SynthesisCancer medicine2023
A systematic review and meta-analysis of predictive and prognostic models for outcome prediction using positron emission tomography radiomics in head and neck squamous cell carcinoma patients.
Synthesis in Cancer medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 2 of them syntheses that pooled it.
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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
15 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- MRI-Based Radiomics and Artificial Intelligence for Prediction of Recurrence and Prognostic Outcomes in Oral Tongue Squamous Cell Carcinoma: A Systematic Review with Functional Meta-Synthesis.Medical sciences (Basel, Switzerland) · 2026Pooled it
- A systematic review and meta-analysis of predictive and prognostic models for outcome prediction using positron emission tomography radiomics in head and neck squamous cell carcinoma patients.Cancer medicine · 2023Pooled it
- Radiomics Using Fused PET and CT Data for Prognostic and Diagnostic Modeling in Head and Neck Cancer: A Systematic Review and Meta-Analysis.Diagnostics (Basel, Switzerland) · 2026Review
- Explainable AI for Predicting Mortality Risk in Metastatic Cancer: Retrospective Cohort Study Using the Memorial Sloan Kettering-Metastatic Dataset.JMIR cancer · 2026Article
- Resistance Mechanisms in Immunotherapy-Radiotherapy/Chemotherapy Combinations in Locally Advanced Head & Neck Squamous Cell Carcinoma.Oncology research · 2026Review
- Editorial: Based models and machine learning on CT, MRI and PET-CT in head and neck cancer diagnosis, staging and outcome prediction.Frontiers in radiology · 2026Article
- Predictive Value of [Journal of clinical medicine · 2025Article
- Improving outcome prediction in oropharyngeal carcinoma through the integration of diffusion-weighted magnetic resonance imaging radiomics.Physics and imaging in radiation oncology · 2025Article
- Data Science Opportunities To Improve Radiotherapy Planning and Clinical Decision Making.Seminars in radiation oncology · 2024Review
- Recurrent Versus Metastatic Head and Neck Cancer: An Evolving Landscape and the Role of Immunotherapy.Biomedicines · 2024Review
- Article
- Role ofCancers · 2024Review
- MRI radiomics in head and neck cancer from reproducibility to combined approaches.Scientific reports · 2024Article
- Developments and future prospects of personalized medicine in head and neck squamous cell carcinoma diagnoses and treatments.Cancer reports (Hoboken, N.J.) · 2024Review
- Methodological evaluation of original articles on radiomics and machine learning for outcome prediction based on positron emission tomography (PET).Nuklearmedizin. Nuclear medicine · 2023Review
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundPositron emission tomography (PET) images of head and neck squamous cell carcinoma (HNSCC) patients can assess the functional and biochemical processes at cellular levels. Therefore, PET radiomics-based prediction and prognostic models have the potentials to understand tumour heterogeneity and assist clinicians with diagnosis, prognosis and management of the disease. We conducted a systematic review of published modelling information to evaluate the usefulness of PET radiomics in the prediction and prognosis of HNSCC patients.
methodsWe searched bibliographic databases (MEDLINE, Embase, Web of Science) from 2010 to 2021 and considered 31 studies with pre-defined inclusion criteria. We followed the CHARMS checklist for data extraction and performed quality assessment using the PROBAST tool. We conducted a meta-analysis to estimate the accuracy of the prediction and prognostic models using the diagnostic odds ratio (DOR) and average C-statistic, respectively.
resultsManual segmentation method followed by 40% of the maximum standardised uptake value (SUV
conclusionsBoth prediction and prognostic models using clinical variables and PET radiomics demonstrated reliable accuracy for detecting adverse outcomes in HNSCC, suggesting the prospect of PET radiomics in clinical settings for diagnosis, prognosis and management of HNSCC patients. Future studies of prediction and prognostic models should emphasise the quality of reporting, external model validation, generalisability to real clinical scenarios and enhanced reproducibility of results.
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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.