Evidence map›Paper›PMID 34336675›Full record

ArticleFrontiers in oncology2021

Prognostic Value of Regression Rate of Plasma EBV DNA After Induction Chemotherapy for Stage II-IVA Nasopharyngeal Carcinoma.

Hao Peng, Bin-Bin Chen, Xiao-Hui Wang, Yun-Xian Mo, Fei Han

Open access · goldAbstract read
In one paragraph

Article in Frontiers in oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. 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 46% 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. Review
  2. Article
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

5 authors at 2 institutions in 1 country.

Hao PengCenter for Translational Medicine, Precision Medicine Institute, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.
Bin-Bin ChenDepartment of Radiation Oncology, Sun Yat-sen University Cancer Center, Guangzhou, China.
Xiao-Hui WangDepartment of Radiation Oncology, Sun Yat-sen University Cancer Center, Guangzhou, China.
Yun-Xian MoDepartment of Radiation Oncology, Sun Yat-sen University Cancer Center, Guangzhou, China.
Fei HanDepartment of Radiation Oncology, Sun Yat-sen University Cancer Center, Guangzhou, 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/

objectiveWe aimed to explore the prognostic value of regression rate (RR) of plasma Epstein-Barr virus (EBV) DNA after induction chemotherapy (IC) in patients with stages II-IVA nasopharyngeal carcinoma (NPC).

methodsEligible patients receiving IC followed by concurrent chemoradiotherapy were included. The cut-off value of pre-treatment EBV DNA (pre-IC DNA) and RR were identified by receiver operating curve (ROC). Recursive partitioning analysis (RPA) was applied to create new staging. Harrell's c-index and time-independent ROC were employed to compare different RPA staging.

resultsIn total, 1,184 patients were included. The cut-off values of pre-IC DNA and RR were 16,200 copies/ml and 95.127% for patients receiving two cycles, and 5,520 copies/ml and 99.994% for those receiving three cycles. Notably, we only focused on patients receiving two cycles of IC. Patients with a RR >95.127% had significantly better 5-year overall survival (OS) than those with a RR ≤95.127% (86.2%

conclusionRR in conjunction with current TNM staging could better conduct risk stratification, prognosis prediction and help to guide precise concurrent chemotherapy.

Indexed as

cumulative platinum dosedecrease rateEpstein-Barr virusinduction chemotherapynasopharyngeal carcinoma

Identifiers

PMID34336675
PMCPMC8319726
OpenAlexW3186119287

What OpenQuestion holds

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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.