Evidence map›Paper›PMID 34402895›Full record

ReviewEndocrinology2021

Sex Differences in Cancer Genomes: Much Learned, More Unknown.

Chenghao Zhu, Paul C Boutros

Open access · bronzeAbstract readReview
In one paragraph

Review in Endocrinology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
2.3field-weighted citation impact, top 11% 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

6 citing papers in PubMed, 18 citations in OpenAlex.

  1. Article
  2. Article
  3. Artificial Intelligence Bias in Health Care: Web-Based Survey.Journal of medical Internet research · 2023
    Article
  4. Article
  5. Article
  6. 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

2 authors at 1 institution in 1 country.

Chenghao ZhuDepartment of Human Genetics, University of California, Los Angeles, CA, USA.
Paul C BoutrosDepartment of Human Genetics, University of California, Los Angeles, CA, USA.ORCID 0000-0003-0553-7520
University of California, Los Angeles · US

Funding

Women's CancersP30CA016042 · NCI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI Samuel Wheeler French · 1985 to 2026
$134.5M
The Evolution of Sarcoma Drug Sensitivity through Time and SpaceR01CA244729 · NCI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI BOUTROS, PAUL CHRISTOPHER, SORAGNI, ALICE · 2020 to 2024
$3.4M
Development of Protein Biomarkers in Post-DRE Urine for use in Liquid Biopsy of Prostate CancerU01CA214194 · NCI · EASTERN VIRGINIA MEDICAL SCHOOL · PI BOUTROS, PAUL CHRISTOPHER, KISLINGER, THOMAS · 2016 to 2021
$2.5M
NCI NIH HHS P30 CA016042NCI NIH HHS R01 CA244729NCI NIH HHS U01 CA214194
6 · The paper itself

Abstract

Cancer is a leading cause of death worldwide. Sex influences cancer in a bewildering variety of ways. In some cancer types, it affects prevalence; in others, genomic profiles, response to treatment, or mortality. In some, sex seems to have little or no influence. How and when sex influences cancer initiation and progression remain a critical gap in our understanding of cancer, with direct relevance to precision medicine. Here, we note several factors that complicate our understanding of sex differences: representativeness of large cohorts, confounding with features such as ancestry, age, obesity, and variability in clinical presentation. We summarize the key resources available to study molecular sex differences and suggest some likely directions for improving our understanding of how patient sex influences cancer behavior.

Indexed as

Sex CharacteristicsAnimalsFemaleGenes, NeoplasmGenomicsHumansMaleNeoplasmsPrecision Medicinecancercancer genomicsgenomicssex difference

Identifiers

PMID34402895
PMCPMC8439393
OpenAlexW3194838568

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.