Evidence map›Paper›PMID 29284539›Full record

ArticleChinese journal of cancer2017

Prognostic values of the integrated model incorporating the volume of metastatic regional cervical lymph node and pretreatment serum Epstein-Barr virus DNA copy number in predicting distant metastasis in patients with N1 nasopharyngeal carcinoma.

Ji-Jin Yao, Guan-Qun Zhou, Ya-Qin Wang, Si-Yang Wang, Wang-Jian Zhang, Ya-Nan Jin, Fan Zhang, Li Li, Li-Zhi Liu, Zhi-Bin Cheng and 3 more

Abstract read
In one paragraph

Article in Chinese journal of cancer, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed, 1 pooled it
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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

20 citing papers in PubMed, 1 synthesis or guideline 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

13 authors.

Ji-Jin YaoDepartment of Radiation Oncology, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, 510060, P. R. China.
Guan-Qun ZhouDepartment of Radiation Oncology, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, 510060, P. R. China.
Ya-Qin WangDepartment of Radiation Oncology, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, 510060, P. R. China.
Si-Yang WangDepartment of Radiation Oncology, The Fifth Affiliated Hospital of Sun Yat-sen University, Zhuhai, Guangdong, 519001, P. R. China.
Wang-Jian ZhangDepartment of Medical Statistics and Epidemiology & Health Information Research Center & Guangdong Key Laboratory of Medicine, School of Public Health, Sun Yat-sen University, Guangzhou, Guangdong, 510080, P. R. China.
Ya-Nan JinDepartment of Radiation Oncology, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, 510060, P. R. China.
Fan ZhangDepartment of Radiation Oncology, The Fifth Affiliated Hospital of Sun Yat-sen University, Zhuhai, Guangdong, 519001, P. R. China.
Li LiDepartment of Imaging Diagnosis and Interventional Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, 510060, P. R. China.
Li-Zhi LiuDepartment of Imaging Diagnosis and Interventional Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, 510060, P. R. China.
Zhi-Bin ChengDepartment of Radiation Oncology, The Fifth Affiliated Hospital of Sun Yat-sen University, Zhuhai, Guangdong, 519001, P. R. China.
Jun MaDepartment of Radiation Oncology, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, 510060, P. R. China.
Zhen-Yu QiDepartment of Radiation Oncology, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, 510060, P. R. China. qizhy@sysucc.org.cn.
Ying SunDepartment of Radiation Oncology, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, 510060, P. R. China. sunying@sysucc.org.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAccording to the 7th edition of the American Joint Committee on Cancer (AJCC) staging system, over 50% of patients with nasopharyngeal carcinoma (NPC) have N1 disease at initial diagnosis. However, patients with N1 NPC are relatively under-researched, and the metastasis risk of this group is not well-stratified. This study aimed to evaluate the prognostic values of gross tumor volume of metastatic regional lymph node (GTVnd) and pretreatment serum copy number of Epstein-Barr virus (EBV) DNA in predicting distant metastasis of patients with N1 NPC, and to develop an integrated prognostic model that incorporates GTVnd and EBV DNA copy number for this group of patients.

methodsThe medical records of 787 newly diagnosed patients with nonmetastatic, histologically proven N1 NPC who were treated at Sun Yat-sen University Cancer Center between November 2009 and February 2012 were analyzed. Computed tomography-derived GTVnd was measured using the summation-of-area technique. Blood samples were collected before treatment to quantify plasma EBV DNA. The receiver operating characteristic (ROC) curve analysis was used to evaluate the cut-off point for GTVnd, and the area under the ROC curve was used to assess the predicted validity of GTVnd. The survival rates were assessed by Kaplan-Meier analysis, and the survival curves were compared using a log-rank test. Multivariate analysis was conducted using the Cox proportional hazard regression model.

resultsThe 5-year distant metastasis-free survival (DMFS) rates for patients with GTVnd > 18.9 vs. ≤ 18.9 mL were 82.2% vs. 93.2% (P < 0.001), and for patients with EBV DNA copy number > 4000 vs. ≤ 4000 copies/mL were 83.5% vs. 93.9% (P < 0.001). After adjusting for GTVnd, EBV DNA copy number, and T category in the Cox regression model, both GTVnd > 18.9 mL and EBV DNA copy number > 4000 copies/mL were significantly associated with poor prognosis (both P < 0.05). According to combination of GTVnd and EBV DNA copy number, all patients were divided into low-, moderate-, and high-risk groups, with the 5-year DMFS rates of 96.1, 87.4, and 73.8%, respectively (P < 0.001). Multivariate analysis confirmed the prognostic value of this model for distant metastatic risk stratification (hazard ratio [HR], 4.17; 95% confidence interval [CI] 2.34-7.59; P < 0.001).

conclusionsGTVnd and serum EBV DNA copy number are independent prognostic factors for predicting distant metastasis in NPC patients with N1 disease. The prognostic model incorporating GTVnd and EBV DNA copy number may improve metastatic risk stratification for this group of patients.

Indexed as

DNA Copy Number VariationsDNA, ViralEpstein-Barr Virus InfectionsFemaleHerpesvirus 4, HumanHumansLymphatic MetastasisMaleNasopharyngeal CarcinomaNasopharyngeal NeoplasmsNeoplasm StagingPrognosisROC CurveSurvival AnalysisDNA, ViralDistant metastasisEpstein–Barr virus DNALymph node volumeNasopharyngeal carcinomaPrognostic model

Identifiers

PMID29284539
PMCPMC5747160

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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.