Risk prediction models for head and neck cancer: a rapid review

Smith, C. D.L., McMahon, A. D. , Ross, A. , Inman, G. J. and Conway, D. I. (2022) Risk prediction models for head and neck cancer: a rapid review. Laryngoscope Investigative Otolaryngology, 7(6), pp. 1893-1908. (doi: 10.1002/lio2.982)

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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.

Item Type:Articles
Glasgow Author(s) Enlighten ID:Smith, Craig and Inman, Professor Gareth and Ross, Dr Alastair and McMahon, Dr Alex and Conway, Professor David
Authors: Smith, C. D.L., McMahon, A. D., Ross, A., Inman, G. J., and Conway, D. I.
College/School:College of Medical Veterinary and Life Sciences > School of Cancer Sciences
College of Medical Veterinary and Life Sciences > School of Medicine, Dentistry & Nursing > Dental School
Journal Name:Laryngoscope Investigative Otolaryngology
ISSN (Online):2378-8038
Published Online:28 November 2022
Copyright Holders:Copyright © 2022 The Authors
First Published:First published in Laryngoscope Investigative Otolaryngology 7(6): 1893-1908
Publisher Policy:Reproduced under a Creative Commons license

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Project CodeAward NoProject NamePrincipal InvestigatorFunder's NameFunder RefLead Dept
315941The TRACC Programme: to Train and Retain Academic Cancer Clinicians / Year 3Gareth InmanCancer Research UK (CRUK)SEBSTF-2021\100009Institute of Cancer Sciences