Evidence map›Paper›PMID 29137948›Full record

ReviewThe American journal of pathology2018

Analysis of Tumor Biology to Advance Cancer Health Disparity Research.

Cheryl J Smith, Tsion Z Minas, Stefan Ambs

Abstract readReview
In one paragraph

Review in The American journal of pathology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed
–field-weighted citation impact
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

23 citing papers in PubMed.

  1. Review
  2. Current trends and future directions of artificial intelligence in lung cancer diagnosis.Chinese journal of cancer research = Chung-kuo yen cheng yen chiu · 2026
    Article
  3. Article
  4. Article
  5. Article
  6. Towards equitable AI in oncology.Nature reviews. Clinical oncology · 2024
    Review
  7. Article
  8. Article
  9. Review
  10. Research Silos in Cancer Disparities: Obstacles to Improving Clinical Outcomes for Underserved Patient Populations.Clinical cancer research : an official journal of the American Association for Cancer Research · 2023
    Article
  11. Biomarkers of Aggressive Prostate Cancer at Diagnosis.International journal of molecular sciences · 2023
    Review
  12. Article
  13. Review
  14. Molecular cancer research : MCR · 2021
    Article
  15. Aspirin Use and Prostate Cancer among African-American Men in the Southern Community Cohort Study.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2021
    Article
  16. Article
  17. Genetics of Smoking Behaviors in American Indians.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2020
    Article
  18. Article
  19. Article
  20. 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

3 authors.

Cheryl J SmithLaboratory of Human Carcinogenesis, Center of Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland.
Tsion Z MinasLaboratory of Human Carcinogenesis, Center of Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland.
Stefan AmbsLaboratory of Human Carcinogenesis, Center of Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland. Electronic address: ambss@mail.nih.gov.

Funding

Novel Markers for Disease Outcome in Breast CancerZIABC010887 · NCI · DIVISION OF BASIC SCIENCES - NCI · PI AMBS, STEFAN · 2009 to 2025
$11.5M
Maryland Prostate Cancer Case-Control StudyZIABC010499 · NCI · DIVISION OF BASIC SCIENCES - NCI · PI AMBS, STEFAN · 2009 to 2025
$11.4M
The Molecular Profile of Prostate Tumors in African-American MenZIABC010624 · NCI · DIVISION OF BASIC SCIENCES - NCI · PI AMBS, STEFAN · 2009 to 2025
$8.0M
Intramural NIH HHS ZIA BC010499Intramural NIH HHS ZIA BC010624Intramural NIH HHS ZIA BC010887
6 · The paper itself

Abstract

Cancer mortality rates in the United States continue to decline. Reductions in tobacco use, uptake of preventive measures, adoption of early detection methods, and better treatments have resulted in improved cancer outcomes for men and women. Despite this progress, some population groups continue to experience an excessive cancer burden when compared with other population groups. One of the most prominent cancer health disparities exists in prostate cancer. Prostate cancer mortality rates are highest among men of African ancestry when compared with other men, both in the United States and globally. This disparity and other cancer health disparities are largely explained by differences in access to health care, diet, lifestyle, cultural barriers, and disparate exposures to carcinogens and pathogens. Dietary and lifestyle factors, pathogens, and ancestry-related factors can modify tumor biology and induce a more aggressive disease. There are numerous examples of how environmental exposures, like tobacco, chronic stress, or dietary factors, induce an adverse tumor biology, leading to a more aggressive disease and decreased patient survival. Because of population differences in the exposure to these risk factors, they can be the cause of cancer disparities. In this review, we will summarize recent advances in our understanding of prostate and breast cancer disparities in the United States and discuss how the analysis of tumor biology can advance health disparity research.

Indexed as

Health Status DisparitiesBiomedical ResearchBlack or African AmericanBreast NeoplasmsEpigenomicsFemaleGenetic Predisposition to DiseaseHumansMaleNeoplasmsProstatic NeoplasmsUnited States

Identifiers

PMID29137948
PMCPMC5785533

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.