pathways. Treatment will be directed by this using a validated automated decision support system

Locations

Country	Name	City	State
Ireland	Beaumont Hospital	Dublin

Sponsors (2)

Lead Sponsor	Collaborator
Royal College of Surgeons, Ireland	GlaxoSmithKline

Country where clinical trial is conducted

Ireland, 

References & Publications (10)

Aaron SD, Boulet LP, Reddel HK, Gershon AS. Underdiagnosis and Overdiagnosis of Asthma. Am J Respir Crit Care Med. 2018 Oct 15;198(8):1012-1020. doi: 10.1164/rccm.201804-0682CI. Review. — View Citation

Blakey JD, Bender BG, Dima AL, Weinman J, Safioti G, Costello RW. Digital technologies and adherence in respiratory diseases: the road ahead. Eur Respir J. 2018 Nov 22;52(5). pii: 1801147. doi: 10.1183/13993003.01147-2018. Print 2018 Nov. Review. — View Citation

Board G. GINA Report, Global Strategy for Asthma Management and Prevention. GINA Report, Global Strategy for Asthma Management and Prevention. 2016.

Heaney LG, Busby J, Bradding P, Chaudhuri R, Mansur AH, Niven R, Pavord ID, Lindsay JT, Costello RW; Medical Research Council UK Refractory Asthma Stratification Programme (RASP-UK). Remotely Monitored Therapy and Nitric Oxide Suppression Identifies Nonadherence in Severe Asthma. Am J Respir Crit Care Med. 2019 Feb 15;199(4):454-464. doi: 10.1164/rccm.201806-1182OC. — View Citation

McDonald VM, Clark VL, Cordova-Rivera L, Wark PAB, Baines KJ, Gibson PG. Targeting treatable traits in severe asthma: a randomised controlled trial. Eur Respir J. 2020 Mar 5;55(3). pii: 1901509. doi: 10.1183/13993003.01509-2019. Print 2020 Mar. — View Citation

Moran C, Doyle F, Sulaiman I, Bennett K, Greene G, Molloy GJ, Reilly RB, Costello RW, Mellon L. The INCA(TM) (Inhaler Compliance Assessment(TM)): A comparison with established measures of adherence. Psychol Health. 2017 Oct;32(10):1266-1287. doi: 10.1080/08870446.2017.1290243. Epub 2017 Feb 28. Erratum in: Psychol Health. 2017 Oct;32(10):i. — View Citation

O'Dwyer S, Greene G, MacHale E, Cushen B, Sulaiman I, Boland F, Bosnic-Anticevich S, Mokoka MC, Reilly RB, Taylor T, Ryder SA, Costello RW. Personalized Biofeedback on Inhaler Adherence and Technique by Community Pharmacists: A Cluster Randomized Clinical Trial. J Allergy Clin Immunol Pract. 2020 Feb;8(2):635-644. doi: 10.1016/j.jaip.2019.09.008. Epub 2019 Sep 27. — View Citation

Sulaiman I, Cushen B, Greene G, Seheult J, Seow D, Rawat F, MacHale E, Mokoka M, Moran CN, Sartini Bhreathnach A, MacHale P, Tappuni S, Deering B, Jackson M, McCarthy H, Mellon L, Doyle F, Boland F, Reilly RB, Costello RW. Objective Assessment of Adherence to Inhalers by Patients with Chronic Obstructive Pulmonary Disease. Am J Respir Crit Care Med. 2017 May 15;195(10):1333-1343. doi: 10.1164/rccm.201604-0733OC. Erratum in: Am J Respir Crit Care Med. 2017 May 15;195(10 ):1407. — View Citation

Sulaiman I, Greene G, MacHale E, Seheult J, Mokoka M, D'Arcy S, Taylor T, Murphy DM, Hunt E, Lane SJ, Diette GB, FitzGerald JM, Boland F, Sartini Bhreathnach A, Cushen B, Reilly RB, Doyle F, Costello RW. A randomised clinical trial of feedback on inhaler adherence and technique in patients with severe uncontrolled asthma. Eur Respir J. 2018 Jan 4;51(1). pii: 1701126. doi: 10.1183/13993003.01126-2017. Print 2018 Jan. — View Citation

Sulaiman I, Seheult J, MacHale E, D'Arcy S, Boland F, McCrory K, Casey J, Bury G, Al-Alawi M, O'Dwyer S, Ryder SA, Reilly RB, Costello RW. Irregular and Ineffective: A Quantitative Observational Study of the Time and Technique of Inhaler Use. J Allergy Clin Immunol Pract. 2016 Sep-Oct;4(5):900-909.e2. doi: 10.1016/j.jaip.2016.07.009. — View Citation

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Comparing gold standard asthma diagnostics to PEFR (L/min)	To assess the sensitivity of using serially measured, digital lung function measures (PEFR L/min) in confirming a diagnosis of asthma.	12 weeks
Primary	Comparing gold standard asthma diagnostics to repeated measures of lung function FEV1/FVC	To assess the sensitivity of using serially measured, lung function FEV1/FVC in confirming a diagnosis of asthma.	12 weeks
Secondary	Diurnal variation	Assess the degree of diurnal variation in patients with mild asthma accounting for treatment effect with bronchodilator.	12 weeks
Secondary	Activity levels	Measure patients daily activity level (in steps per day)	12 weeks