ArticleTherapeutic advances in medical oncology2022
M1 stage subdivisions based on
Article in Therapeutic advances in medical oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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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.
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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.
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Who cites it
7 citing papers in PubMed, 10 citations in OpenAlex.
- Integrated primary tumor and all metastatic lymph nodes radiomics from 18 F-FDG PET/CT for precise M1 subclassification in nasopharyngeal carcinoma.BMC cancer · 2026Article
- Article
- Real-world treatment practices and survival outcomes of patients with de novo metastatic nasopharyngeal carcinoma after chemoimmunotherapy.Cancer immunology, immunotherapy : CII · 2025Article
- The role of radiotherapy in distant nasopharyngeal carcinoma: a SEER analysis.Translational cancer research · 2025Article
- Pretreatment FDG PET in prognosis of locoregionally advanced nasopharyngeal carcinoma treated with intensity-modulated radiation therapy.International journal of medical sciences · 2025Article
- RadShap: An Explanation Tool for Highlighting the Contributions of Multiple Regions of Interest to the Prediction of Radiomic Models.Journal of nuclear medicine : official publication, Society of Nuclear Medicine · 2024Article
- Prognostic value of pre-treatment [BMC cancer · 2024Article
Corrections and comments
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Authors and funding
12 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Purpose: To establish a risk classification of de novo metastatic nasopharyngeal carcinoma (mNPC) patients based on Methods: In all, 586 de novo mNPC patients who underwent Results: Multivariate Cox regression analyses revealed that total lesion glycolysis of locoregional lesions (LRL-TLG), the number of bone metastases (BMs), metabolic tumor volume of distant soft tissue metastases (DSTM-MTV), pretreatment Epstein-Barr virus DNA (EBV DNA), and liver involvement were independent prognosticators for OS. The number of BMs, LRL-TLG, and DSTM-MTV were incorporated as the PPS. Eligible patients were divided into three stages by the RPA-risk stratification model: M1a (low risk, PPS Conclusions: The PPS-based RPA stratification model could identify suitable candidates for LRRT. Patients with stage M1a disease could benefit from LRRT.
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Registered trials
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