Evidence map›Paper›PMID 32718075›Full record

ReviewCancers2020

PET Imaging Agents (FES, FFNP, and FDHT) for Estrogen, Androgen, and Progesterone Receptors to Improve Management of Breast and Prostate Cancers by Functional Imaging.

John A Katzenellenbogen

Open access · goldAbstract readReview
In one paragraph

Review in Cancers, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
2.1field-weighted citation impact, top 10% 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

15 citing papers in PubMed, 29 citations in OpenAlex.

  1. Review
  2. Article
  3. Characterization of an Estrogen Receptor α-SelectiveWorld journal of nuclear medicine · 2024
    Article
  4. Article
  5. Review
  6. Article
  7. Review
  8. Review
  9. The influence ofHepatobiliary surgery and nutrition · 2022
    Article
  10. Breast surgery: a narrative review.The Medical journal of Australia · 2022
    Review
  11. Article
  12. Novel Tracers and Radionuclides in PET Imaging.Radiologic clinics of North America · 2021
    Review
  13. Clinical perspectives for the use of total body PET/CT.European journal of nuclear medicine and molecular imaging · 2021
    Article
  14. ZR-75-1 breast cancer models to study the utility ofTranslational cancer research · 2021
    Article
  15. 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

1 author at 1 institution in 1 country.

John A KatzenellenbogenDepartment of Chemistry and Cancer Center at Illinois, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA.
University of Illinois Urbana-Champaign · US

Funding

Breast Cancer Research Foundation BCRF 19-084NIH HHS CA015836NIH HHS CA220284
6 · The paper itself

Abstract

Many breast and prostate cancers are driven by the action of steroid hormones on their cognate receptors in primary tumors and in metastases, and endocrine therapies that inhibit hormone production or block the action of these receptors provide clinical benefit to many but not all of these cancer patients. Because it is difficult to predict which individuals will be helped by endocrine therapies and which will not, positron emission tomography (PET) imaging of estrogen receptor (ER) and progesterone receptor (PgR) in breast cancer, and androgen receptor (AR) in prostate cancer can provide useful, often functional, information on the likelihood of endocrine therapy response in individual patients. This review covers our development of three PET imaging agents, 16α-[

Indexed as

breast cancerendocrine therapyFDHTFESFFNPhormone-challenge testPET imagingprostate cancerradiopharmaceuticalsreceptor-targeting

Identifiers

PMID32718075
PMCPMC7465097
OpenAlexW3044161789

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.