ArticleEuropean journal of nuclear medicine and molecular imaging2021
Nomogram for the prediction of primary distant metastasis of nasopharyngeal carcinoma to guide individualized application of FDG PET/CT.
Article in European journal of nuclear medicine and molecular imaging, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06831357 (Development and Multicenter Validation of a Deep Learning Model Based on Whole Slide Imaging and Magnetic Resonance Imaging of the Nasopharynx and Lymph Nodes to Predict Distant Metastases at Diagnosis in Nasopharyngeal Carcinoma), which is not on this map. Cited by 12 papers.
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Development and Multicenter Validation of a Deep Learning Model Based on Whole Slide Imaging and Magnetic Resonance Imaging of the Nasopharynx and Lymph Nodes to Predict Distant Metastases at Diagnosis in Nasopharyngeal Carcinoma
Who cites it
12 citing papers in PubMed.
- 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
- Diagnostic and Economic Evaluation of [Journal of clinical medicine · 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
- Predictability of peripheral blood inflammatory markers in prediction of lymph node metastasis in gastric cancer.Therapeutic advances in gastroenterology · 2026Article
- Deep learning-radiomics-SUVmax integration fromFrontiers in oncology · 2026Article
- Article
- Early detection of positive urine culture in patients with urolithiasis: a machine learning model with dynamic online nomogram.Annals of medicine · 2025Article
- Pretreatment FDG PET in prognosis of locoregionally advanced nasopharyngeal carcinoma treated with intensity-modulated radiation therapy.International journal of medical sciences · 2025Article
- A Nomogram Prognostic Model for Advanced Hepatocellular Carcinoma Based on the Interaction Between CD8OncoTargets and therapy · 2023Article
- Deep Learning for Predicting Distant Metastasis in Patients with Nasopharyngeal Carcinoma Based on Pre-Radiotherapy Magnetic Resonance Imaging.Combinatorial chemistry & high throughput screening · 2023Article
- Development and validation of a machine learning model to predict the risk of lymph node metastasis in renal carcinoma.Frontiers in endocrinology · 2022Article
- Prognostic Relevance of 18F-FDG-PET/CT-Guided Target Volume Delineation in Loco-Regionally Advanced Nasopharyngeal Carcinomas: A Comparative Study.Frontiers in oncology · 2021Article
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Authors and funding
22 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeThis study aimed to establish an effective nomogram to predict primary distant metastasis (DM) in patients with nasopharyngeal carcinoma (NPC) to guide the application of PET/CT.
methodsIn total, 3591 patients with pathologically confirmed NPC were consecutively enrolled. The nomogram was constructed based on 1922 patients treated between 2007 and 2014. Multivariate logistical regression was applied to identify the independent risk factors of DM. The predictive value of the nomogram was evaluated using the concordance index (C-index), calibration curve, probability density functions (PDFs), and clinical utility curve (CUC). The results were validated in 1669 patients enrolled from 2015 to 2016. Net reclassification improvement (NRI) was applied to compare performances of the nomogram with other clinical factors. The best cut-off value of the nomogram chosen for clinical application was analyzed.
resultsA total of 355 patients showed primary DM among 3591 patients, yielding an incidence rate of 9.9%. Sex, N stage, EBV DNA level, lactate dehydrogenase level, and hemoglobin level were independent predictive factors for primary DM. C-indices in the training and validation cohort were 0.796 (95% CI, 0.76-0.83) and 0.779 (95% CI, 0.74-0.81), respectively. The NRI indices demonstrated that this model had better predictive performance than plasma EBV DNA level and N stage. We advocate for a threshold probability of 3.5% for guiding the application of PET/CT depending on the clinical utility analyses.
conclusionThis nomogram is a useful tool to predict primary DM of NPC and guide the clinical application of PET/CT individually at the initial staging.
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