Evidence map›Paper›PMID 30922137›Full record

ArticleThe Journal of international medical research2019

Serum level of miR-142-3p predicts prognostic outcome for colorectal cancer following curative resection.

Wencang Gao, Dexiang Pang, Senquan Yu

Abstract read
In one paragraph

Article in The Journal of international medical research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 1 pooled it
–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

12 citing papers in PubMed, 1 synthesis or guideline pooled it.

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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.

Wencang Gao1 Oncology Department, The Second Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou, Zhejiang, PR China.
Dexiang Pang1 Oncology Department, The Second Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou, Zhejiang, PR China.
Senquan Yu1 Oncology Department, The Second Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou, Zhejiang, PR China.ORCID https://orcid.org/0000-0002-2311-0267

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveMicroRNA (miR)-142-3p may function as a tumor suppressor in the development of various cancers. In this study, we measured serum levels of miR-142-3p in patients with colorectal cancer (CRC) to evaluate the diagnostic and prognostic value of miR-142-3p.

methodsSerum samples from 363 consecutive CRC patients and 156 healthy controls were retrospectively collected. Serum miR-142-3p levels were measured using real-time quantitative reverse transcription polymerase chain reaction. All patients were followed up regularly after tumor resection. The correlation between serum miR-142-3p level and survival outcomes was analyzed.

resultsSerum levels of miR-142-3p were significantly lower in CRC patients than in healthy volunteers. A low serum miR-142-3p level was significantly associated with advanced cancer. Survival analysis demonstrated that patients with a low serum miR-142-3p had a lower 5-year overall survival rate than patients with a high serum miR-142-3p level (67.4% vs. 76.9%). Serum miR-142-3p level was also shown to be an independent risk factor for CRC in multivariate analysis (hazard ratio, 2.68; 95% confidence interval: 1.21-7.95).

conclusionsSerum miR-142-3p might serve as a useful diagnostic and prognostic marker for CRC.

Indexed as

Colorectal NeoplasmsFemaleGene Expression Regulation, NeoplasticHumansMaleMicroRNAsMiddle AgedPrognosisROC CurveMicroRNAsMIRN142 microRNA, humanbiomarkercolorectal cancermicroRNAprognosisSerum miR-142-3ptumor suppression

Identifiers

PMID30922137
PMCPMC6567755

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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.