Clinical Evaluation of Digital Therapeutics: Present and Future / 대한의료정보학회지
Healthcare Informatics Research
; : 188-197, 2022.
Article
em En
| WPRIM
| ID: wpr-937627
Biblioteca responsável:
WPRO
ABSTRACT
Objectives@#Digital therapeutics (DTx) are software-based therapeutic interventions based on clinical evidence. Randomized clinical trials (RCTs) are often the source of clinical evidence, similar to conventional drugs or medical devices. However, novel approaches such as the use of real-world data or digital biomarkers are also utilized. This article aimed to review how DTx products have been clinically evaluated. @*Methods@#DTx products approved by the US Food and Drug Administration as of 2020 were reviewed and products with sufficient published information were selected. Pivotal clinical trials were analyzed according to the elements of the Consolidated Standards of Reporting Trials (CONSORT) guideline. Case reviews were presented for other clinical evaluation strategies, considering the small number of publications. @*Results@#Most approved DTx products used RCTs for clinical evaluations. Similar to conventional RCTs, parallel-group designs with statistical hypothesis testing were adopted. However, DTx trials were often not blinded due to practical issues and involved various comparator groups. In addition, DTx products could be readily evaluated in home-based settings and delivered through the internet. Other evaluation approaches included retrospective analyses using insurance claims data or usage data, which enabled long-term evaluations of effectiveness. Digital biomarkers obtained from real-time and continuous log data were also used to improve the objectiveness of endpoints. @*Conclusions@#RCTs accounted for the majority of DTx evaluations. The designs of DTx trials were comparable to those of drug or device trials, but blinding and comparator elements were often different. Furthermore, the use of real-world data and digital biomarkers are also being tried.
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1
Índice:
WPRIM
Tipo de estudo:
Clinical_trials
/
Guideline
Idioma:
En
Revista:
Healthcare Informatics Research
Ano de publicação:
2022
Tipo de documento:
Article