Evidence map›Paper›PMID 35860831›Full record

ReviewTherapeutic advances in medical oncology2022

Prognostic/predictive markers in systemic therapy resistance and metastasis in breast cancer.

Evthokia A Hobbs, Natalie Chen, Alphi Kuriakose, Elizabeth Bonefas, Bora Lim

Open access · goldAbstract readReview
In one paragraph

Review in Therapeutic advances in medical oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.7field-weighted citation impact, top 28% 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

5 citing papers in PubMed, 9 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. Review
  5. 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

5 authors at 2 institutions in 1 country.

Evthokia A HobbsHematology and Oncology, Oregon Health & Science University, Portland, OR, USA.
Natalie ChenHematology and Oncology, Baylor College of Medicine, Houston, TX, USA.
Alphi KuriakoseLester and Sue Smith Breast Center, Baylor College of Medicine, Houston, TX, USA.
Elizabeth BonefasSurgical Oncology, Baylor College of Medicine, Houston, TX, USA.
Bora LimHematology and Oncology, Baylor College of Medicine, One Baylor Plaza, BCM600, Houston, TX 70030, USA.ORCID https://orcid.org/0000-0002-4182-6058
Baylor College of Medicine · USOregon Health & Science University · US

Funding

TRAINING FOR ACADEMIC ONCOLOGY/HEMATOLOGYT32CA009666 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI Michael Davies, Courtney DiNardo · 1994 to 2026
$9.8M
NCI NIH HHS T32 CA009666
6 · The paper itself

Abstract

Breast cancer is a highly heterogeneous group of diseases posing a significant challenge in biomarker-driven research and the development of effective targeted therapies. Especially the treatment of metastatic breast cancer poses even more challenges, as we still lose more than 42,000 women and men each year in the United States alone. New biological insight helps to improve breast cancer treatment through early detection, adaptation to chemotherapy resistance, and tailoring to find the right size of care. This review focuses on existing and new areas of predictive biomarkers under development to tailor the management of breast cancer and the application of integrative approaches that have resulted in the promising candidate biomarker discovery. Furthermore, we review new methods to detect metastatic progression using imaging, and blood-based assays. We hope to increase the attention and awareness of a new generation of therapeutic development strategies in metastatic breast cancer.

Indexed as

biomarkersemerging therapy resistancemetastatic breast cancertranslational research

Identifiers

PMID35860831
PMCPMC9290149
OpenAlexW4285613640

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.