Select digital therapeutic products are intended for diagnostic application. Diagnostic application refers to detecting the presence or absence of a condition, the risk of developing a condition in the future, or treatment response (beneficial or adverse). Prescription digital therapeutics used for diagnostic purposes can be noted as "Software as a medical device" (SaMD) which states that software is intended to be used for a medical purpose, without being part of a hardware medical device or software that stores or transmits medical information. Devices receive marketing clearance or approval by the U.S. Food and Drug Administration either through the de novo premarket process, 510(k) process, or pre-market approval and must be prescribed by a healthcare provider. The U.S. Food and Drug Administration additionally recognizes a “mobile medical app” defined as a mobile app that incorporates device software functionality that meets the definition of a device, and either is intended to be used as an accessory to a regulated medical device, or to transform a mobile platform into a regulated medical device. 

Canvas DX (formerly known as Coagnoa App) is intended for use by healthcare providers as an aid in the diagnosis of Autism Spectrum Disorder (ASD) for patients ages 18 months through 72 months who are at risk for developmental delay based on concerns of a parent, caregiver, or healthcare provider. The device is not intended for use as a stand-alone diagnostic device but as an adjunct to the diagnostic process. The device is for prescription use only. Canvas DX includes 3 questionnaires: parent/caregiver, a video analyst, and a health care provider, with an algorithm that synthesizes the 3 inputs for use by the primary care provider.

The LIVMOR Halo AF Detection System consists of an algorithm to filter and detect irregular pulse rhythm that may be suggestive of atrial fibrillation (AF) from photoplethysmograph (PPG) data, a patient user interface to notify the patient of data collection, and a physician user interface to alert the physician when irregular pulse rhythm suggestive of AF is detected. This medical device software interfaces with the LIVMOR Halo+ Home Monitoring System and compatible smartwatch to capture PPG data and sync to servers. The data from the recording session is analyzed. When a signal is suggestive of AF, the rhythm is flagged for physician review through the LIVMOR HeartView physician portal.

The use of prescription digital therapeutics for diagnostic applications is considered EXPERIMENTAL/INVESTIGATIVE for all indications due to the lack of clinical evidence demonstrating an impact on improved health outcomes. 

Summary of Evidence

Two publications analyzing data from the same study addressed the clinical validity (i.e., diagnostic accuracy) of the Canvas Dx digital therapeutics system; however, no trials evaluating clinical utility (i.e., impact on diagnostic decision making or health outcomes) for its use in the diagnosis of autism spectrum disorder (ASD) were identified. No systematic reviews, clinical practice guidelines, or position statements specifically addressing the Canvas Dx were identified. Additionally, there is no published peer-reviewed evidence for Halo AF Detection System. Overall, there is a lack of clinical evidence evaluating digital therapeutics for diagnostic applications and their impact on improved health outcomes.

Rationale

Two studies on diagnostic performance of Canvas Dx have been published. The first study by Abbas et al. (2020) reported on the technical development and performance of the Canvas Dx (formerly known as Cognoa App) for diagnosing ASD. The second study by Megerian (2022) was a double-blind, multicenter, prospective, comparator cohort study testing the diagnostic accuracy of Canvas Dx in a primary care setting. The study compared Canvas Dx output to diagnostic agreement by 2 or more independent specialists in a cohort of 18 to 72-month-olds with developmental delay concerns. A total of 711 participants were enrolled and 425 completed both the device input and specialist evaluation component of the study between August 2019 and June 2020. The majority of study participants (68% or 290/425) were classified as “indeterminates” by Canvas DX. Major limitations include the lack of clarity on how the test fits into the current treatment pathway, and the appropriate referral process for testing. It is unclear if Canvas Dx is a "rule-out" or "rule-in" test, or perhaps both. Major limitations in the design and conduct of the study include missing data and lack of generalizability. As per the protocol, the study planned to enroll 725 participants between the ages of ≥18 months and <72 months of age from 30 clinical sites within the United States. However, 711 participants were enrolled from 14 sites across 6 states. Of these, 425 completed both the device input and specialist evaluation component of the study and were included in the final analysis. The estimated dropout rate was 40%. No clear description of reasons for discrepancy in the number of clinical sites (30 proposed sites versus 14 actual sites), characteristics of missing observations, or sensitivity analyses of missing data assumptions were provided. Issues related to the generalizability of the study findings were also noted. Data on participants stratified by enrollment sites/states and origin of primary concern for developmental delay (whether it was patient/caregiver or healthcare professional) were not reported. Commentary on these issues is needed to fully interpret the study findings.

No published, peer-reviewed evidence for the Halo AF Detection System was identified.

The CDC has provided screening and diagnosis tool recommendations for the diagnosis of ASD for healthcare providers. The commonly used tools include Evidence-based screening tools that incorporate parent reports (e.g., Ages and Stages Questionnaire, the Parents’ Evaluation of Developmental Status, and Child Development Inventories) and diagnostic tools which usually rely on parents’ or caregivers’ descriptions of their child’s development and a professional’s observation of the child’s behavior. The Canvas Dx is not highlighted in this communication.

Reference List

1.   Policy for Device Software Functions and Mobile Medical Applications   Guidance for Industry and Food and Drug Administration Staff Document issued on September 28, 2022.

2.   U.S. Food and Drug Administration, FDA News Release. FDA Authorizes Marketing of Diagnostic Aid for Autism Spectrum Disorder. June 2021. Available at: https://www.fda.gov/news-events/press-announcements/fda-authorizes-marketing-diagnostic-aid-autism-spectrum-disorder

3.   U.S. Food and Drug Administration, 501(k) Premarket Notification. Halo AF Detection System. September 23, 2020. Available at: https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/pmn.cfm?ID=K201208

4.   Abbas H, Garberson F, Liu-Mayo S, et al. Multi-modular AI Approach to Streamline Autism Diagnosis in Young Children. Sci Rep. Mar 19 2020; 10(1): 5014. PMID 32193406

5.   Megerian JT, Dey S, Melmed RD, et al. Evaluation of an artificial intelligence-based medical device for diagnosis of autism spectrum disorder. NPJ Digit Med. May 05 2022; 5(1): 57. PMID 35513550

6.   NIH: U.S. National Library of Medicine. ClinicalTrials.gov.

7.   Hayes Evolving Evidence Review Canvas Dx (Cogna Inc.) for Diagnosis of Autism Spectrum Disorder. October 2021. Available at: https://evidence.hayesinc.com/report/eer.canvasdx5180

8.   Center for Disease Control and Prevention (CDC). Autism spectrum disorder (ASD) screening and diagnosis. February 11, 2020. Available at: https://www.cdc.gov/ncbddd/autism/hcp-screening.html#DiagnosticTools. Accessed September 28, 2023. 

9.     Autism Spectrum Disorder: Links to Commonly Used Screening Instruments and Tools (AAP Toolkits). American Academy of Pediatrics. Available at Autism Toolkit | AAP Toolkits | American Academy of Pediatrics Assessed on September 22, 2023.