Evidence map›Paper›PMID 39563526›Full record

ArticleFuture oncology (London, England)2024

Multimodality high-frequency ultrasound in the evaluation of cervical malignant lymphoma before biopsy.

Hongyan Deng, Kunpeng Cao, Xinhua Ye, Wenjuan Lu, Wenqin Chen, Ya Yuan, Yasu Zhou, Hua Shu

Abstract read
PubMed Full text at PMC Publisher
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Article in Future oncology (London, England), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

8 authors.

Hongyan DengDepartment of Ultrasound, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
Kunpeng CaoDepartment of Ultrasound, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
Xinhua YeDepartment of Ultrasound, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
Wenjuan LuDepartment of Ultrasound, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
Wenqin ChenDepartment of Ultrasound, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
Ya YuanDepartment of Ultrasound, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
Yasu ZhouDepartment of Ultrasound, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
Hua ShuDepartment of Ultrasound, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo investigate the application value of multimodality ultrasound in the evaluation of lymphoma.

methodsThe regression models were performed to determine whether there were differences in differentiating lymphoma from benign lymph nodes. Receiver operator curves were drawn to evaluate the diagnostic performance of three ultrasound modalities.

resultsMultivariate analysis showed statistically significant differences in the long to short axes ratio, visibility of the hilum, Adler grade of blood flow, cortical echo, maximum elasticity, elastic color pattern, enhancement distribution, and Area. The combination of three modalities achieved a sensitivity of 95.6%, specificity of 87.5%, accuracy of 93.5%, positive predicted value of 97.0%, and negative predicted value of 82.4%.

conclusionMultimodal ultrasound can provide valuable differential diagnosis and improve the diagnostic performance.

Indexed as

LymphomaROC CurveUltrasonographyAdultAgedBiopsyDiagnosis, DifferentialFemaleHumansLymph NodesMaleMiddle AgedMultimodal ImagingSensitivity and SpecificityYoung Adultbiopsycomplicationcontrast-enhanced ultrasonographyhigh-frequency ultrasoundlymphomaMultimodalityshear-wave elastographysuperficial lymph node

Identifiers

PMID39563526
PMCPMC11633403

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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.