Evidence map›Paper›PMID 33982217›Full record

ArticleDigestive diseases and sciences2022

Development and Validation of a Novel Circulating miRNA-Based Diagnostic Score for Early Detection of Hepatocellular Carcinoma.

Bin Yu, Shujun Zhou, Han Liang, Qifa Ye, Yanfeng Wang

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In one paragraph

Article in Digestive diseases and sciences, 2022. 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 38% 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, 10 citations in OpenAlex.

  1. miR-184 in hepatocellular carcinoma: a promising therapeutic target.Journal of physiology and biochemistry · 2025
    Review
  2. Hepatocellular Carcinoma: The Search for an Optimal Screening Test.Middle East journal of digestive diseases · 2025
    Review
  3. Article
  4. Article
  5. Review
  6. Article
  7. The Potential Role of miRNAs in Cognitive Frailty.Frontiers in aging neuroscience · 2021
    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 at 2 institutions in 1 country.

Bin YuZhongnan Hospital of Wuhan University, Institute of Hepatobiliary Diseases of Wuhan University, Transplant Center of Wuhan University, Hubei Key Laboratory of Medical Technology on Transplantation, Wuhan, Hubei, 430071, People's Republic of China.
Shujun ZhouZhongnan Hospital of Wuhan University, Institute of Hepatobiliary Diseases of Wuhan University, Transplant Center of Wuhan University, Hubei Key Laboratory of Medical Technology on Transplantation, Wuhan, Hubei, 430071, People's Republic of China.
Han LiangZhongnan Hospital of Wuhan University, Institute of Hepatobiliary Diseases of Wuhan University, Transplant Center of Wuhan University, Hubei Key Laboratory of Medical Technology on Transplantation, Wuhan, Hubei, 430071, People's Republic of China.
Qifa YeZhongnan Hospital of Wuhan University, Institute of Hepatobiliary Diseases of Wuhan University, Transplant Center of Wuhan University, Hubei Key Laboratory of Medical Technology on Transplantation, Wuhan, Hubei, 430071, People's Republic of China.
Yanfeng WangZhongnan Hospital of Wuhan University, Institute of Hepatobiliary Diseases of Wuhan University, Transplant Center of Wuhan University, Hubei Key Laboratory of Medical Technology on Transplantation, Wuhan, Hubei, 430071, People's Republic of China. yanfengwang@whu.edu.cn.ORCID 0000-0002-3859-0937
Wuhan University · CNCentral South University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundWith the rise of liquid biopsy in oncology, circulating miRNAs have become one of the most promising noninvasive biomarkers for early detection of hepatocellular carcinoma (HCC). However, a reliable HCC-related circulating miRNA panel and corresponding diagnostic model remain to be explored.

methodsFive large public datasets related to intact miRNA profiles in the serum or tumors of HCC patients were included and divided into training cohorts (GSE113740 and TCGA-LIHC) and validation cohorts (GSE112264, GSE113486 and GSE106817). Compared with non-cancer controls and high-risk patients, key miRNAs dysregulated in both the serum and tumors of HCC patients were identified by differential expression analysis and overlapping analysis. The corresponding diagnostic model was constructed by LASSO logistic regression and evaluated by receiver operating characteristic curves and a nomogram with calibration plot.

resultsA distinctive panel of HCC-related circulating miRNAs, including three upregulated miRNAs (miR-184, miR-532-5p, miR-221-3p) and three downregulated miRNAs (miR-5589-5p, let-7b-3p, miR-26b-3p), were rigorously screened out, all of which displayed significant discriminability between HCC patients and controls (all P < 0.05). In addition, a reliable six-circulating miRNA-based diagnostic score was constructed and displayed robust diagnostic ability for HCC (particularly for early-stage HCC) (AUC = 0.9535, P < 0.05) compared with that of the serum α-fetoprotein test. Importantly, its efficacy was sufficiently validated in three independent datasets (AUC = 0.9780/0.9961/0.9681, all P < 0.05). Furthermore, a visual nomogram based on the diagnostic score was correspondingly established to strengthen its clinical applicability.

conclusionThe six-circulating miRNA-based diagnostic score may be a reliable noninvasive biomarker for early-stage HCC screening and dynamic monitoring of postoperative recurrence.

Indexed as

Carcinoma, HepatocellularCirculating MicroRNALiver NeoplasmsMicroRNAsBiomarkers, TumorHumansBiomarkers, TumorCirculating MicroRNAMicroRNAsCirculating miRNAsEarly diagnosisHepatocellular carcinomaLiquid biopsyModel

Identifiers

PMID33982217
OpenAlexW3160046031

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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.