ArticleCureus2025
The Composite Digital Therapeutic Index (cDTI): A Multidimensional Framework and Proof-of-Concept Application to FDA-Authorized Treatments.
Article in Cureus, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction Prescription digital therapeutics (PDTs) are an emerging class of regulated software-based interventions with increasing FDA authorizations. However, there is no standardized framework to evaluate and benchmark their overall therapeutic value. We aimed to develop and validate a Composite Digital Therapeutic Index (cDTI) framework. This proof-of-concept application integrates efficacy, engagement, quality of evidence, and safety profile from registrational trials to compare PDTs using publicly available regulatory summaries, registries, and study readouts. Methods We developed a scoring framework incorporating four domains (efficacy, engagement, evidence quality, and safety), each quantified and combined into a composite index. Efficacy was calculated using standardized mean difference (SMD; Hedges' g) adjusted for statistical significance. Engagement was based on the mean proportion of patients achieving therapeutic module completion. Evidence quality was graded using an adapted American Academy of Neurology Class of Evidence framework. Safety was assessed based on treatment-emergent adverse events (TEAEs) using a hierarchical penalty system. In a proof-of-concept application of the framework, we applied cDTI to two FDA-cleared first- and second-generation PDTs, reSET-O for opioid use disorder (Pear Therapeutics, Boston, MA, USA) and CT-132 for episodic migraine (Click Therapeutics, New York, NY, USA), respectively. Results CT-132 achieved a cDTI score of 0.296, substantially (1287%) higher than reSET-O, which scored 0.023. CT-132's superior performance was driven by a statistically significant efficacy outcome (adjusted SMD 0.33), high engagement (89.7%), Class I evidence quality with sham and double-blind, and no treatment-related adverse events. In contrast, reSET-O showed a non-significant primary outcome (adjusted SMD 0.0895), moderate engagement (63.0%), Class III evidence quality without patient blind and usual-care control, and missing systematic safety reporting requiring a conservative penalty. Discussion The cDTI successfully differentiated the overall therapeutic profiles of two PDTs across multiple clinical and usability domains. This multidimensional approach highlights how digital therapeutics with similar regulatory status can differ meaningfully in trial quality, efficacy, engagement, and safety. The cDTI offers a transparent, reproducible method for comparing PDTs and may aid stakeholders including providers, payers, regulators, and patients in decision-making about digital therapeutic adoption and coverage. Conclusion The cDTI provides a reproducible framework to evaluate PDTs based on clinical, usability, and safety parameters. Future work aims to expand the framework across all FDA-cleared PDTs and explore incorporation of real-world effectiveness, equity, and cost-effectiveness domains.
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