Evidence map›Paper›PMID 35572056›Full record

ArticleApplied bionics and biomechanics2022

A Novel Prognostic Stratified System Based on Tumor Budding and the Cell Nest Size in Ureter Urothelial Carcinoma.

Jialin Li, Xinyue Li, Jing Yang

RetractedOpen access · goldAbstract readRetracted Publication
In one paragraph

Article in Applied bionics and biomechanics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It has been retracted, and should not be counted. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.9field-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

3 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
  2. Article
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors at 1 institution in 1 country.

Jialin LiDepartment of Pathology, Jinzhou Medical University, Jinzhou, Liaoning, 40 Songpo Road, Linghe District, Jinzhou, Liaoning, China.
Xinyue LiDepartment of Pathology, Jinzhou Medical University, Jinzhou, Liaoning, 40 Songpo Road, Linghe District, Jinzhou, Liaoning, China.
Jing YangDepartment of Pathology, Jinzhou Medical University, Jinzhou, Liaoning, 40 Songpo Road, Linghe District, Jinzhou, Liaoning, China.ORCID https://orcid.org/0000-0002-0438-6006
Jinzhou Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

At present, malignant tumor stratification based on the TNM stage is very important for predicting patient prognosis and selecting appropriate treatment. The prognostic factor of ureter urothelial carcinoma is mainly based on the stage according to AJCC (8th) TNM classification. None of the histomorphologic features is recommended to assess patient's prognosis. Recently, a novel three-tiered grading system based on tumor budding and the cell nest size (referred as TBNS system) has been applied to be highly prognostic for some squamous cell carcinomas, including esophageal, pulmonary, uterine cervix cancer, and endocervical endocarcinoma. In this study, we explored the application of this TBNS grading system in ureter urothelial carcinoma consisting 87 surgically resected cases and no neoadjuvant therapy. Tumor budding and the cell nest size were assessed and correlated with clinicopathological data and survival. The results showed that higher tumor budding, cell nest size, and TBNS grading system were strongly related to shorter overall survival (OS), disease-specific survival (DSS), and disease-free survival (DFS). Multivariate survival analysis showed the TBNS grading system to be closely related to the independent prognosis of DFS and DSS. In conclusion, the TBNS grading system based on tumor budding and cell nest size, if further validated, could satisfactorily predict the prognosis of uterine urothelial carcinoma and be applicable in routine pathologic description of this cancer type.

Identifiers

PMID35572056
PMCPMC9106466
OpenAlexW4229016140

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

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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.