Evidence map›Paper›PMID 35761336›Full record

ReviewCancer cell international2022

Advances in biomarkers and techniques for pancreatic cancer diagnosis.

Haotian Wu, Suwen Ou, Hongli Zhang, Rui Huang, Shan Yu, Ming Zhao, Sheng Tai

Abstract readReview
In one paragraph

Review in Cancer cell international, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.

0numbers the graph read from it
0cells of the map it votes in
30citing 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

30 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Review
  7. Review
  8. Article
  9. Article
  10. Review
  11. Article
  12. Article
  13. Review
  14. Review
  15. Review
  16. Article
  17. Article
  18. Review
  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

7 authors.

Haotian Wu *Department of General Surgery, The Second Affiliated Hospital of Harbin Medical University, Harbin, 150086, China.
Suwen Ou *Department of General Surgery, The Second Affiliated Hospital of Harbin Medical University, Harbin, 150086, China.
Hongli ZhangHarbin Medical University, Harbin, 150086, China.
Rui HuangDepartment of General Surgery, The Second Affiliated Hospital of Harbin Medical University, Harbin, 150086, China.
Shan YuDepartment of Pathology, The Second Affiliated Hospital of Harbin Medical University, Harbin, 150086, China. yushan@hrbmu.edu.cn.
Ming ZhaoDepartment of Gastroenterology, The First Affiliated Hospital of Chengdu Medical College, Sichuan, 610500, China. zhaoming24@126.com.
Sheng TaiDepartment of General Surgery, The Second Affiliated Hospital of Harbin Medical University, Harbin, 150086, China. taisheng1973@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Pancreatic cancer is the most lethal type of malignancy and is characterized by high invasiveness without severe symptoms. It is difficult to detect PC at an early stage because of the low diagnostic accuracy of existing routine methods, such as abdominal ultrasound, CT, MRI, and endoscopic ultrasound (EUS). Therefore, it is of value to develop new diagnostic techniques for early detection with high accuracy. In this review, we aim to highlight research progress on novel biomarkers, artificial intelligence, and nanomaterial applications on the diagnostic accuracy of pancreatic cancer.

Indexed as

Artificial intelligenceBiomarkersDiagnosisNanomaterialsPancreatic cancer

Identifiers

PMID35761336
PMCPMC9237966

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.