ReviewDigital biomarkers
Interpretation of Change in Novel Digital Measures: A Statistical Review and Tutorial.
Review in Digital biomarkers. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.
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
2 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Digital Technologies and Biomarkers for Locomotor Capacity Assessment in Older Adults: Systematic Review.Journal of medical Internet research · 2026Pooled it
- Putting Theory into Practice by Developing a Novel Digital Health Technology-Derived Endpoint in Sleep Quality.Digital biomarkersArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Novel clinical measures assessed by a digital health technology tool require thresholds to interpret change over time, such as the minimal clinically important difference. Establishing such thresholds is a key component of clinical validation, facilitating understanding of relevant treatment effects. Summary: Many of the approaches to derive interpretative thresholds for patient-reported outcomes can be applied to digital clinical measures. We present theoretical background to the use of interpretative thresholds, including the distinction between thresholds based on perceived importance versus measurement error, and thresholds for group- versus individual-level interpretations. We then review methods to estimate such thresholds, including anchor-based approaches. We illustrate the methods using data on cough frequency counts as measured by a wearable device in a clinical trial. Key Messages: This paper provides an overview of statistical methodologies to estimate thresholds for the interpretation of change.
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What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.