Evidence map›Paper›PMID 28815101›Full record

ArticleAMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science2017

Characterizing the Strength of Evidence in FDA Labels for Pharmacogenomic Biomarker-Guided Medication Use.

Lauren Chin, Beth Devine, Sarah Baradaran, Katelyn Keyloun, William Canestaro, Jonathan Pham

Abstract read
In one paragraph

Article in AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

6 authors.

Lauren ChinPharmaceutical Outcomes Research and Policy Program, Department of Pharmacy.
Beth DevinePharmaceutical Outcomes Research and Policy Program, Department of Pharmacy.
Sarah BaradaranPharmaceutical Outcomes Research and Policy Program, Department of Pharmacy.
Katelyn KeylounPharmaceutical Outcomes Research and Policy Program, Department of Pharmacy.
William CanestaroPharmaceutical Outcomes Research and Policy Program, Department of Pharmacy.
Jonathan PhamPharmaceutical Outcomes Research and Policy Program, Department of Pharmacy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

There is great heterogeneity in drug treatment response that is thought to be due to individual-level allelic variation in pharmacogenomic biomarkers. FDA Drug Labels provide information to guide pharmacogenomic biomarker use. Yet, the strength of evidence for clinical validity and clinical utility is lacking. We characterized the strength of evidence and treatment recommendations contained in FDA Drug Labels as of December 2015. Pharmacogenomic biomarker information was provided for 137 drugs, involving 49 pharmacogenomic biomarkers, constituting 166 drug-biomarker pairs. Convincing/adequate evidence of clinical validity was found for 46% of pairs, of clinical utility for 29% of pairs, and of both, for 27% of pairs. Despite evidence of convincing/adequate validity/utility, no treatment recommendation was provided for 37% of pairs. Germline biomarkers represented nearly three-quarters of all drug-biomarker pairs, however, only 29% and 16% of pairs had convincing/adequate evidence for clinical validity and clinical utility, respectively. Separately, somatic biomarkers that serve as molecular targets for targeted therapies, had convincing/adequate evidence for 95% of pairs for clinical validity, and for 67% for clinical utility. The strength of evidence for pharmacogenomic biomarker use is low, underscoring the need for additional research to achieve the promise of precision medicine.

Identifiers

PMID28815101
PMCPMC5543369

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Registered trials

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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.