Evidence map›Paper›PMID 37960513›Full record

ReviewSensors (Basel, Switzerland)2023

Application of Biosensors in Detecting Breast Cancer Metastasis.

Yu Deng, Yubi Zhang, Meng Zhou, Bin Wu, Jing Zhou

Abstract readReview
In one paragraph

Review in Sensors (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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

1 citing paper in PubMed.

  1. 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.

Yu DengDepartment of Breast and Thyroid Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China.
Yubi ZhangDepartment of Breast and Thyroid Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China.
Meng ZhouDepartment of Breast and Thyroid Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China.
Bin WuDepartment of Orthopedics, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China.
Jing ZhouDepartment of Breast and Thyroid Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Breast cancer has garnered global attention due to its high incidence worldwide, and even more noteworthy is that approximately 90% deaths due to breast cancer are attributed to cancer metastasis. Therefore, the early diagnosis of breast cancer metastasis holds significant importance for reducing mortality outcomes. Biosensors play a crucial role in the early detection of metastatic breast cancer due to their advantages, such as ease of use, portability, and real-time analysis capabilities. This review primarily described various types of sensors for detecting breast cancer metastasis based on biomarkers and cell characteristics, including electrochemical, optical, and microfluidic chips. We offered detailed descriptions of the performance of these various biosensors and made comparisons between them. Furthermore, we described the pathology of breast cancer and summarized commonly used biomarkers for metastatic breast cancer. Finally, we discussed the advantages of current-stage biosensors and the challenges that need to be addressed, as well as prospects for their future development.

Indexed as

Biosensing TechniquesBreast NeoplasmsBiomarkersCutaneous Malignant MelanomaEarly Detection of CancerElectrochemical TechniquesFemaleHumansBiomarkersbiomarkerbiosensorbreast cancermetastasis

Identifiers

PMID37960513
PMCPMC10649164

What OpenQuestion holds

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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.