Evidence map›Paper›PMID 35309836›Full record

ArticleComputational and mathematical methods in medicine2022

Diagnostic Value of MRI Combined with CXCR4 Expression Level in Lymph Node Metastasis Head and Neck Squamous Cell Carcinoma.

Jin Zhao, Xingde Li, Ming Wang, Fenghai Liu, Jingrun Wang

RetractedOpen access · hybridAbstract readRetracted Publication
In one paragraph

Article in Computational and mathematical methods in medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It has been retracted, and should not be counted. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.2field-weighted citation impact, top 56% 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, 2 citations in OpenAlex.

  1. Article
  2. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors at 1 institution in 1 country.

Jin ZhaoDepartment of Oncology, Cangzhou Central Hospital, Cangzhou, Hebei 061000, China.
Xingde LiDepartment of Radiation Oncology, Cangzhou Central Hospital, Cangzhou, Hebei 061000, China.ORCID https://orcid.org/0000-0002-0098-4906
Ming WangDepartment of Radiation Oncology, Cangzhou Central Hospital, Cangzhou, Hebei 061000, China.
Fenghai LiuDepartment of Nuclear Magnetic Resonance, Cangzhou Central Hospital, Cangzhou, Hebei 061000, China.
Jingrun WangDepartment of Radiation Oncology, Cangzhou Central Hospital, Cangzhou, Hebei 061000, China.
Cangzhou Central Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: To explore the diagnostic value of magnetic resonance imaging (MRI) combined with CXCR4 expression levels in lymph node metastasis of the head and neck squamous cell carcinoma (HNSCC). Methods: 289 patients with HNSCC were divided into lymph node metastasis group (LNM group, Results: Compared with the non-LNM group, patients in the LNM group had a lower degree of pathological differentiation, and the positive rate of TNM staging and vascular invasion was higher. The signal intensity of T1WI and T2WI were low intensity and high intensity, respectively, and the ADC value was significantly reduced. At the same time, the expression level of CXCR4 in the tumor tissues of the LNM group was also significantly increased. In addition, compared with MRI and CXCR4 used alone, MRI combined with CXCR4 has a higher predictive value. Conclusion: MRI has a good effect in demonstrating lymph node metastasis. CXCR4 is significantly upregulated in lymph node metastasis tumor tissue. The combination of the two can be used for clinical diagnosis of HNSCC lymph node metastasis.

Indexed as

AgedBiomarkers, TumorComputational BiologyFemaleHead and Neck NeoplasmsHumansLogistic ModelsLymphatic MetastasisMagnetic Resonance ImagingMaleMiddle AgedReceptors, CXCR4Squamous Cell Carcinoma of Head and NeckBiomarkers, TumorCXCR4 protein, humanReceptors, CXCR4

Identifiers

PMID35309836
PMCPMC8924604
OpenAlexW4221098249

What OpenQuestion holds

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LicenceCC BY
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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.