Evidence map›Paper›PMID 40517221›Full record

ArticleRadiation oncology (London, England)2025

Beyond the ratio of tumor reduction: residual volume after induction chemotherapy emerges as the optimal biomarker in advanced nasopharyngeal cancer.

Sixue Dong, Guangsen Pan, Zhen Zhang, Weigang Hu, Ruiping Zhai, Hongmei Ying, Jiazhou Wang

Abstract read
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Article in Radiation oncology (London, England), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Sixue Dong *Department of Radiation Oncology, Fudan University Shanghai Cancer Center, Shanghai, 200032, China.
Guangsen Pan *Department of Radiation Oncology, Fudan University Shanghai Cancer Center, Shanghai, 200032, China.
Zhen ZhangDepartment of Radiation Oncology, Fudan University Shanghai Cancer Center, Shanghai, 200032, China.
Weigang HuDepartment of Radiation Oncology, Fudan University Shanghai Cancer Center, Shanghai, 200032, China.
Ruiping ZhaiDepartment of Radiation Oncology, Fudan University Shanghai Cancer Center, Shanghai, 200032, China.
Hongmei YingDepartment of Radiation Oncology, Fudan University Shanghai Cancer Center, Shanghai, 200032, China. yinghm@hotmail.com.
Jiazhou WangDepartment of Radiation Oncology, Fudan University Shanghai Cancer Center, Shanghai, 200032, China. wjiazhou@gmail.com.

Funding

National Key Research and Development Program of China 2022YFC2404603, 2022YFC2404600National Natural Science Foundation of China 12375339, 11675042
6 · The paper itself

Abstract

purposeTo investigate and compare the prognostic value of tumor volumetric characteristics during induction chemotherapy (IC) for advanced nasopharyngeal carcinoma (NPC). MATERIALS AND

methodsA retrospective cohort of 250 patients with NPC treated with IC followed by radiotherapy or chemoradiotherapy was analyzed. Tumor volumes were measured using MRI at two time points of before-treatment and after-IC. Cohorts with high and low tumor heterogeneity were identified by analyzing the gross tumor volume (GTV) through the gray-level co-occurrence matrix (GLCM). Incorporating the clinical factors, volumetric characteristics (Vpre−IC, Vpost−IC, ΔVabs, and ΔVrel) were evaluated to identify the prognostic value using univariable and multivariable analyses in various cohorts, respectively. Kaplan-Meier survival analyses with median and optimal cutoff values were conducted. Multivariable analysis was repeated on 1 × 105 resampled cohorts with the Bootstrap method to identify the feature importance. Subgroup analyses were performed based on T-category, IC regimens, post-IC treatment protocols, and tumor changes.

resultsThere is virtually no correlation between Vpost−IC and ΔVrel with ρ = -0.08. Various analyses all suggest Vpost−IC emerged as the most robust biomarker across all endpoints (P < 0.001 ∼ 0.002), followed by ΔVrel and T-category, which were more important than the other features. The predictive value of Vpost−IC surpasses that of ΔVrel especially in the high heterogeneity cohort. Specifically, a Vpost−IC value of 20.6 cm³ could be regarded as a threshold provided optimal risk stratification for progression-free survival (PFS) and overall survival (OS).

conclusionVpost−IC is a critical biomarker for determining clinical outcomes in advanced NPC. Patients with Vpost−IC measurements above 20.6 cm³ are classified as high-risk, indicating a requirement for escalating radiotherapy and/or chemotherapy.

Indexed as

Induction ChemotherapyNasopharyngeal CarcinomaNasopharyngeal NeoplasmsNeoplasm, ResidualTumor BurdenAdultAgedBiomarkers, TumorChemoradiotherapyFemaleHumansMagnetic Resonance ImagingMaleMiddle AgedPrognosisRetrospective StudiesBiomarkers, TumorAdvanced NPCInduction chemotherapyPrognostic predictionRadiotherapyTumor volume

Identifiers

PMID40517221
PMCPMC12167576

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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.