Evidence map›Paper›PMID 31281485›Full record

ArticleJournal of Cancer2019

Clinicopathological and prognostic significance of programmed death ligand 1 expression in Korean melanoma patients.

Sumi Yun, Yujun Park, Seyoung Moon, Soomin Ahn, Kyoungyul Lee, Hyo Jin Park, Hye Seung Lee, Gheeyoung Choe, Kyu Sang Lee

Abstract read
In one paragraph

Article in Journal of Cancer, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 1 pooled it
–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

12 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Article
  4. Review
  5. Review
  6. Review
  7. Article
  8. Article
  9. Review
  10. Article
  11. Article
  12. 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

9 authors.

Sumi YunDepartment of Diagnostic Pathology, Samkwang Medical Laboratories, Seoul, Republic of Korea.
Yujun ParkDepartment of Pathology, Seoul National University Bundang Hospital, Seongnam-si, Gyeonggi-do, Republic of Korea.
Seyoung MoonDepartment of Pathology, Seoul National University Bundang Hospital, Seongnam-si, Gyeonggi-do, Republic of Korea.
Soomin AhnDepartment of Pathology, Seoul National University Bundang Hospital, Seongnam-si, Gyeonggi-do, Republic of Korea.
Kyoungyul LeeDepartment of Pathology, Kangwon National University Hospital, Chuncheon-Si, Kangwon-Do, Republic of Korea.
Hyo Jin ParkDepartment of Pathology, Sheikh Khalifa Specialty Hospital, Ras al Khaimah, United Arab Emirates.
Hye Seung LeeDepartment of Pathology, Seoul National University Bundang Hospital, Seongnam-si, Gyeonggi-do, Republic of Korea.
Gheeyoung ChoeDepartment of Pathology, Seoul National University Bundang Hospital, Seongnam-si, Gyeonggi-do, Republic of Korea.
Kyu Sang LeeDepartment of Pathology, Seoul National University Bundang Hospital, Seongnam-si, Gyeonggi-do, Republic of Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Programmed death ligand 1 (PD-L1) expression provides significant value to predict prognosis and response following immunotherapy in several types of cancers. However, its clinicopathological and prognostic significance in melanoma remains unclear. PD-L1 and the number of tumor infiltrating lymphocytes (TILs) were investigated in 63 Korean patients with melanoma based on the melanoma scoring system. We also compared the results using the PD-L1 antibodies-22C3 and E1L3N clones. In addition,

Indexed as

22C3melanomaprognosisprogrammed death ligand 1tumor infiltrating lymphocytes

Identifiers

PMID31281485
PMCPMC6590033

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.