Evidence map›Paper›PMID 36530897›Full record

ArticleFrontiers in medicine2022

Recurrence risk stratification based on Epstein-Barr virus DNA to identify enlarged retropharyngeal lymph nodes of nasopharyngeal carcinoma: A model-histopathologic correlation study.

Minjie Mao, Xueping Wang, Sharvesh Raj Seeruttun, Peidong Chi, Kewei Huang, Wen Liu, Wencheng Tan

Open access · goldAbstract read
In one paragraph

Article in Frontiers in medicine, 2022. 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, top 74% 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

1 citing paper in PubMed, 0 citations in OpenAlex.

  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

7 authors at 2 institutions in 1 country.

Minjie MaoDepartment of Laboratory Medicine, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, China.
Xueping WangDepartment of Laboratory Medicine, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, China.
Sharvesh Raj SeeruttunState Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, China.
Peidong ChiDepartment of Laboratory Medicine, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, China.
Kewei HuangDepartment of Laboratory Medicine, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, China.
Wen LiuDepartment of Laboratory Medicine, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, China.
Wencheng TanState Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, China.
Sun Yat-sen University · CNSun Yat-sen University Cancer Center · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Accurate assessment of the nature of enlarged retropharyngeal lymph nodes (RLN) of nasopharyngeal carcinoma (NPC) patients after radiotherapy is related to selecting appropriate treatments and avoiding unnecessary therapy. This study aimed to develop a non-invasive and effective model for predicting the recurrence of RLN (RRLN) in NPC. Materials and methods: The data of post-radiotherapy NPC patients ( Results: Abnormal enhancement, minimum axis diameter (MAD) and EBV-DNA were identified as independent risk factors for RRLN and could stratify NPC patients into three risk groups. The probability of RRLN in the low-, medium-, and high-risk groups were 37.5, 82.4, and 100%, respectively. The AUC of the final predictive model was 0.882 (95% CI: 0.782-0.982) in the discovery cohort and 0.926 (95% CI, 0.827-1.000) in the validation cohort, demonstrating good clinical accuracy for predicting the RRLN of NPC patients. The favorable performance of the model was confirmed by the calibration plot and decision curve analysis. Conclusion: The nomogram model constructed in the study could be reliable in predicting the risk of RRLN after radiotherapy for NPC patients.

Indexed as

EBVnasopharyngeal carcinomaprediction modelrecurrenceretropharyngeal lymph nodes

Identifiers

PMID36530897
PMCPMC9752871
OpenAlexW4311069818

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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.