Evidence map›Paper›PMID 31261511›Full record

ArticleMedicine2019

MiR-101 acts as a novel bio-marker in the diagnosis of bladder carcinoma.

Xiaoyan Chen

Open access · goldAbstract read
In one paragraph

Article in Medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 1 pooled it
3.3field-weighted citation impact, top 8% 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

9 citing papers in PubMed, 1 synthesis or guideline pooled it, 22 citations in OpenAlex.

  1. Pooled it
  2. Review
  3. Review
  4. Review
  5. Article
  6. Article
  7. Review
  8. Advances in urinary biomarker discovery in urological research.Investigative and clinical urology · 2020
    Review
  9. 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

1 author at 1 institution in 1 country.

Xiaoyan ChenDepartment of Urology, Zhongnan Hospital, Wuhan, Hubei, China.
Zhongnan Hospital of Wuhan University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

MiR-101 plays an important role in tumorigenesis. The aim of this study was to estimate diagnostic potential of serum miR-101 in bladder cancer.Serum level of miR-101 in 122 bladder cancer patients and 110 healthy volunteers was detected using quantitative real-time polymerase chain reaction method. The association between miR-101 expression and clinicopathological characteristic was analyzed via χ test. Then receiver operating characteristic (ROC) curve was plotted to evaluate diagnostic value of serum miR-101 in bladder cancer.MiR-101 expression was statistically down-regulated in bladder cancer patients compared to healthy controls. MiR-101 expression was significantly associated with TNM stage (P = .019), pathological grade (P = .006) and lymph node metastasis (P = .010). ROC analysis suggested that miR-101 had high value in discriminating between bladder cancer patients and healthy individuals with an AUC value of 0.884. The cut-off value for serum miR-101 in bladder cancer diagnosis was 1.645, with a sensitivity of 82.0% and a specificity of 80.9%.MiR-101 is decreased in bladder cancer patients, and shows negative association with aggressive clinical characteristics. MiR-101 may serve as a bio-marker in diagnosing bladder cancer.

Indexed as

Area Under CurveBiomarkers, TumorDown-RegulationFemaleGene Expression Regulation, NeoplasticHumansMaleMicroRNAsMiddle AgedReal-Time Polymerase Chain ReactionROC CurveUrinary Bladder NeoplasmsBiomarkers, TumorMicroRNAsMIRN101 microRNA, human

Identifiers

PMID31261511
PMCPMC6616305
OpenAlexW2955235010

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.