Evidence map›Paper›PMID 19995676›Full record

ReviewJournal of clinical epidemiology2010

Expectations, validity, and reality in pharmacogenetics.

Nita A Limdi, David L Veenstra

Abstract readReview
In one paragraph

Review in Journal of clinical epidemiology, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
10.3field-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

16 citing papers in PubMed, 48 citations in OpenAlex.

  1. Review
  2. The art and science of drug titration.Therapeutic advances in drug safety · 2020
    Review
  3. Review
  4. Article
  5. Article
  6. Article
  7. Review
  8. Review
  9. Getting our priorities straight: a novel framework for stakeholder-informed prioritization of cancer genomics research.Genetics in medicine : official journal of the American College of Medical Genetics · 2013
    Article
  10. Building the evidence base for decision making in cancer genomic medicine using comparative effectiveness research.Genetics in medicine : official journal of the American College of Medical Genetics · 2012
    Review
  11. Article
  12. Article
  13. Article
  14. Review
  15. Article
  16. 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

2 authors at 2 institutions in 1 country.

Nita A LimdiDepartment of Neurology, University of Alabama at Birmingham, Birmingham, AL 35294-0021, USA. nlimdi@uab.edu
David L Veenstra
University of Alabama at Birmingham · USUniversity of Washington · US

Funding

Predictors of hemorrhage among patients on direct acting oral anticoagulantsR01HL092173 · NHLBI · UNIVERSITY OF ALABAMA AT BIRMINGHAM · PI LIMDI, NITA A · 2008 to 2023
$10.4M
Pharmacogenetic Optimization of Anticoagulation TherapyK23NS045598 · NINDS · UNIVERSITY OF ALABAMA AT BIRMINGHAM · PI LIMDI, NITA A · 2003 to 2007
$795k
NHLBI NIH HHS R01 HL092173NHLBI NIH HHS R01HL092173NINDS NIH HHS K23 NS045598NINDS NIH HHS K23NS45598OGDP CDC HHS GD000005OGDP CDC HHS U18 GD000005OGDP CDC HHS U18GD000005-01
6 · The paper itself

Abstract

In this review, we discuss the potential expectations, validity, predictive ability, and reality of pharmacogenetics in (1) titration of medication dose, (2) prediction of intended (efficacy) drug response, and (3) dose prediction of unintended (adverse) drug response. We expound on what these potential genetic predictors tell us and, more importantly, what they cannot tell us. Although pharmacogenetic markers have been hailed as promising tools, these proclamations are based mainly on associations rather than their evaluation as predictors. To put the expectations of the promise of pharmacogenetics in a realistic perspective, we review three examples. First, warfarin pharmacogenetics, wherein although the validity of the genetic variant dose is established and there is a validity of genetic variant-hemorrhage association, the clinical utility of testing is not clear. Second, the strong and clinically relevant HLA-Stevens-Johnson syndrome/toxic epidermal necrolysis association highlights the role of ethnicity. Third, the influence of CYP2D6 on tamoxifen efficacy, a model candidate with potential clinical utility but unclear validity. These examples highlight both the challenges and opportunities of pharmacogenomics. First, establishing a valid association between a genetic variation and drug response; second, doing so for a clinically meaningful outcome; and third, providing solid evidence or rationale for improvement in patient outcomes compared with current standard of care.

Indexed as

AnticoagulantsAntineoplastic Agents, HormonalCytochrome P-450 CYP2D6Dose-Response Relationship, DrugDrug MonitoringDrug-Related Side Effects and Adverse ReactionsGenetic VariationGenotypeHemorrhageHumansPharmacogeneticsPolymorphism, GeneticPrecision MedicineStevens-Johnson SyndromeTamoxifenWarfarinAnticoagulantsAntineoplastic Agents, HormonalCytochrome P-450 CYP2D6TamoxifenWarfarin

Identifiers

PMID19995676
PMCPMC2888890
OpenAlexW2078878055

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.