Evidence map›Paper›PMID 36687184›Full record

ArticleWorld journal of clinical cases2023

Identification of a four-miRNA signature predicts the prognosis of papillary thyroid cancer.

Fan Yang, Yi-Li Zhou

Open access · diamondAbstract read
In one paragraph

Article in World journal of clinical cases, 2023. 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
0.7field-weighted citation impact, top 25% 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

3 citing papers in PubMed, 3 citations in OpenAlex.

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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

2 authors at 1 institution in 1 country.

Fan YangDepartment of Thyroid Surgery, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou 325000, Zhejiang Province, China.
Yi-Li ZhouDepartment of Thyroid Surgery, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou 325000, Zhejiang Province, China. yilistar@163.com.
First Affiliated Hospital of Wenzhou Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIn recently diagnosed patients with thyroid cancer, papillary thyroid cancer (PTC), as the most common histological subtype, accounts for 90% of all cases. Although PTC is known as a relatively adolescent malignant disease, there still is a high possibility of recurrence in PTC patients with a poor prognosis. Therefore, new biomarkers are necessary to guide more effective stratification of PTC patients and personalize therapy to avoid overtreatment or inadequate treatment. Accumulating evidence demonstrates that microRNAs (miRNAs) have broad application prospects as diagnostic biomarkers in cancer.

aimTo explore novel markers consisting of miRNA-associated signatures for PTC prognostication.

methodsWe obtained and analyzed the data of 497 PTC patients from The Cancer Genome Atlas. The patients were randomly assigned to either a training or testing cohort.

resultsWe discovered 237 differentially expressed miRNAs in tumorous thyroid tissues compared with normal tissues, which contained 172 up-regulated and 65 down-regulated miRNAs. The evaluation of differently expressed miRNAs was conducted using our risk score model. We then successfully generated a four-miRNA potential prognostic signature [risk score = (-0.001 × hsa-miR-181a-2-3p) + (0.003 × hsa-miR-138-5p) + (-0.018 × hsa-miR-424-3p) + (0.284 × hsa-miR-612)], which reliably distinguished patients from high and low risk with a significant difference in the overall survival (

conclusionOur results indicated a four-miRNA signature that has a robust predictive effect on the prognosis of PTC. Accordingly, we would recommend more radical therapy and closer follow-ups for high-risk groups.

Indexed as

microRNAPapillary thyroid cancerPrognosisSignature

Identifiers

PMID36687184
PMCPMC9846980
OpenAlexW4313591292

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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.