Evidence map›Paper›PMID 28599426›Full record

ArticleOncology letters2017

Dynamic monitoring of circulating microRNAs as a predictive biomarker for the diagnosis and recurrence of papillary thyroid carcinoma.

Yanqing Zhang, Desheng Xu, Jiaqi Pan, Zhengkai Yang, Meijun Chen, Jun Han, Sijia Zhang, Lulu Sun, Hong Qiao

Open access · diamondAbstract read
In one paragraph

Article in Oncology letters, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
30citing papers in PubMed, 4 pooled it
1.3field-weighted citation impact, top 22% 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

30 citing papers in PubMed, 4 syntheses or guidelines pooled it, 50 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Pooled it
  5. Article
  6. Article
  7. Article
  8. Article
  9. Observational
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article
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

9 authors at 3 institutions in 1 country.

Yanqing ZhangDepartment of Hematology, The Second Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang 150086, P.R. China.
Desheng XuDepartment of Anesthesiology, Harbin Medical University Cancer Hospital, Harbin, Heilongjiang 150040, P.R. China.
Jiaqi PanDepartment of Hematology, The Second Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang 150086, P.R. China.
Zhengkai YangDepartment of Biochemistry, Harbin Medical University, Harbin, Heilongjiang 150086, P.R. China.
Meijun ChenDepartment of Endocrinology, The Second Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang 150086, P.R. China.
Jun HanDepartment of Endocrinology, The Second Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang 150086, P.R. China.
Sijia ZhangDepartment of Endocrinology, The Second Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang 150086, P.R. China.
Lulu SunDepartment of Endocrinology, The Second Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang 150086, P.R. China.
Hong QiaoDepartment of Endocrinology, The Second Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang 150086, P.R. China.
Harbin Medical University · CNSecond Affiliated Hospital of Harbin Medical University · CNThird Affiliated Hospital of Harbin Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Circulating microRNAs (miRNAs/miRs) are considered to be potential biomarkers for numerous types of cancer. However, previous investigations into the expression of miRNAs in the serum of patients with papillary thyroid carcinoma (PTC) to predict diagnosis, prognosis and recurrence have reported conflicting results, and the role of miRNAs remains unclear. The present study dynamically assessed the circulating miRNA profile in patients with PTC and determined whether miRNAs in the serum could be used as biomarkers for the diagnosis, prognosis and recurrence of PTC. The expression levels of 3 reportedly upregulated miRNAs (miR-222, miR-221 and miR-146b) were analyzed using reverse transcription-quantitative polymerase chain reaction in 106 patients with PTC, 35 patients with benign thyroid nodules (BTN) and 40 paired controls. Patients with either newly diagnosed PTC or BTN who were undergoing thyroidectomies were recruited for a dynamic analysis of preoperative and postoperative serum miRNA levels. The results indicated that the expression levels of serum miR-222, miR-221 and miR-146b were significantly increased in patients with newly diagnosed PTC compared with controls and patients with BTN. Receiver operating characteristic curve analysis indicated that these miRNAs had a high diagnostic sensitivity and specificity for PTC prior to surgery. The expression of these three miRNAs in serum was significantly associated with poorer prognostic variables, including extrathyroidal invasion, metastatic lymph nodes and high-risk or advanced tumor node metastasis stage. More notably, the present study identified 2.36-, 2.69- and 5.39-fold reductions in the serum levels of miR-222, miR-221 and miR-146b, respectively, subsequent to patients undergoing a thyroidectomy. In addition, miR-222, miR-221 and miR-146b were overexpressed in the PTC with recurrence group compared with the PTC without recurrence group. Collectively, dynamic monitoring of circulating miRNAs may serve as a non-invasive biomarker for the diagnosis of PTC and the postoperative monitoring of its progression and recurrence.

Indexed as

circulating biomarkersmicroRNApapillary thyroid carcinomaprognosisrecurrence

Identifiers

PMID28599426
PMCPMC5452941
OpenAlexW2607251732

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.