Evidence map›Paper›PMID 32514246›Full record

ReviewCancer cell international2020

Long noncoding RNAs as potential biomarkers in retinoblastoma: a systematic review and meta-analysis.

Jiali Wu, Dashi Qian, Xiaodong Sun

Open access · goldAbstract readReview
In one paragraph

Review in Cancer cell international, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
0.7field-weighted citation impact, top 36% 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

7 citing papers in PubMed, 12 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Long non-coding RNAs involved in retinoblastoma.Journal of cancer research and clinical oncology · 2023
    Review
  6. Article
  7. The regulatory roles of long noncoding RNAs in osteoporosis.American journal of translational research · 2020
    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

3 authors at 1 institution in 2 countries.

Jiali WuDepartment of Ophthalmology, Shanghai General Hospital (Shanghai First People's Hospital), Shanghai Jiao Tong University, School of Medicine, Shanghai, 200080 China.
Dashi QianDepartment of Translation and Interpreting, Shanghai Jiao Tong University School of Foreign Language, Shanghai, China.
Xiaodong SunDepartment of Ophthalmology, Shanghai General Hospital (Shanghai First People's Hospital), Shanghai Jiao Tong University, School of Medicine, Shanghai, 200080 China.ORCID 0000-0001-7203-3651
Shanghai Jiao Tong University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundRetinoblastoma is the most common malignant rare intraocular tumor of childhood. Long noncoding RNAs (lncRNAs) have been reported participating in its progression, but their significance remains inconclusive. We conducted this systematic review and meta-analysis to explore specific lncRNA biomarker in patients with retinoblastoma. MATERIALS AND

methodsEligible articles were searched from the Pubmed, Web of Science, Embase and the Cochrane library. Hazard ratios (HRs) and odds ratios (ORs) were extracted or calculated to evaluate the relationship between lncRNAs and retinoblastoma. The meta-analysis part was conducted with STATA v.15 software.

resultsA total of 9 articles with 834 retinoblastoma patients are yielded. Heterogeneity among HRs of overall survival (OS) is notably high (I

conclusionDifferential expression of lncRNAs has been reported in retinoblastoma. Some of them showed potential in retinoblastoma prognosis and progression.

Indexed as

LncRNAMeta-analysisPrognosticRetinoblastoma

Identifiers

PMID32514246
PMCPMC7257223
OpenAlexW3029707934

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.