Smartphone Evaluation for Airway Diseases

(AWARE Trial)

Recruiting in Palo Alto (17 mi)

+1 other location

Overseen by Erick Forno, MD MPH

Age: Any Age

Sex: Any

Travel: May Be Covered

Time Reimbursement: Varies

Trial Phase: Academic

Recruiting

Sponsor: Indiana University

Disqualifiers: Acute illness, Chronic illness, others

No Placebo Group

Trial Summary

What is the purpose of this trial?

The study will evaluate the feasibility of using smartphone speakers and microphones to evaluate the caliber of the airways, detect airway obstruction, aid in airway disease diagnosis, and identify disease exacerbations.

Will I have to stop taking my current medications?

The trial information does not specify whether you need to stop taking your current medications. It's best to discuss this with the trial coordinators or your doctor.

What data supports the effectiveness of the treatment AWARE for airway diseases?

Research shows that smartphone apps can help people manage asthma and other respiratory conditions by improving self-management and symptom reporting. For example, a study found that a smartphone app for cystic fibrosis helped detect symptom flare-ups earlier, which can lead to better health outcomes. ^{1 2 3 4 5}

Is the smartphone app for airway diseases safe for humans?

The MASK app, used for monitoring allergic rhinitis and asthma, has been deployed in 23 countries and is available in 16 languages, suggesting it is widely used and generally considered safe. Additionally, a smartphone app for cystic fibrosis was developed to report symptoms, indicating that similar technologies have been safely used in other respiratory conditions. ^{3 6 7 8 9}

How is the AWARE treatment for airway diseases different from other treatments?

The AWARE treatment is unique because it uses a smartphone-based platform to screen and diagnose asthma and COPD (chronic obstructive pulmonary disease) by integrating data from an electronic stethoscope, a peak flow meter app, and a patient questionnaire, which is then analyzed using a machine learning algorithm. This approach is particularly beneficial in areas with limited access to specialized healthcare, offering a novel way to improve diagnosis and management of these conditions. ^{5 10 11 12 13}

Research Team

Erick Forno, MD MPH

Principal Investigator

Indiana University

Eligibility Criteria

This trial is for individuals with airway conditions like Bronchiectasis, Ciliary Motility Disorders, COPD, Cystic Fibrosis, Asthma or a floppy airway. It's also open to healthy people who can serve as controls. Specific eligibility criteria are not provided.

Inclusion Criteria

I am between 8 and 65 years old.

Ability to perform spirometry and oscillometry

Signed informed consent (and assent for children as appropriate)

Exclusion Criteria

I don't have any illnesses that could affect my lung function tests.

Inability or unwillingness to perform AWARE, spirometry, or oscillometry

Trial Timeline

Screening

Participants are screened for eligibility to participate in the trial

2-4 weeks

Development and Testing

Development and improvement of smartphone sensing and machine learning approaches for airway disease diagnosis and lung function estimation

Up to two weeks per subject

Multiple visits (in-person and virtual)

Home Monitoring

Subgroup of subjects perform AWARE at home to evaluate supervised vs unsupervised and in-clinic vs at-home measurements

Up to two weeks

Follow-up

Participants are monitored for safety and effectiveness after the main study activities

4 weeks

Treatment Details

Interventions

• AWARE (Behavioural Intervention)

Trial Overview The AWARE (Acoustic Waveform Respiratory Evaluation) study tests if smartphone speakers and microphones can measure airway size, detect blockages, help diagnose airway diseases and spot when the disease gets worse.

Participant Groups

Group I: Other Airway Diseases Experimental Treatment 1 Intervention

This group will include subjects with airway ciliary motility disorders, bronchiectasis, and airway malaria. Given variability in the clinical presentation and diagnosis of these conditions, they will be ascertained by physician diagnosis and reviewed by study physician investigators.

Group II: Healthy Controls Experimental Treatment 1 Intervention

This will include generally healthy subjects who do not have any of the airway diseases included in the study, nor other chronic cardiorespiratory or other diseases that may alter lung function or the ability to participate in the study.

Group III: Cystic Fibrosis (CF) Experimental Treatment 1 Intervention

Physician diagnosis based on U.S. CF Foundation guidelines, including signs/symptoms of CF and either a positive sweat chloride test (\>60 mmol/L), or an indeterminate sweat chloride test (30-59 mmol/L) plus two CF-causing CFTR mutations. The study may include subjects with different CFTR mutation classes as well as both on and off CFTR modulators.

Group IV: Chronic Obstructive Pulmonary Disease (COPD) Experimental Treatment 1 Intervention

Physician diagnosis, plus symptoms of COPD per GOLD guidelines, plus post-bronchodilator FEV1/FVC \<0.70 or below the lower limit of normal (LLN) using GLI reference equations.

Group V: Asthma Experimental Treatment 1 Intervention

Physician diagnosis plus at least one of the following in the past year: asthma symptoms that improve with albuterol; prescribed asthma controller medication(s); an acute asthma exacerbation requiring systemic steroids; or an emergency department visit or hospitalization for asthma. Alternatively, report of current asthma symptoms per US NAEPP or Global Initiative for Asthma (GINA) guidelines, plus documentation of bronchodilator response or airway hyperresponsiveness.

Who Is Running the Clinical Trial?

Indiana University

Lead Sponsor

Trials

1,063

Recruited

1,182,000+

Alan Palkowitz

Indiana University

Chief Executive Officer since 2020

PhD in Chemistry from Indiana University

David Ingram

Indiana University

Chief Medical Officer since 2020

MD from Indiana University School of Medicine

National Heart, Lung, and Blood Institute (NHLBI)

Collaborator

Trials

3,987

Recruited

47,860,000+

Dr. Gary H. Gibbons

National Heart, Lung, and Blood Institute (NHLBI)

Chief Executive Officer since 2012

MD from Harvard Medical School

Dr. James P. Kiley

National Heart, Lung, and Blood Institute (NHLBI)

Chief Medical Officer since 2011

MD from University of California, San Francisco

University of Pittsburgh

Collaborator

Trials

1,820

Recruited

16,360,000+

David Apelian

University of Pittsburgh

Chief Executive Officer since 2019

PhD in Molecular Biology from Rutgers University, MD from the University of Medicine and Dentistry of New Jersey, MBA from Quinnipiac University

Pamela D. Garzone

University of Pittsburgh

Chief Medical Officer

PhD in Clinical Science from the University of Pittsburgh

Findings from Research

A smartphone application designed for asthma self-management significantly improved patients' knowledge about their condition, with scores increasing from an average of 2.43 to 4.3 after using the app (p < 0.001).

The app was well-received by users, achieving a 'good' usability rating from 30 asthma patients, 8 IT specialists, and 2 asthma specialists, indicating its potential effectiveness in helping patients manage their asthma better.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Enhancing Asthma Patients' Self-Management through Smartphone-Based Application: Design, Usability Evaluation, and Educational Intervention. Farzandipour, M., Nabovati, E., Heidarzadeh Arani, M., et al.[2020]

A survey of 360 participants revealed that while many individuals believe mobile apps could help manage allergic respiratory diseases, only a small percentage (2 out of 360) regularly use these apps after downloading them.

The study highlights a significant gap in the effective use of medical apps, with 87.2% of participants never having downloaded an app related to their condition, indicating a need for improved app quality and better patient-targeting strategies.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

The role of mobile apps in allergic respiratory diseases: an Italian multicentre survey report. Lombardi, C., Bonini, M., Passalacqua, G.[2019]

In a study involving 288 participants with poorly controlled asthma, mobile phone-based monitoring did not show significant improvements in asthma control or self-efficacy compared to traditional paper-based monitoring after six months.

Both monitoring methods resulted in similar rates of acute exacerbations and healthcare costs, but the mobile phone service was more expensive due to telemonitoring costs, making it not cost-effective.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Clinical and cost effectiveness of mobile phone supported self monitoring of asthma: multicentre randomised controlled trial. Ryan, D., Price, D., Musgrave, SD., et al.[2023]

The MASK-air® app's daily visual analog scales (VASs) for monitoring allergic rhinitis symptoms show high intra-rater reliability (ICCs between 0.870 and 0.937), indicating that users can consistently report their symptoms over time.

The VASs also demonstrate moderate to high concurrent validity when compared to established measures like the EQ-5D and CARAT scores, suggesting they are effective tools for assessing the impact of allergic rhinitis on daily activities.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Validity, reliability, and responsiveness of daily monitoring visual analog scales in MASK-air®. Sousa-Pinto, B., Eklund, P., Pfaar, O., et al.[2022]

The MASK initiative, utilizing a mobile app for managing allergic rhinitis and asthma, has been deployed in 23 countries and is available in 16 languages, highlighting its global reach and potential for improving patient self-management.

Key findings from the MASK project indicate that many patients self-medicate and often do not adhere to treatment guidelines, suggesting a need for better patient education and support in managing their conditions.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

MASK 2017: ARIA digitally-enabled, integrated, person-centred care for rhinitis and asthma multimorbidity using real-world-evidence. Bousquet, J., Arnavielhe, S., Bedbrook, A., et al.[2022]

A study using data from the MASK-air® app involving 17,780 users showed that data-driven combined symptom-medication scores (CSMSs) had moderate-to-strong correlations with established measures of rhinitis impact, indicating their effectiveness in assessing treatment outcomes.

Among the CSMSs evaluated, cluster analysis-based scores demonstrated high accuracy in distinguishing levels of rhinitis control, making them strong candidates for use as primary endpoints in future clinical trials for allergic rhinitis.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Development and validation of combined symptom-medication scores for allergic rhinitis. Sousa-Pinto, B., Azevedo, LF., Jutel, M., et al.[2022]

A study of 626 chronic rhinosinusitis (CRS) patients using the mySinusitisCoach app revealed that nearly half of the patients were uncontrolled in their symptoms, significantly affecting their quality of life, especially in terms of sleep and daily activities.

Patients who had undergone functional endoscopic sinus surgery (FESS) reported lower symptom severity, but those with more than three surgeries did not experience the same benefits, indicating a limit to the effectiveness of surgical interventions.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Real-life assessment of chronic rhinosinusitis patients using mobile technology: The mySinusitisCoach project by EUFOREA. Seys, SF., De Bont, S., Fokkens, WJ., et al.[2021]

In a study involving 101 children with seasonal allergic rhinitis, adherence to daily symptom recording via a mobile app varied significantly, with 64.4% of participants being highly adherent (recording data on over 80% of days).

The study found that a higher percentage of changes in trend in symptom scores (RTSS, CSMS, and VAS) was associated with highly adherent patients, suggesting that this trend change could serve as a reliable proxy for the quality and accuracy of patient-reported data in managing allergic rhinitis.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Validation Parameters of Patient-Generated Data for Digitally Recorded Allergic Rhinitis Symptom and Medication Scores in the @IT.2020 Project: Exploratory Study. Dramburg, S., Perna, S., Di Fraia, M., et al.[2022]

The study introduces a cloud-based wearable IoT aldehyde sensor system designed to monitor environmental factors that can trigger asthma, potentially improving asthma management.

This innovative sensor system allows for real-time data collection and analysis, which can help researchers and patients better understand and manage asthma triggers in their daily environments.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

A Wearable IoT Aldehyde Sensor for Pediatric Asthma Research and Management. Li, B., Dong, Q., Downen, RS., et al.[2020]

A total of 72 mobile applications related to allergic rhinitis were identified, with 54 being unique, indicating a significant interest in digital tools for managing this condition.

Over half of the apps (51.4%) involved physician input in their development, suggesting a focus on credible and reliable information for users, while most apps were free and received an average rating of 3.9 out of 5.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Mobile Applications for Allergic Rhinitis. Zhou, AH., Patel, VR., Baredes, S., et al.[2018]

A mobile platform combining an electronic stethoscope, peak flow meter app, and patient questionnaire effectively screens for asthma and COPD, achieving a high accuracy with an AUC of 0.95 for identifying patients from the general population.

The platform not only identifies asthma and COPD but also distinguishes between the two conditions with even greater accuracy, achieving an AUC of 0.97, making it a promising tool for improving diagnosis in areas with limited access to healthcare professionals.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

A mobile platform for automated screening of asthma and chronic obstructive pulmonary disease. Chamberlain, DB., Kodgule, R., Fletcher, RR.[2020]

The BREATHE platform is a mobile health framework that integrates various sensors to monitor pediatric asthma, collecting continuous data on health metrics, environmental exposures, and daily activities from 20 participants over a week.

Initial findings suggest that BREATHE can effectively correlate environmental triggers with asthma symptoms, although usability challenges were noted, indicating the need for improvements in user engagement and convenience.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Biomedical REAl-Time Health Evaluation (BREATHE): toward an mHealth informatics platform. Bui, AAT., Hosseini, A., Rocchio, R., et al.[2022]

References

1. Germany pubmed.ncbi.nlm.nih.gov

Enhancing Asthma Patients' Self-Management through Smartphone-Based Application: Design, Usability Evaluation, and Educational Intervention. [2020]

2. Italy pubmed.ncbi.nlm.nih.gov

The role of mobile apps in allergic respiratory diseases: an Italian multicentre survey report. [2019]

3. Netherlands pubmed.ncbi.nlm.nih.gov

A smartphone application for reporting symptoms in adults with cystic fibrosis improves the detection of exacerbations: Results of a randomised controlled trial. [2021]

4. England pubmed.ncbi.nlm.nih.gov

Clinical and cost effectiveness of mobile phone supported self monitoring of asthma: multicentre randomised controlled trial. [2023]

5. England pubmed.ncbi.nlm.nih.gov

Validity, reliability, and responsiveness of daily monitoring visual analog scales in MASK-air®. [2022]

6. England pubmed.ncbi.nlm.nih.gov

MASK 2017: ARIA digitally-enabled, integrated, person-centred care for rhinitis and asthma multimorbidity using real-world-evidence. [2022]

7. Denmark pubmed.ncbi.nlm.nih.gov

Development and validation of combined symptom-medication scores for allergic rhinitis. [2022]

8. Denmark pubmed.ncbi.nlm.nih.gov

Real-life assessment of chronic rhinosinusitis patients using mobile technology: The mySinusitisCoach project by EUFOREA. [2021]

9. Canada pubmed.ncbi.nlm.nih.gov

Validation Parameters of Patient-Generated Data for Digitally Recorded Allergic Rhinitis Symptom and Medication Scores in the @IT.2020 Project: Exploratory Study. [2022]

10. Switzerland pubmed.ncbi.nlm.nih.gov

A Wearable IoT Aldehyde Sensor for Pediatric Asthma Research and Management. [2020]

11. United States pubmed.ncbi.nlm.nih.gov

Mobile Applications for Allergic Rhinitis. [2018]

12. United States pubmed.ncbi.nlm.nih.gov

A mobile platform for automated screening of asthma and chronic obstructive pulmonary disease. [2020]

13. United States pubmed.ncbi.nlm.nih.gov

Biomedical REAl-Time Health Evaluation (BREATHE): toward an mHealth informatics platform. [2022]