Clinical validation of digital biomarkers for pediatric patients with asthma and cystic fibrosis - Potential for clinical trials and clinical care

What diagnostic tests are available for respiratory infections or pulmonary exacerbations in cystic fibrosis: A scoping literature review

A scoping review methodological framework formed the basis of this review. A search of two electronic databases captured relevant literature published from 2013. 1184 articles were screened, 200 of which met inclusion criteria. Included studies were categorised as tests for either respiratory infections OR pulmonary exacerbations. Data were extracted to ascertain test type, sample type, and indication of use for each test type. For infection, culture is the most common testing method, particularly for bacterial infections, whereas PCR is utilised more for the diagnosis of viral infections. Spirometry tests, indicating lung function, facilitate respiratory infection diagnoses. There is no clear definition of what an exacerbation is in persons with CF. A clinical checklist with risk criteria can determine if a patient is experiencing an exacerbation event, however the diagnosis is clinician-led and will vary between individuals. Fuchs criteria are one of the most frequently used tests to assess signs and symptoms of exacerbation in persons with CF. This scoping review highlights the development of home monitoring tests to facilitate earlier and easier diagnoses, and the identification of novel biomarkers for indication of infections/exacerbations as areas of current research and development. Research is particularly prevalent regarding exhaled breath condensate and volatile organic compounds as an alternative sampling/biomarker respectively for infection diagnosis. Whilst there are a wide range of tests available for diagnosing respiratory infections and/or exacerbations, these are typically used clinically in combination to ensure a rapid, accurate diagnosis which will ultimately benefit both the patient and clinician.

Remote endpoints for clinical trials in cystic fibrosis: Report from the U.S. CF foundation remote endpoints task force

The COVID-19 pandemic necessitated a rapid shift in clinical research to perform virtual visits and remote endpoint assessments, providing a key opportunity to optimize the use of remote endpoints for clinical trials in cystic fibrosis. The use of remote endpoints could allow more diverse participation in clinical trials while minimizing participant burden but must be robustly evaluated to ensure adequate performance and feasibility. In response, the Cystic Fibrosis Foundation convened the Remote Endpoint Task Force (Supplemental Table 1), a multidisciplinary group of CF researchers with remote endpoint expertise and community members tasked to better understand the current and future use of remote endpoints for clinical research. Here, we describe the current use of remote endpoints in CF clinical research, address key unanswered questions regarding their use and feasibility, and discuss the next steps to determine clinical trial readiness.

DIGIPREDICT: physiological, behavioural and environmental predictors of asthma attacks-a prospective observational study using digital markers and artificial intelligence-study protocol

INTRODUCTION

Asthma attacks are a leading cause of morbidity and mortality but are preventable in most if detected and treated promptly. However, the changes that occur physiologically and behaviourally in the days and weeks preceding an attack are not always recognised, highlighting a potential role for technology. The aim of this study 'DIGIPREDICT' is to identify early digital markers of asthma attacks using sensors embedded in smart devices including watches and inhalers, and leverage health and environmental datasets and artificial intelligence, to develop a risk prediction model to provide an early, personalised warning of asthma attacks.

METHODS AND ANALYSIS

A prospective sample of 300 people, 12 years or older, with a history of a moderate or severe asthma attack in the last 12 months will be recruited in New Zealand. Each participant will be given a smart watch (to assess physiological measures such as heart and respiratory rate), peak flow meter, smart inhaler (to assess adherence and inhalation) and a cough monitoring application to use regularly over 6 months with fortnightly questionnaires on asthma control and well-being. Data on sociodemographics, asthma control, lung function, dietary intake, medical history and technology acceptance will be collected at baseline and at 6 months. Asthma attacks will be measured by self-report and confirmed with clinical records. The collected data, along with environmental data on weather and air quality, will be analysed using machine learning to develop a risk prediction model for asthma attacks.

ETHICS AND DISSEMINATION

Ethical approval has been obtained from the New Zealand Health and Disability Ethics Committee (2023 FULL 13541). Enrolment began in August 2023. Results will be presented at local, national and international meetings, including dissemination via community groups, and submission for publication to peer-reviewed journals.

TRIAL REGISTRATION NUMBER

Australian New Zealand Clinical Trials Registry ACTRN12623000764639; Australian New Zealand Clinical Trials Registry.

Objectives for algorithmic decision-making systems in childhood asthma: Perspectives of children, parents, and physicians

Objectives

To identify with children, parents and physicians the objectives to be used as parameters for algorithmic decision-making systems (ADMSs) adapting treatments in childhood asthma.

Methods

We first conducted a qualitative study based on semi-structured interviews to explore the objectives that children aged 8-17 years, their parents, and their physicians seek to achieve when taking/giving/prescribing a treatment for asthma. Following the grounded theory approach, each interview was independently coded by two researchers; reconciled codes were used to assess code frequency, categories were defined, and the main objectives identified. We then conducted a quantitative study based on questionnaires using these objectives to determine how children/parents/physicians ranked these objectives and whether their responses were aligned.

Results

We interviewed 71 participants (31 children, 30 parents and 10 physicians) in the qualitative study and identified seven objectives associated with treatment uptake and five objectives associated with treatment modalities. We included 291 participants (137 children, 137 parents, and 17 physicians) in the quantitative study. We found little correlation between child, parent, and physician scores for each of the objectives. Each child's asthma history influenced the choice of scores assigned to each objective by the child, parents, and physician.

Conclusion

The identified objectives are quantifiable and relevant to the management of asthma in the short and long term. They can therefore be incorporated as parameters for future ADMS. Shared decision-making seems essential to achieve consensus among children, parents, and physicians when choosing the weight to assign to each of these objectives.

Identifying Game-Based Digital Biomarkers of Cognitive Risk for Adolescent Substance Misuse: Protocol for a Proof-of-Concept Study

BACKGROUND

Adolescents at risk for substance misuse are rarely identified early due to existing barriers to screening that include the lack of time and privacy in clinic settings. Games can be used for screening and thus mitigate these barriers. Performance in a game is influenced by cognitive processes such as working memory and inhibitory control. Deficits in these cognitive processes can increase the risk of substance use. Further, substance misuse affects these cognitive processes and may influence game performance, captured by in-game metrics such as reaction time or time for task completion. Digital biomarkers are measures generated from digital tools that explain underlying health processes and can be used to predict, identify, and monitor health outcomes. As such, in-game performance metrics may represent digital biomarkers of cognitive processes that can offer an objective method for assessing underlying risk for substance misuse.

OBJECTIVE

This is a protocol for a proof-of-concept study to investigate the utility of in-game performance metrics as digital biomarkers of cognitive processes implicated in the development of substance misuse.

METHODS

This study has 2 aims. In aim 1, using previously collected data from 166 adolescents aged 11-14 years, we extracted in-game performance metrics from a video game and are using machine learning methods to determine whether these metrics predict substance misuse. The extraction of in-game performance metrics was guided by literature review of in-game performance metrics and gameplay guidebooks provided by the game developers. In aim 2, using data from a new sample of 30 adolescents playing the same video game, we will test if metrics identified in aim 1 correlate with cognitive processes. Our hypothesis is that in-game performance metrics that are predictive of substance misuse in aim 1 will correlate with poor cognitive function in our second sample.

RESULTS

This study was funded by National Institute on Drug Abuse through the Center for Technology and Behavioral Health Pilot Core in May 2022. To date, we have extracted 285 in-game performance metrics. We obtained institutional review board approval on October 11, 2022. Data collection for aim 2 is ongoing and projected to end in February 2024. Currently, we have enrolled 12 participants. Data analysis for aim 2 will begin once data collection is completed. The results from both aims will be reported in a subsequent publication, expected to be published in late 2024.

CONCLUSIONS

Screening adolescents for substance use is not consistently done due to barriers that include the lack of time. Using games that provide an objective measure to identify adolescents at risk for substance misuse can increase screening rates, early identification, and intervention. The results will inform the utility of in-game performance metrics as digital biomarkers for identifying adolescents at high risk for substance misuse.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/46990.

Home monitoring in asthma: towards digital twins

PURPOSE OF REVIEW

We highlight the recent advances in home monitoring of patients with asthma, and show that these advances converge towards the implementation of digital twin systems.

RECENT FINDINGS

Connected devices for asthma are increasingly numerous, reliable and effective: new electronic monitoring devices extend to nebulizers and spacers, are able to assess the quality of the inhalation technique, and to identify asthma attack triggers when they include a geolocation function; environmental data can be acquired from databases and refined by wearable air quality sensors; smartwatches are better validated. Connected devices are increasingly integrated into global monitoring systems. At the same time, machine learning techniques open up the possibility of using the large amount of data collected to obtain a holistic assessment of asthma patients, and social robots and virtual assistants can help patients in the daily management of their asthma.

SUMMARY

Advances in the internet of things, machine learning techniques and digital patient support tools for asthma are paving the way for a new era of research on digital twins in asthma.