Evidence map›Paper›PMID 33585189›Full record

ArticleFrontiers in oncology2020

Molecular Pathological Markers Correlated With the Recurrence Patterns of Glioma.

Shunnan Ge, Yingwu Shi, Gang Zhu, Songlun Li, Yaning Cai, Peigang Ji, Jinghui Liu, Wei Guo, Li Gong, Miao Lou and 5 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in oncology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.7field-weighted citation impact, top 30% 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

1 citing paper in PubMed, 6 citations in OpenAlex.

  1. 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

15 authors at 2 institutions in 1 country.

Shunnan GeDepartment of Neurosurgery, Tangdu Hospital, Fourth Military Medical University, Xi'an, China.
Yingwu ShiDepartment of Neurosurgery, Tangdu Hospital, Fourth Military Medical University, Xi'an, China.
Gang ZhuDepartment of Neurosurgery, Tangdu Hospital, Fourth Military Medical University, Xi'an, China.
Songlun LiMedical Department of Tangdu Hospital, Fourth Military Medical University, Xi'an, China.
Yaning CaiDepartment of Neurosurgery, Tangdu Hospital, Fourth Military Medical University, Xi'an, China.
Peigang JiDepartment of Neurosurgery, Tangdu Hospital, Fourth Military Medical University, Xi'an, China.
Jinghui LiuDepartment of Neurosurgery, Tangdu Hospital, Fourth Military Medical University, Xi'an, China.
Wei GuoDepartment of Neurosurgery, Tangdu Hospital, Fourth Military Medical University, Xi'an, China.
Li GongDepartment of Pathology, Tangdu Hospital, Fourth Military Medical University, Xi'an, China.
Miao LouDepartment of Neurosurgery, Tangdu Hospital, Fourth Military Medical University, Xi'an, China.
Fuqiang FengDepartment of Neurosurgery, The Second Hospital of Shanxi Medical University, Taiyuan, China.
Yuan WangDepartment of Neurosurgery, Tangdu Hospital, Fourth Military Medical University, Xi'an, China.
Yulong ZhaiDepartment of Neurosurgery, Tangdu Hospital, Fourth Military Medical University, Xi'an, China.
Yan QuDepartment of Neurosurgery, Tangdu Hospital, Fourth Military Medical University, Xi'an, China.
Liang WangDepartment of Neurosurgery, Tangdu Hospital, Fourth Military Medical University, Xi'an, China.
Air Force Medical University · CNShanxi Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeGlioma is one of the most common tumors of the central nervous system, and many patients suffer from recurrence even after standard comprehensive treatment. However, little is known about the molecular markers that predict the recurrence patterns of glioma. This study aimed to demonstrate the correlations between molecular markers and glioma recurrence patterns, which included local/nonlocal recurrence and paraventricular/nonparaventricular recurrence.

methodsImmunohistochemical techniques were used to assess the molecular markers of 88 glioma tissues following surgical resection. The recurrence patterns were divided into local recurrence, marginal recurrence, distant recurrence, multirecurrence, and subarachniod recurrence, with the last four recurrence patterns being collectively called nonlocal recurrence. According to whether the recurrence invaded ventricles, the nonlocal recurrence patterns were divided into paraventricular and nonparaventricular recurrence. Then, we compared the different recurrence patterns and their clinical characteristics, focusing on the expression of molecular markers.

resultsMore patients in the nonlocal recurrence group received combined radiotherapy and chemotherapy than patients in the local recurrence group (p=0.019). Sex, age, extent of surgery, time to recurrence, tumor location, size, and WHO grade were not different in the defined groups (P>0.05). Recurrent tumor volume and WHO grade were significantly different between the paraventricular and nonparaventricular recurrence groups (p=0.046 and 0.033). The expression of Ki-67, P53, and PCNA in the nonlocal recurrence group was significantly higher than that in the local recurrence group (p=0.015, 0.009, and 0.037), while the expression of S-100 in the nonlocal recurrence group was significantly lower than that in the local recurrence group (p=0.015). Cox regression indicated hazard ratio (HR) for high expression level of PCNA associated with non-local recurrence was 3.43 (95% CI, 1.15, 10.24), and HR for high expression level of MGMT associated with paraventricular recurrence was 2.64 (95% CI, 1.15,6.08).

conclusionsKi-67, P53, PCNA, and MGMT might be important clinical markers for nonlocal recurrence and paraventricular recurrence.

Indexed as

gliomalocal recurrencemolecular markersO6-Methylguanine DNA methyltransferaseparaventricular recurrence

Identifiers

PMID33585189
PMCPMC7873968
OpenAlexW3193216927

What Socratic 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 Socratic graph.