ArticleCancer imaging : the official publication of the International Cancer Imaging Society2023
A prediction model of nodal metastasis in cN0 oral squamous cell carcinoma using metabolic and pathological variables.
Article in Cancer imaging : the official publication of the International Cancer Imaging Society, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 7 papers.
What it found
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Who cites it
7 citing papers in PubMed, 7 citations in OpenAlex.
- Nodal status dictates divergent prognostic drivers in oral squamous cell carcinoma: metabolic burden in pN0 vs. sarcopenia and nodal burden in pN.Frontiers in oncology · 2026Article
- Roles of Wnt ligands and receptors in oral squamous cell carcinoma.Journal of Zhejiang University. Science. B · 2025Review
- Development and validation of a prediction model for lymph node metastasis in oral squamous cell carcinoma using serum biomarkers.American journal of cancer research · 2025Article
- Predictors of Occult Metastasis and Prognostic Factors in Patients with cN0 Oral Cancer Who Underwent Elective Neck Dissection.Diseases (Basel, Switzerland) · 2024Article
- Prognostic Utility of Neck Lymph Node-to-Primary Tumor Standardized Uptake Value Ratio in Oral Cavity Cancer.Biomedicines · 2023Article
- Correction: A prediction model of nodal metastasis in cN0 oral squamous cell carcinoma using metabolic and pathological variables.Cancer imaging : the official publication of the International Cancer Imaging Society · 2023Article
- A 3 M Evaluation Protocol for Examining Lymph Nodes in Cancer Patients: Multi-Modal, Multi-Omics, Multi-Stage Approach.Technology in cancer research & treatmentReview
Corrections and comments
- Erratum issued
Authors and funding
9 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe efficacy of
methodsConsecutive cN0 OSCC patients with preoperative
resultsNodal maximum standardized uptake value(nodal SUVmax) and pathological T stage were selected as significant variables. A prediction model incorporating the two variables was used to plot a nomogram. The area under the curve was 0.871(Standard Error [SE], 0.035; 95% Confidence Interval [CI], 0.787-0.931) in the training cohort, and 0.809(SE, 0.069; 95% CI, 0.666-0.910) in the validation cohort, with good calibration demonstrated.
conclusionsA prediction model incorporates metabolic and pathological variables has good performance for predicting nodal metastasis in cN0 OSCC patients. However, further studies with large populations are needed to verify our findings.
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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.