Evidence map›Paper›PMID 35146485›Full record

ArticleFrontiers in digital health2021

Redefining and Validating Digital Biomarkers as Fluid, Dynamic Multi-Dimensional Digital Signal Patterns.

Rhoda Au, Vijaya B Kolachalama, Ioannis C Paschalidis

Open access · goldAbstract read
In one paragraph

Article in Frontiers in digital health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
5.1field-weighted citation impact, top 4% of its field
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

13 citing papers in PubMed, 20 citations in OpenAlex.

  1. Article
  2. Review
  3. Review
  4. Article
  5. Review
  6. Reinventing "N" in the A/T/N framework: The case for digital.The journal of prevention of Alzheimer's disease · 2025
    Article
  7. Review
  8. Review
  9. Article
  10. Article
  11. Machine Learning in Clinical Trials: A Primer with Applications to Neurology.Neurotherapeutics : the journal of the American Society for Experimental NeuroTherapeutics · 2023
    Review
  12. Article
  13. Communicating and Using Dementia Risk Evidence.Journal of Alzheimer's disease : JAD · 2022
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors at 2 institutions in 1 country.

Rhoda AuDepartment of Anatomy and Neurobiology, Neurology and Framingham Heart Study, Boston University School of Medicine, Boston, MA, United States.
Vijaya B KolachalamaBoston University Alzheimer's Disease Center, Boston, MA, United States.
Ioannis C PaschalidisFaculty of Computing and Data Sciences, Boston University, Boston, MA, United States.
Boston University · USFramingham Heart Study · US

Funding

TBDU19AG068753 · NIA · BOSTON UNIVERSITY MEDICAL CAMPUS · PI Rhoda Au · 2020 to 2026
$42.4M
South Texas Alzheimer's Disease Research CenterP30AG066546 · NIA · UNIVERSITY OF TEXAS HLTH SCIENCE CENTER · PI Mohamad Habes · 2021 to 2026
$24.0M
MRI, Genetics &Cognitive Precursors of AD &DementiaR01AG016495 · NIA · BOSTON UNIVERSITY MEDICAL CAMPUS · PI AU, RHODA · 1999 to 2016
$12.5M
Temporal Trends, Novel Imaging and Molecular Characterization of Preclinical and Clinical Alzheimer's Disease in the Framingham CohortsR01AG054076 · NIA · UNIVERSITY OF TEXAS HLTH SCIENCE CENTER · PI DECARLI, CHARLES, SESHADRI, SUDHA · 2016 to 2020
$12.3M
MRI, Cognitive, Genetic & Biomarker Precursors of AD & Dementia in Young AdultsR01AG033040 · NIA · BOSTON UNIVERSITY MEDICAL CAMPUS · PI AU, RHODA, SESHADRI, SUDHA · 2009 to 2019
$11.2M
Precision Brain Health Monitoring for Alzheimer's Disease Risk Detection in the Framingham Study: Black & AA Recruitment SupplementRF1AG072654 · NIA · BOSTON UNIVERSITY MEDICAL CAMPUS · PI AU, RHODA, GOLDSTEIN, LEE E. · 2021 to 2023
$2.4M
Cognitive Heterogeneity in those with high Alzheimer's Disease RiskRF1AG062109 · NIA · BOSTON UNIVERSITY MEDICAL CAMPUS · PI AU, RHODA · 2020 to 2021
$1.8M
Cognitive heterogeneity in those with high Alzheimer's Disease RiskR56AG062109 · NIA · BOSTON UNIVERSITY MEDICAL CAMPUS · PI AU, RHODA · 2018 to 2018
$517k
NIA NIH HHS P30 AG066546NIA NIH HHS R01 AG016495NIA NIH HHS R01 AG033040NIA NIH HHS R01 AG054076NIA NIH HHS R56 AG062109NIA NIH HHS RF1 AG062109NIA NIH HHS RF1 AG072654NIA NIH HHS U19 AG068753
6 · The paper itself

Abstract

"Digital biomarker" is a term broadly and indiscriminately applied and often limited in its conceptualization to mimic well-established biomarkers as defined and approved by regulatory agencies such as the United States Food and Drug Administration (FDA). There is a practical urgency to revisit the definition of a digital biomarker and expand it beyond current methods of identification and validation. Restricting the promise of digital technologies within the realm of currently defined biomarkers creates a missed opportunity. A whole new field of prognostic and early diagnostic digital biomarkers driven by data science and artificial intelligence can break the current cycle of high healthcare costs and low health quality that is being driven by today's chronic disease detection and treatment approaches. This new class of digital biomarkers will be dynamic and require developing new FDA approval pathways and next-generation gold standards.

Indexed as

biomarkersdigitaldigital biomarkersfluidic dynamic digital patternsnew regulatory standardstechnology

Identifiers

PMID35146485
PMCPMC8822623
OpenAlexW4206591569

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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 OpenQuestion graph.