Evidence map›Paper›PMID 22608383›Full record

ArticleAmerican journal of preventive medicine2012

A population approach to precision medicine.

Muin J Khoury, Marta L Gwinn, Russell E Glasgow, Barnett S Kramer

Open access · greenAbstract read
In one paragraph

Article in American journal of preventive medicine, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 70 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
70citing papers in PubMed, 2 pooled it
7.6field-weighted citation impact, top 2% 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

70 citing papers in PubMed, 2 syntheses or guidelines pooled it, 159 citations in OpenAlex.

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  15. Malmö Breast ImaginG database: objectives and development.Journal of medical imaging (Bellingham, Wash.) · 2023
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10 more citing papers are in PubMed but not listed here.

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 2 institutions in 1 country.

Muin J KhouryOffice of Public Health Genomics, CDC, Atlanta, GA 30333, USA. muk1@cdc.gov
Marta L Gwinn
Russell E Glasgow
Barnett S Kramer
National Cancer Institute · USOffice of Public Health Genomics · US

Funding

Intramural NIH HHS Z99 CA999999NCI NIH HHS Y99 CA999999
6 · The paper itself

Abstract

The term P4 medicine is used to denote an evolving field of medicine that uses systems biology approaches and information technologies to enhance wellness rather than just treat disease. Its four components include predictive, preventive, personalized, and participatory medicine. In the current paper, it is argued that in order to fulfill the promise of P4 medicine, a "fifth P" must be integrated-the population perspective-into each of the other four components. A population perspective integrates predictive medicine into the ecologic model of health; applies principles of population screening to preventive medicine; uses evidence-based practice to personalize medicine; and grounds participatory medicine on the three core functions of public health: assessment, policy development, and assurance. Population sciences-including epidemiology; behavioral, social, and communication sciences; and health economics, implementation science, and outcomes research-are needed to show the value of P4 medicine. Balanced strategies that implement both population- and individual-level interventions can best maximize health benefits, minimize harm, and avoid unnecessary healthcare costs.

Indexed as

Public HealthClinical ProtocolsDelivery of Health Care, IntegratedEvidence-Based MedicineHumansMass ScreeningModels, TheoreticalPrimary PreventionPublic Health PracticeUnited States

Identifiers

PMID22608383
PMCPMC3629731
OpenAlexW2134319420

What OpenQuestion holds

Textmetadata
LicenceTDM
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.