Evidence map›Paper›PMID 27512841›Full record

ArticleMedicine2016

The diagnostic value of 1.5-T diffusion-weighted MR imaging in detecting 5 to 10 mm metastatic cervical lymph nodes of nasopharyngeal carcinoma.

Guan Qiao Jin, Jun Yang, Li Dong Liu, Dan Ke Su, Duo Ping Wang, Sheng Fa Zhao, Zhi Ling Liao

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In one paragraph

Article in Medicine, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 1 pooled it
–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

12 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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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

7 authors.

Guan Qiao JinDepartment of Radiology Department of Head and Neck Surgery Department of Ultrasound Department of Pathology, Affiliated Tumor Hospital, Guang xi Medical University, Nanning, P.R. China.
Jun Yang
Li Dong Liu
Dan Ke Su
Duo Ping Wang
Sheng Fa Zhao
Zhi Ling Liao

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The aim of the study was to prospectively assess the diagnostic accuracy of 1.5 T diffusion-weighted imaging (DWI) for 5 to 10 mm metastatic cervical lymph nodes of patients with nasopharyngeal carcinoma (NPC). All patients with histopathologically confirmed NPC underwent DWI with 2 b values of 0 and 800 s/mm were enrolled. The shortest axial diameter and mean apparent diffusion coefficient (ADC) value were recorded when lymph nodes with a shortest axial diameter from 5 to 10 mm were measured. The correlation between the pathological diagnoses and mean ADC values in the benign and metastatic lymph nodes were compared using the Z test. Receiver operating characteristic (ROC) curve analysis was performed to evaluate the diagnostic performance of DWI. Three hundred fourteen nodes of 52 patients with NPC consisted of 46.5% (146/314) metastatic lymph nodes and 53.5% (168/314) benign lymph nodes. The mean ADC value (×10 mm/s) of benign lymph nodes was (1.110 ± 0.202), which was significantly higher than that of metastatic nodes (0.878 ± 0.159) (P < 0.05). The sensitivity, specificity, positive predictive value, and negative predictive value, accuracy for differentiating metastatic from benign lymph nodes using a cutoff ADC value of 0.924 × 10 mm/s was 83.56%, 82.74%, 80.79%, 85.28%, and 82.80%, respectively. The area under the ROC curve was 0.851 (95% confidence intervals: 0.807-0.889). This study demonstrated that DWI is helpful in detecting 5 to 10 mm metastatic lymph nodes of patients with NPC.

Indexed as

AdultAgedCervical VertebraeCohort StudiesDiagnosis, DifferentialDiffusion Magnetic Resonance ImagingFemaleHumansLymphatic MetastasisLymph NodesMaleMiddle AgedNasopharyngeal NeoplasmsNeoplasm InvasivenessNeoplasm StagingProspective Studies

Identifiers

PMID27512841
PMCPMC4985296

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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.