Evidence map›Paper›PMID 28346074›Full record

ReviewPharmacogenomics2017

Germline genetic predictors of aromatase inhibitor concentrations, estrogen suppression and drug efficacy and toxicity in breast cancer patients.

Daniel L Hertz, N Lynn Henry, James M Rae

Open access · greenAbstract readReview
In one paragraph

Review in Pharmacogenomics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed, 2 pooled it
3.3field-weighted citation impact, top 8% 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

27 citing papers in PubMed, 2 syntheses or guidelines pooled it, 37 citations in OpenAlex.

  1. Pooled it
  2. Genetic Variation and Hot Flashes: A Systematic Review.The Journal of clinical endocrinology and metabolism · 2020
    Pooled it
  3. Genome-wide association study of aromatase inhibitor discontinuation due to musculoskeletal symptoms.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2022
    Trial
  4. Effects ofPharmacogenomics · 2019
    Trial
  5. Prevalence and predictive testing preferences for breast cancer treatment side effects.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2025
    Article
  6. Article
  7. Review
  8. Article
  9. Article
  10. Review
  11. Effects ofPharmacogenomics · 2023
    Article
  12. Observational
  13. Review
  14. Article
  15. Prevalence and correlates of joint pain among Chinese breast cancer survivors receiving aromatase inhibitor treatment.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2022
    Article
  16. Review
  17. Article
  18. Article
  19. Article
  20. 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

3 authors at 2 institutions in 1 country.

Daniel L HertzDepartment of Clinical Pharmacy, University of Michigan College of Pharmacy, Ann Arbor, MI 48109-1065, USA.
N Lynn HenryHuntsman Cancer Institute, University of Utah, Salt Lake City, UT 84103, USA.
James M RaeBreast Oncology Program, University of Michigan Comprehensive Cancer Center, Ann Arbor, MI 48109-1065, USA.
University of Michigan–Ann Arbor · USUniversity of Utah · US

Funding

Genetic Predictors of Anti-Estrogen Clinical Activity in Breast Cancer PatientsR01GM099143 · NIGMS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI RAE, JAMES MICHAEL · 2011 to 2015
$1.6M
NIGMS NIH HHS R01 GM099143
6 · The paper itself

Abstract

The third-generation aromatase inhibitors (AIs), anastrozole, letrozole and exemestane, are highly effective for the treatment of estrogen receptor-positive breast cancer in postmenopausal women. AIs inhibit the aromatase (CYP19A1)-mediated production of estrogens. Most patients taking AIs achieve undetectable blood estrogen concentrations resulting in drug efficacy with tolerable side effects. However, some patients have suboptimal outcomes, which may be due, in part, to inherited germline genetic variants. This review summarizes published germline genetic associations with AI treatment outcomes including systemic AI concentrations, estrogenic response to AIs, AI treatment efficacy and AI treatment toxicities. Significant associations are highlighted with commentary about prioritization for future validation to identify pharmacogenetic predictors of AI treatment outcomes that can be used to inform personalized treatment decisions in patients with estrogen receptor-positive breast cancer.

Indexed as

Adult Germline Stem CellsAnimalsAromataseAromatase InhibitorsBreast NeoplasmsEstrogensFemaleHormone AntagonistsHumansPredictive Value of TestsTreatment OutcomeAromataseAromatase InhibitorsCYP19A1 protein, humanEstrogensHormone Antagonistsaromatase inhibitorsefficacyestrogensGWASpharmacogeneticspharmacogenomicspharmacokineticsreviewtoxicity

Identifiers

PMID28346074
PMCPMC6219438
OpenAlexW2601601396

What OpenQuestion holds

Textmetadata
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.