ArticleEuropean radiology2023
Prediction of outcomes in patients with local recurrent nasopharyngeal carcinoma: development and validation of a four-factor prognostic model integrating baseline characteristics and [
Article in European radiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 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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Who cites it
6 citing papers in PubMed, 9 citations in OpenAlex.
- [Predictive value ofZhong nan da xue xue bao. Yi xue ban = Journal of Central South University. Medical sciences · 2026Article
- Multimodal glyco-lipid-EBVDNA signature prognostic model for individualized risk stratification of locally advanced nasopharyngeal carcinoma.European journal of nuclear medicine and molecular imaging · 2026Article
- 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
- Deep learning-radiomics-SUVmax integration fromFrontiers in oncology · 2026Article
- Impact of the radiotherapy rhythm on prognosis in nasopharyngeal carcinoma.Annals of medicine · 2024Article
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Authors and funding
12 authors at 2 institutions in 1 country.
Funding
Abstract
objectivesTo investigate the prognostic value of [
methodsA total of 358 lrNPC patients seen from 2010 to 2019 at Sun Yat-sen University Cancer Center with complete baseline characteristics and [
resultsMultivariate Cox analysis results suggested that age ≥ 47 years (hazard ratio (HR), 1.62 (1.18-2.24); p = 0.003)，with smoking history (HR, 1.41 (1.01-1.98); p = 0.046), recurrent T stage {[rT3 vs rT1/2: HR, 1.81 (1.04-3.12); p = 0.037]; [rT4 vs rT1/2: HR, 2.46 (1.32-4.60); p = 0.005]}, and TLG {[37.1-184.3 vs ≤ 37.1: HR, 2.26 (1.49-3.42); p < 0.001]; [>184.3 vs ≤ 37.1: HR, 4.31 (2.50-7.43); p < 0.001]) were independent predictors of OS. A 4-factor nomogram was generated to stratify patients into 3 risk groups. This novel model showed good discrimination with a high C-index (0.752, 95%CI: 0.714-0.790). In addition, the calibration curves showed good agreement between the predicted probabilities and actual observations and decision curve analysis (DCA) suggested that the nomogram was useful for clinical decision-making.
conclusionsOur study confirmed that [ KEY POINTS: • [
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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.