Head and neck cancer risk calculator (HaNC-RC) – v.2. adjustments and addition of symptoms and social history factors

Tikka, Theofano and Kavanagh, Kimberley and Lowit, Anja and Jiafeng, Pan and Burns, Harry and Nixon, Iain J. and Paleri, Vinidh and MacKenzie, Kenneth (2020) Head and neck cancer risk calculator (HaNC-RC) – v.2. adjustments and addition of symptoms and social history factors. Clinical Otolaryngology. ISSN 1749-4478

[img]
Preview
Text (Tikka-etal-CO-2020-Head-and-neck-cancer-risk-calculator)
Tikka_etal_CO_2020_Head_and_neck_cancer_risk_calculator.pdf
Final Published Version
License: Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 logo

Download (324kB)| Preview

    Abstract

    Objectives: Head and neck cancer (HNC) diagnosis through the 2-week wait, urgent suspicion of cancer (USOC) pathway has failed to increase early cancer detection rates in the UK. A head and neck cancer risk calculator (HaNC-RC) has previously been designed to aid referral of high-risk patients to USOC clinics (predictive power: 77%). Our aim was to refine the HaNC-RC to increase its prediction potential. Design: Following sample size calculation, prospective data collection and statistical analysis of referral criteria and outcomes. Setting: Large tertiary care cancer centre in Scotland. Participants: 3531 new patients seen in routine, urgent and USOC head and neck (HaN) clinics. Main outcome measures: Data collected were as follows: demographics, social history, presenting symptoms and signs and HNC diagnosis. Univariate and multivariate regression analysis were performed to identify significant predictors of HNC. Internal validation was performed using 1000 sample bootstrapping to estimate model diagnostics included the area under the receiver operator curve (AUC), sensitivity and specificity. Results: The updated version of the risk calculator (HaNC-RC v.2) includes age, gender, unintentional weight loss, smoking, alcohol, positive and negative symptoms and signs of HNC. It has achieved an AUC of 88.6% with two recommended triage referral cut-offs to USOC (cut-off: 7.1%; sensitivity: 85%, specificity: 78.3%) or urgent clinics (cut-off: 2.2%; sensitivity: 97.1%; specificity of 52.9%). This could redistribute cancer detection through USOC clinics from the current 60.9%–85.2%, without affecting total numbers seen in each clinical setting. Conclusions: The use of the HaNC-RC v.2 has a significant potential in both identifying patients at high risk of HNC early thought USOC clinics but also improving health service delivery practices by reducing the number of inappropriately urgent referrals.