ArticleCancers2021
A Prospectively Validated Prognostic Model for Patients with Locally Advanced Squamous Cell Carcinoma of the Head and Neck Based on Radiomics of Computed Tomography Images.
Article in Cancers, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 2 of them syntheses that pooled it.
What it found
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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.
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.
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Who cites it
11 citing papers in PubMed, 2 syntheses or guidelines pooled it, 30 citations in OpenAlex.
- Role of radiomics as a predictor of disease recurrence in ovarian cancer: a systematic review.Abdominal radiology (New York) · 2024Pooled it
- Clinical predictive models for recurrence and survival in treated laryngeal and hypopharyngeal cancer: a systematic review and meta-analysis.Frontiers in oncology · 2024Pooled it
- Regionally modulated radiomics analysis in PET/CT imaging: application to prognosis prediction of head and neck cancer.Physical and engineering sciences in medicine · 2026Article
- Construction and validation of a prognostic nine-gene signature associated with radiosensitivity in head and neck squamous cell carcinoma.Clinical and translational radiation oncology · 2023Article
- Artificial intelligence-driven radiomics study in cancer: the role of feature engineering and modeling.Military Medical Research · 2023Review
- Article
- Prognostic value ofEJNMMI research · 2023Article
- Head and neck cancer treatment outcome prediction: a comparison between machine learning with conventional radiomics features and deep learning radiomics.Frontiers in medicine · 2023Article
- Gross tumour volume radiomics for prognostication of recurrence & death following radical radiotherapy for NSCLC.NPJ precision oncology · 2022Article
- Article
- Dynamic Risk Prediction via a Joint Frailty-Copula Model and IPD Meta-Analysis: Building Web Applications.Entropy (Basel, Switzerland) · 2022Article
Corrections and comments
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Authors and funding
20 authors at 10 institutions in 4 countries.
Funding
Abstract
backgroundLocoregionally advanced head and neck squamous cell carcinoma (HNSCC) patients have high relapse and mortality rates. Imaging-based decision support may improve outcomes by optimising personalised treatment, and support patient risk stratification. We propose a multifactorial prognostic model including radiomics features to improve risk stratification for advanced HNSCC, compared to TNM eighth edition, the gold standard. PATIENT AND
methodsData of 666 retrospective- and 143 prospective-stage III-IVA/B HNSCC patients were collected. A multivariable Cox proportional-hazards model was trained to predict overall survival (OS) using diagnostic CT-based radiomics features extracted from the primary tumour. Separate analyses were performed using TNM8, tumour volume, clinical and biological variables, and combinations thereof with radiomics features. Patient risk stratification in three groups was assessed through Kaplan-Meier (KM) curves. A log-rank test was performed for significance (
resultsA model combining an 11-feature radiomics signature, clinical and biological variables, TNM8, and volume could significantly stratify the validation cohort into three risk groups (
conclusionA combination of radiomics features with other predictors can predict OS very accurately for advanced HNSCC patients and improves on the current gold standard of TNM8.
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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.