Evidence map›Paper›PMID 25557788›Full record

ArticleTumour biology : the journal of the International Society for Oncodevelopmental Biology and Medicine2015

MD-miniRNA could be a more accurate biomarker for prostate cancer screening compared with serum prostate-specific antigen level.

Dong Xue, Cui-Xing Zhou, Yun-Bo Shi, Hao Lu, Xiao-Zhou He

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Article in Tumour biology : the journal of the International Society for Oncodevelopmental Biology and Medicine, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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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. Article
  2. Review
  3. Article
  4. Review
  5. Review
  6. Review
  7. Long Non-Coding RNA as Potential Biomarker for Prostate Cancer: Is It Making a Difference?International journal of environmental research and public health · 2017
    Review
  8. Review
  9. Cancer prevention: state of the art and future prospects.Journal of preventive medicine and hygiene · 2015
    Review
4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Dong XueDepartment of Urology, Third Affiliated Hospital, Suzhou University, Changzhou, 213003, China.
Cui-Xing Zhou
Yun-Bo Shi
Hao Lu
Xiao-Zhou He

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Prostate cancer and prostatic hyperplasia detection remains a great challenge, lacking of effective non-invasive and specific diagnostic biomarkers. In the current study, we aimed to identify the relative expression of plasma MD-miniRNA and its diagnostic performance in differentiating prostate cancer and prostatic hyperplasia patients from healthy controls, compared with serum prostate-specific antigen (PSA) level. All of the clinical participants (63 prostate cancer patients, 32 prostatic hyperplasia patients, and 50 healthy controls) were obtained from the Third Affiliated Hospital of Suzhou University in China between January 2013 and April 2014. Clinical characteristics were well matched. Plasma samples were extracted to test the relative expression of MD-miniRNA using the method of qRT-PCR. SPSS 22.0 statistical software package was used to analyze the data and GraphPad Prism 6.0 was used to generate the graphs. Relativity expression of plasma MD-miniRNA was significantly upregulated in prostate cancer, compared with prostatic hyperplasia patients and healthy controls. Serum PSA level revealed similar differences among these groups. MD-miniRNA presented a relatively high diagnostic accuracy with AUC of 0.86 (95 % CI 0.80-0.93) in differentiating prostate cancer patients from healthy controls. Simultaneously, MD-miniRNA was able to discriminate prostate cancer patients from prostatic hyperplasia controls with AUC of 0.79 (95 % CI 0.70-0.88). In addition, MD-miniRNA displayed a better diagnostic performance than PSA level. However, the panel of these two biomarkers revealed the best diagnostic performance, compared with either single biomarker. Results of this study showed that plasma MD-miniRNA could serve as a promising and noninvasive biomarker for diagnosing prostate cancer. Further large-scale studies are needed to confirm its clinical diagnosis accuracy.

Indexed as

AgedDiagnosis, DifferentialHumansMaleMiddle AgedProstate-Specific AntigenProstatic HyperplasiaProstatic NeoplasmsRNA, Long NoncodingMD-miniRNA, humanProstate-Specific AntigenRNA, Long Noncoding

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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.