Evidence map›Paper›PMID 31124961›Full record

SynthesisMedicine2019

Prognostic value of long noncoding RNA ROR in patients with cancer in China: A systematic review and meta-analysis.

Shuai Li, Xin-Can Yue, Chao-Yan Sun, Hai-Yan Qin, Xiao-Yang Zhang

Abstract readMeta-AnalysisSystematic Review
In one paragraph

Synthesis in Medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Article
  3. 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

5 authors.

Shuai LiDepartment of Intensive Care Unit of Neuroscience.
Xin-Can YueDepartment of Intensive Care Unit of Neuroscience.
Chao-Yan SunDepartment of Intensive Care Unit of Neuroscience.
Hai-Yan QinDepartment of Intensive Care Unit of Neuroscience.
Xiao-Yang ZhangDepartment of Neurosurgery, Zhoukou Central Hospital, Zhoukou, Henan Province, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundFor cancer, it is common that there is usually a dysregulation of the long noncoding RNA regulator of reprogramming (LncRNA ROR). To illustrate the application of LncRNA ROR, which serves as the prognostic marker for the malignant tumors, it is of great importance to conduct a meta-analysis.

methodsThere were 3 databases being applied. The data used were collected before January 5, 2018. These 3 databases include the OVID, PubMed, and Science databse. To further explore the association between the expression and survival of LncRNA ROR, it calculated the 95% confidence intervals (CIs) and hazard ratios (HRs). Meanwhile, the odds ratios (ORs) have been calculated for the evaluation of the correlation between the pathological and expression parameters of LncRNA ROR.

resultsThere were 8 researches participated by 720 patients. According to the HR, it has been implied that there was a high LncRNA ROR expression related with the weak disease-free survival (DFS) (HR = 3.48, 95% CI, 2.24-5.41) and overall survival (OS) (HR = 2.47, 95% CI, 1.76-3.47) among the cancer patients with none dramatic heterogeneity. There was also a correlation among lymph node metastasis (OR = 5.38, 95% CI, 2.21-13.12), high tumor stage (OR = 3.80, 95% CI, 1.95-7.41), and larger tumor size (OR = 4.43, 95% CI, 1.26-15.51).

conclusionsThus, it can be predicted about the lymph node metastasis and high tumor stage, larger tumor size, DFS, and poor OS based on the high LncRNA ROR. This suggests that high LncRNA ROR can be used as a new indicator of poor prognosis in cancer.

Indexed as

Biomarkers, TumorChinaHumansLymphatic MetastasisNeoplasmsNeoplasm StagingRNA, Long NoncodingSurvival AnalysisTumor BurdenBiomarkers, TumorRNA, Long Noncoding

Identifiers

PMID31124961
PMCPMC6571364

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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.