Evidence map›Paper›PMID 34335759›Full record

ArticleJournal of oncology2021

A Diagnostic Analysis Workflow to Optimal Multiple Tumor Markers to Predict the Nonmetastatic Breast Cancer from Breast Lumps.

Nan Jiang, Tian Tian, Xianyang Chen, Guofen Zhang, Lijie Pan, Chengping Yan, Guoshan Yang, Lili Wang, Xuchen Cao, Xin Wang

Open access · hybridAbstract read
In one paragraph

Article in Journal of oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.6field-weighted citation impact, top 33% 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

2 citing papers in PubMed, 8 citations in OpenAlex.

  1. Article
  2. 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

10 authors at 2 institutions in 1 country.

Nan JiangThe First Department of Breast Cancer, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin 300060, China.
Tian TianThe First Department of Breast Cancer, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin 300060, China.
Xianyang ChenBao Feng Biotech (Beijing) Co., Ltd., Beijing, China.
Guofen ZhangDepartment of General Surgery, First Hospital of Tsinghua University, Beijing 100016, China.
Lijie PanDepartment of General Surgery, First Hospital of Tsinghua University, Beijing 100016, China.
Chengping YanDepartment of General Surgery, First Hospital of Tsinghua University, Beijing 100016, China.
Guoshan YangDepartment of General Surgery, First Hospital of Tsinghua University, Beijing 100016, China.
Lili WangDepartment of Laboratory Medicine, First Hospital of Tsinghua University, Beijing 100016, China.
Xuchen CaoThe First Department of Breast Cancer, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin 300060, China.
Xin WangThe First Department of Breast Cancer, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin 300060, China.ORCID https://orcid.org/0000-0002-0074-745X
Beijing Hua Xin Hospital · CNTianjin Medical University Cancer Institute and Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo assess the diagnostic performance of clinically common single markers and combinations to distinguish nonmetastatic breast cancer and benign breast tumor. A predictive model with a better diagnostic ability for nonmetastatic breast cancer was established by using the diagnostic process.

methodsA total of 222 patients with nonmetastatic breast cancer and 265 patients with benign breast disease were enrolled in this study. CEA, Ca 15-3, Ca 125, Ca 72-4, CYFRA 21-1, FERR, AFP, and NSE were measured by an electrochemiluminescent immunoenzymometric assay on the Elecsys system. There are four key steps for our diagnostic workflow, that is, feature selection, algorithm selection, parameter optimization, and outer test data was used to validate the optimal algorithm and markers.

resultsCEA, Ca 15-3, CYFRA 21-1, AFP, and FERR were selected using the

conclusionsNo single marker of these eight markers was good at identifying nonmetastatic breast cancer from benign tumors. But a diagnostic analysis workflow was established to develop a predictive model with better diagnostic capability for nonmetastatic breast cancer. This workflow is also applicable to the optimization of other disease markers and diagnostic models. The predictive model showed good diagnostic performance, and it could be gradually incorporated as a support method for the diagnosis of nonmetastatic breast cancer.

Identifiers

PMID34335759
PMCPMC8289572
OpenAlexW3180235696

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

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.