Evidence map›Paper›PMID 31767040›Full record

ArticleJournal of ovarian research2019

Evaluation of the value of preoperative CYFRA21-1 in the diagnosis and prognosis of epithelial ovarian cancer in conjunction with CA125.

Chunjing Jin, Minfeng Yang, Xueqiao Han, Haidan Chu, Yan Zhang, Meihong Lu, Zhonghui Wang, Xinxin Xu, Wenwen Liu, Feng Wang and 1 more

Open access · goldAbstract read
In one paragraph

Article in Journal of ovarian research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
3.0field-weighted citation impact, top 9% 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

13 citing papers in PubMed, 20 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

11 authors at 3 institutions in 1 country.

Chunjing JinLaboratory Medicine Center, Affiliated Hospital of Nantong University, 20 Xisi Road, Nantong, 226001, China.ORCID http://orcid.org/0000-0002-3032-5960
Minfeng YangTeaching and Research Office of Medical Laboratory, Suzhou Vocational Health College, 1 Kerui Road, Huqiu District, Suzhou City, 215004, Jiangsu Province, China.
Xueqiao HanClinical medical laboratory, Jiangsu University, 301 Xuefu road, Jingkou District, Zhenjiang city, 212013, Jiangsu Province, China.
Haidan ChuLaboratory Medicine Center, Affiliated Hospital of Nantong University, 20 Xisi Road, Nantong, 226001, China.
Yan ZhangLaboratory Medicine Center, Affiliated Hospital of Nantong University, 20 Xisi Road, Nantong, 226001, China.
Meihong LuLaboratory Medicine Center, Affiliated Hospital of Nantong University, 20 Xisi Road, Nantong, 226001, China.
Zhonghui WangLaboratory Medicine Center, Affiliated Hospital of Nantong University, 20 Xisi Road, Nantong, 226001, China.
Xinxin XuLaboratory Medicine Center, Affiliated Hospital of Nantong University, 20 Xisi Road, Nantong, 226001, China.
Wenwen LiuLaboratory Medicine Center, Affiliated Hospital of Nantong University, 20 Xisi Road, Nantong, 226001, China.
Feng WangLaboratory Medicine Center, Affiliated Hospital of Nantong University, 20 Xisi Road, Nantong, 226001, China. richardwangf@163.com.
Shaoqing JuLaboratory Medicine Center, Affiliated Hospital of Nantong University, 20 Xisi Road, Nantong, 226001, China. jsq814@hotmail.com.
Nantong University · CNJiangsu University · CNSuzhou Vocational Health College · CN

Funding

Key Social Development Project of Jiangsu Province BE2015654Key Social Development Project of Jiangsu Province BE2019691National Natural Science Foundation of China 81672099National Natural Science Foundation of China 81871720National Natural Science Foundation of China 81873978
6 · The paper itself

Abstract

Growing evidence indicates that the tumor biomarker cytokeratin 19 fragment (CYFRA21-1) is significant for a variety of cancers. However, its role in epithelial ovarian cancer (EOC) has rarely been reported. In this study, a receiver operating characteristic (ROC) curve was utilized to estimate the diagnostic efficiency of CYFRA21-1. The correlation between the CYFRA21-1 level and prognosis was analyzed by Kaplan-Meier survival analysis and univariable and multivariable analyses. The relationship between serum CYFRA21-1 levels and different clinicopathological variables was also analyzed. At the same time, the standard serum marker cancer antigen 125 (CA125) was measured. The results demonstrated that CYFRA21-1 expression was significantly increased in EOC compared with expression in benign ovarian diseases and healthy controls, which was similar to CA125 (P < 0.001). CYFRA21-1 expression was positively correlated with CA125 (r = 0.201; P = 0.0032). CYFRA21-1 expression was significantly correlated with lymph node metastasis and ascites (P < 0.001). Furthermore, the median survival time of EOC patients with high CYFRA21-1 expression was 42 months, compared with 54 months in the low CYFRA21-1 expression patients by Kaplan-Meier analysis (P < 0.05), while the high and low CA125 expression groups had no difference in median survival time. Univariate and multivariate analyses indicated that CYFRA21-1 was a poor prognostic factor associated with overall survival (OS), while CA125 was not. Our study indicates that CYFRA21-1 acts as a good complementary diagnostic biomarker and may be superior to CA125 as a prognostic indicator in EOC.

Indexed as

AdultAgedAged, 80 and overAntigens, NeoplasmCA-125 AntigenCarcinoma, Ovarian EpithelialFemaleHumansKaplan-Meier EstimateKeratin-19Membrane ProteinsMiddle AgedOvarian NeoplasmsPreoperative PeriodPrognosisYoung Adultantigen CYFRA21.1Antigens, NeoplasmCA-125 AntigenKeratin-19Membrane ProteinsMUC16 protein, humanCYFRA21-1DiagnosisEpithelial ovarian cancerPrognosis

Identifiers

PMID31767040
PMCPMC6876093
OpenAlexW2990870358

What OpenQuestion holds

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LicenceCC BY
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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.