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IFHNOS 2026
Impact of an Outcome Prediction Model on Clinician Confidence and Treatment Recommendations in Older Patients with Head and Neck Cancer
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Institution: University of New South Wales - NSW, Australia

Aims: To evaluate whether an outcome prediction model influences clinician confidence and treatment recommendations for older patients undergoing radiotherapy for head and neck cancer (HNC). Methodology: Radiation oncologists treating HNC in Australia & New Zealand participated in a survey comprising 5 clinical vignettes of HNC presentations in patients ≥70 years. These represented stage II oropharynx squamous cell carcinoma (SCC), stage III larynx SCC, stage IVA oropharynx SCC, stage I tonsillar SCC and stage I larynx SCC. Each vignette included relevant patient and tumour details. Clinicians selected recommendations for treatment intent, radiotherapy and systemic therapy from predefined options and rated their confidence in decision-making (0-100 scale). Model-predicted risks of recurrence (locoregional and distant) and non-cancer mortality were then presented, and clinicians updated their recommendations and confidence. Changes in confidence were analysed using paired t-tests. Results: 44 clinicians participated, of whom 59% of clinicians reported being comfortable using prediction models to support clinical decision-making, 16% were uncomfortable and 23% were neutral. Mean (95% CI) confidence across all cases increased from 73.7 (71.2-76.2) to 78.0 (75.6-80.4) points after presentation of model-based risks. Confidence increased significantly in 3 vignettes with mean increases of 7.9 (p <0.01, stage III larynx), 5.3 (p =0.03, stage 1 oropharynx) and 6.4 (p <0.01, stage IVA oropharynx) points; but decreased by a mean -4.5 points in 1 vignette (p =0.04, stage I larynx).Treatment recommendations changed for 7 of 220 decision points (3.2%) across 4 vignettes (no changes for stage I larynx). Conclusion: The prediction model increased clinician confidence by 4.3 points with minimal impact on treatment recommendations. These findings suggest value for clinical decision-support, but highlight the need for further evaluation of clinical impact.
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Dr Farhannah Aly - , Dr Joseph Descallar - , Dr Kristy Robledo - , A/Prof Purnima Sundaresan - , Prof Lois Holloway - , Prof Shalini Vinod -