ArticleCancers2025
Development and Internal Evaluation of AI-Assisted Cervical Muscle-Based Scores (FUNC-RISK) in Head and Neck Cancer: A Pilot Study.
Article in Cancers, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- FocusedON-BC: A Robust Deep Learning Framework for Automated Body Composition Assessment.Nutrients · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundAn accurate prognostic assessment is essential to optimize treatment strategies in head and neck cancer (HNC). This study aimed to develop and internally evaluate an AI-assisted survival risk score derived from automatically quantified cervical muscle parameters on routine radiotherapy-planning CT scans.
methodsPretreatment CT images were processed in a single-center cohort of 65 HNC patients, using AI-assisted automated segmentation to obtain the cervical skeletal muscle index (SMI), intramuscular adipose tissue area (IMAT), and mean muscle attenuation (HU). A multivariable Cox regression model was used to generate the continuous FUNC-RISK score, and model performance was assessed using time-dependent ROC curves at 36 and 60 months.
resultsPatient-, tumor-, and treatment-related characteristics were not predictive of survival. SMI (
conclusionsFUNC-RISK provides preliminary evidence of clinically meaningful prognostic stratification based on AI-derived cervical muscle quantity and quality metrics obtained from routine radiotherapy-planning CT scans. These exploratory results support the potential role of automated body-composition analysis in personalized risk assessment for HNC, although external multicenter validation is required before clinical implementation.
Indexed as
Identifiers
What OpenQuestion holds
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.