Evidence map›Paper›PMID 29707260›Full record

ReviewJournal of clinical and translational science2017

Can composite digital monitoring biomarkers come of age? A framework for utilization.

Christopher Kovalchick, Rhea Sirkar, Oliver B Regele, Lampros C Kourtis, Marie Schiller, Howard Wolpert, Rhett G Alden, Graham B Jones, Justin M Wright

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Journal of clinical and translational science, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–field-weighted citation impact
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

9 citing papers in PubMed.

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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

9 authors.

Christopher KovalchickEli Lilly Innovation Center, Cambridge, MA, USA.
Rhea SirkarEli Lilly Innovation Center, Cambridge, MA, USA.
Oliver B RegeleEli Lilly Innovation Center, Cambridge, MA, USA.
Lampros C KourtisEli Lilly Innovation Center, Cambridge, MA, USA.
Marie SchillerEli Lilly Innovation Center, Cambridge, MA, USA.
Howard WolpertEli Lilly Innovation Center, Cambridge, MA, USA.
Rhett G AldenEli Lilly Innovation Center, Cambridge, MA, USA.
Graham B JonesClinical & Translational Science Institute, Tufts University Medical Center, Boston, MA, USA.ORCID 0000-0003-2195-3567
Justin M WrightEli Lilly Innovation Center, Cambridge, MA, USA.

Funding

Tufts Clinical and Translational Research InstituteUL1TR001064 · NCATS · TUFTS UNIVERSITY BOSTON · PI SELKER, HARRY P. · 2013 to 2017
$26.4M
NCATS NIH HHS UL1 TR001064
6 · The paper itself

Abstract

introductionThe application of digital monitoring biomarkers in health, wellness and disease management is reviewed. Harnessing the near limitless capacity of these approaches in the managed healthcare continuum will benefit from a systems-based architecture which presents data quality, quantity, and ease of capture within a decision-making dashboard.

methodsA framework was developed which stratifies key components and advances the concept of contextualized biomarkers. The framework codifies how direct, indirect, composite, and contextualized composite data can drive innovation for the application of digital biomarkers in healthcare.

resultsThe de novo framework implies consideration of physiological, behavioral, and environmental factors in the context of biomarker capture and analysis. Application in disease and wellness is highlighted, and incorporation in clinical feedback loops and closed-loop systems is illustrated.

conclusionsThe study of contextualized biomarkers has the potential to offer rich and insightful data for clinical decision making. Moreover, advancement of the field will benefit from innovation at the intersection of medicine, engineering, and science. Technological developments in this dynamic field will thus fuel its logical evolution guided by inputs from patients, physicians, healthcare providers, end-payors, actuarists, medical device manufacturers, and drug companies.

Indexed as

biomarkersclosed loopDigital medicineIoTsensors

Identifiers

PMID29707260
PMCPMC5916505

What OpenQuestion holds

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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.