ArticleScientific reports2023
Identification of CT-based non-invasive radiomic biomarkers for overall survival prediction in oral cavity squamous cell carcinoma.
Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06854107 (Intratumoral and Peritumoral Habitat Radiomics of MRI Predict Pathologic Complete Response to Neoadjuvant Chemoimmunotherapy in Oral Squamous Cell Carcinoma), which is not on this map. Cited by 14 papers.
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The trial behind it
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.
Intratumoral and Peritumoral Habitat Radiomics of MRI Predict Pathologic Complete Response to Neoadjuvant Chemoimmunotherapy in Oral Squamous Cell Carcinoma
Who cites it
14 citing papers in PubMed, 21 citations in OpenAlex.
- Impact of Radiomics Parameters and Clinical Integration on Prognostication in Head and Neck Squamous Cell Carcinoma: A Multicenter Study.Life (Basel, Switzerland) · 2026Article
- Feature Selection and Machine Learning Strategies for CT Radiomics-Based Survival Prediction in Non-Small Cell Lung Cancer: A Comparative Study.Diagnostics (Basel, Switzerland) · 2026Article
- MRI-Based DeltaHabitat Radiomic Model Predicts Pathological Complete Response in Oral Cavity Cancer Treated With Neoadjuvant Chemoimmunotherapy.Cancer medicine · 2026Article
- A comparison of dimensionality reduction approaches for pre-treatment PSMA-PET/CT radiomics in prostate adenocarcinoma outcome prediction.Radiation medicine and protection · 2026Article
- Innovative Biomarkers for Oral Immunity: Advancements and Clinical Applications.Advances in experimental medicine and biology · 2026Review
- Prediction of metastasis-free survival in patients with localized prostate adenocarcinoma using primary tumor and lymph node radiomics from pre-treatment PSMA-PET/CT scans.Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology · 2025Article
- Graph feature selection for enhancing radiomic stability and reproducibility across multiple institutions in head and neck cancer.Scientific reports · 2025Article
- Value of PET radiomic features for diagnosis and reccurence prediction of newly diagnosed oral squamous cell carcinoma.Scientific reports · 2025Article
- The role of molecular biomarkers in the diagnosis, prognosis, and treatment stratification of oral squamous cell carcinoma: A comprehensive review.The journal of liquid biopsy · 2025Review
- Machine learning predicts conventional imaging metastasis-free survival (MFS) for oligometastatic castration-sensitive prostate cancer (omCSPC) using prostate-specific membrane antigen (PSMA) PET radiomics.Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology · 2024Article
- Radiomic Biomarkers of Locoregional Recurrence: Prognostic Insights from Oral Cavity Squamous Cell Carcinoma preoperative CT scans.Research square · 2024Article
- Leukotriene B4 receptor knockdown affects PI3K/AKT/mTOR signaling and apoptotic responses in colorectal cancer.Biomolecules & biomedicine · 2024Article
- Article
- Radiomic biomarkers of locoregional recurrence: prognostic insights from oral cavity squamous cell carcinoma preoperative CT scans.Frontiers in oncology · 2024Article
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Authors and funding
8 authors at 4 institutions in 2 countries.
Funding
Abstract
This study addresses the limited non-invasive tools for Oral Cavity Squamous Cell Carcinoma (OSCC) survival prediction by identifying Computed Tomography (CT)-based biomarkers to improve prognosis prediction. A retrospective analysis was conducted on data from 149 OSCC patients, including CT radiomics and clinical information. An ensemble approach involving correlation analysis, score screening, and the Sparse-L1 algorithm was used to select functional features, which were then used to build Cox Proportional Hazards models (CPH). Our CPH achieved a 0.70 concordance index in testing. The model identified two CT-based radiomics features, Gradient-Neighboring-Gray-Tone-Difference-Matrix-Strength (GNS) and normalized-Wavelet-LLL-Gray-Level-Dependence-Matrix-Large-Dependence-High-Gray-Level-Emphasis (HLE), as well as stage and alcohol usage, as survival biomarkers. The GNS group with values above 14 showed a hazard ratio of 0.12 and a 3-year survival rate of about 90%. Conversely, the GNS group with values less than or equal to 14 had a 49% survival rate. For normalized HLE, the high-end group (HLE > - 0.415) had a hazard ratio of 2.41, resulting in a 3-year survival rate of 70%, while the low-end group (HLE ≤ - 0.415) had a 36% survival rate. These findings contribute to our knowledge of how radiomics can be used to predict the outcome so that treatment plans can be tailored for patients people with OSCC to improve their survival.
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Registered trials
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.