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Risk prediction models for head and neck cancer: A rapid review
Craig D L Smith1,2, Alex D McMahon1, Alastair Ross1
1School of Medicine, Dentistry, and Nursing University of Glasgow Glasgow UK.
Background:
Cancer risk assessment models are used to support prevention and early detection. However, few models have been developed for head and neck cancer (HNC).
Methods:
A rapid review of Embase and MEDLINE identified n = 3045 articles. Following dual screening, n = 14 studies were included. Quality appraisal using the PROBAST (risk of bias) instrument was conducted, and a narrative synthesis was performed to identify the best performing models in terms of risk factors and designs.
Results:
Six of the 14 models were assessed as "high" quality. Of these, three had high predictive performance achieving area under curve values over 0.8 (0.87-0.89). The common features of these models were their inclusion of predictors carefully tailored to the target population/anatomical subsite and development with external validation.
Conclusions:
Some existing models do possess the potential to identify and stratify those at risk of HNC but there is scope for improvement.
