ArticleTherapeutic advances in medical oncology2020
Risk stratification for nasopharyngeal carcinoma: a real-world study based on locoregional extension patterns and Epstein-Barr virus DNA load.
Article in Therapeutic advances in medical oncology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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.
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.
Who cites it
12 citing papers in PubMed, 21 citations in OpenAlex.
- CD44 expression associates with EBV LMP1, reduced CD8⁺ T cell infiltration, and lower PD-L1 combined positive score in nasopharyngeal carcinoma.Infectious agents and cancer · 2026Article
- Augmenting medical image specific foundation model with classical radiomic signatures for improved nasopharyngeal carcinoma stage classification.Frontiers in medical technology · 2026Article
- Integrated Early CRP Kinetics and Plasma EBV DNA Clearance as Prognostic Biomarkers in De Novo Metastatic Nasopharyngeal Carcinoma Treated with First-Line Chemoimmunotherapy.Journal of inflammation research · 2025Article
- Risk stratification of LA-NPC during chemoradiotherapy based on clinical classification and TVRR.Cancer medicine · 2024Article
- Nomogram Based on Hemoglobin, Albumin, Lymphocyte and Platelet Score to Predict Overall Survival in Patients with T3-4N0-1 Nasopharyngeal Carcinoma.Journal of inflammation research · 2023Article
- Article
- Article
- Review
- Residual Volume of Lymph Nodes During Chemoradiotherapy Based Nomogram to Predict Survival of Nasopharyngeal Carcinoma Patient Receiving Induction Chemotherapy.Frontiers in oncology · 2021Article
- Prognostic Value of Plasma Epstein-Barr Virus DNA Levels Pre- and Post-Neoadjuvant Chemotherapy in Patients With Nasopharyngeal Carcinoma.Frontiers in oncology · 2021Article
- First-Line Immunochemotherapy Versus Palliative Chemotherapy Plus Definitive Radiation Therapy forCancer control : journal of the Moffitt Cancer CenterArticle
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
aimThe present study aimed to evaluate the combined value of locoregional extension patterns (LEPs) and circulating cell-free Epstein-Barr virus (cf EBV) DNA for risk stratification of locoregionally advanced nasopharyngeal carcinoma (LA-NPC) to better guide therapeutic strategies.
methodsA total of 7227 cases of LA-NPC were reviewed retrospectively and classified into six groups according to their LEP (ascending, descending, or mixed type) and pre-treatment cf EBV-DNA load (⩾
resultsSurvival curves for the low, intermediate, and high-risk clusters were significantly different for all endpoints. The 5-year survival rate for the low, intermediate, and high-risk clusters, respectively, were: PFS (83.5%, 73.2%, 62.6%,
conclusionOur results could facilitate the development of risk-stratification and risk-adapted therapeutic strategies for patients with LA-NPC.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.