Evidence map›Paper›PMID 33114567›Full record

ReviewGenes2020

Digital Health Applications for Pharmacogenetic Clinical Trials.

Hetanshi Naik, Latha Palaniappan, Euan A Ashley, Stuart A Scott

Open access · goldAbstract readReview
In one paragraph

Review in Genes, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.3field-weighted citation impact, top 14% 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

4 citing papers in PubMed, 12 citations in OpenAlex.

  1. Review
  2. Review
  3. Article
  4. Review
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

4 authors at 3 institutions in 1 country.

Hetanshi NaikDepartment of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.ORCID 0000-0002-5894-7390
Latha PalaniappanDepartment of Medicine, Stanford University Medical Center, Palo Alto, CA 94305, USA.
Euan A AshleyDepartment of Medicine, Genetics, and Biomedical Data Science, Stanford University Medical Center, Palo Alto, CA 94305, USA.
Stuart A ScottDepartment of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.ORCID 0000-0001-5720-1864
Stanford Health Care · USIcahn School of Medicine at Mount Sinai · USStanford Medicine · US

Funding

META - Mentor, Educate, Train, Advocate: Patient Oriented Researchers in Cardiometabolic DiseaseK24HL150476 · NHLBI · STANFORD UNIVERSITY · PI Latha P Palaniappan · 2020 to 2026
$846k
NHLBI NIH HHS K24 HL150476
6 · The paper itself

Abstract

Digital health (DH) is the use of digital technologies and data analytics to understand health-related behaviors and enhance personalized clinical care. DH is increasingly being used in clinical trials, and an important field that could potentially benefit from incorporating DH into trial design is pharmacogenetics. Prospective pharmacogenetic trials typically compare a standard care arm to a pharmacogenetic-guided therapeutic arm. These trials often require large sample sizes, are challenging to recruit into, lack patient diversity, and can have complicated workflows to deliver therapeutic interventions to both investigators and patients. Importantly, the use of DH technologies could mitigate these challenges and improve pharmacogenetic trial design and operation. Some DH use cases include (1) automatic electronic health record-based patient screening and recruitment; (2) interactive websites for participant engagement; (3) home- and tele-health visits for patient convenience (e.g., samples for lab tests, physical exams, medication administration); (4) healthcare apps to collect patient-reported outcomes, adverse events and concomitant medications, and to deliver therapeutic information to patients; and (5) wearable devices to collect vital signs, electrocardiograms, sleep quality, and other discrete clinical variables. Given that pharmacogenetic trials are inherently challenging to conduct, future pharmacogenetic utility studies should consider implementing DH technologies and trial methodologies into their design and operation.

Indexed as

Computational BiologyHumansMedical InformaticsPattern Recognition, AutomatedPharmacogeneticsPharmacogenomic TestingPrecision MedicineTelemedicineWearable Electronic Devicesclinical trialsdigital healthhealth information technologypersonalized medicinepharmacogeneticstelehealthwearable devices

Identifiers

PMID33114567
PMCPMC7692850
OpenAlexW3095822456

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.