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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.
Laryngoscope Investigative Otolaryngology
|December 22, 2022
Summary
Few head and neck cancer (HNC) risk models exist. High-quality models with tailored predictors and external validation show promise for identifying and stratifying HNC risk.
Area of Science:
- Oncology
- Biostatistics
- Epidemiology
Background:
- Cancer risk assessment models are crucial for prevention and early detection strategies.
- A significant gap exists in the availability of validated risk assessment models specifically for head and neck cancer (HNC).
Purpose of the Study:
- To conduct a rapid review to identify and evaluate existing risk assessment models for head and neck cancer.
- To determine the performance and quality of identified HNC risk models.
Main Methods:
- A comprehensive literature search of Embase and MEDLINE identified 3045 articles.
- 14 studies were included after dual screening, with quality appraisal using the PROBAST instrument.
- Narrative synthesis was employed to identify best-performing models based on risk factors and study designs.
Main Results:
- Six of the 14 included models were rated as "high" quality.
- Three high-quality models demonstrated excellent predictive performance, with AUC values ranging from 0.87 to 0.89.
- Key features of the best-performing models included tailored predictors for specific populations/subsites and external validation.
Conclusions:
- Existing head and neck cancer risk assessment models show potential for identifying and stratifying individuals at risk.
- There is a clear need for further development and refinement of HNC risk models to enhance their accuracy and utility.
