Quality of life and toxicity guided treatment plan optimisation for head and neck cancer.

• Quality of Life (QOL)-optimised radiotherapy for head and neck cancer. • Efficient and consistent QOL-weighted NTCP-guided optimisation. • Prioritised sparing of OARs related to high impact toxicities. • QOL-based treatment plan evaluation and selection. • Systematic improvement of QOL compared to conventional VMAT. To evaluate the feasibility of semi-automatic Quality of Life (QOL)-weighted normal tissue complication probability (NTCP)-guided VMAT treatment plan optimisation in head and neck cancer (HNC) and compare predicted QOL to that obtained with conventional treatment. This study included 30 HNC patients who were treated with definitive radiotherapy. QOL-weighted NTCP-guided VMAT plans were optimised directly on 80 multivariable NTCP models of 20 common toxicities and symptoms on 4 different time points (6, 12, 18 and 24 months after radiotherapy) and each NTCP model was weighted relative to its impact on QOL. Planning results, NTCP and predicted QOL were compared with the clinical conventional VMAT plans. QOL-weighted NTCP-guided VMAT plans were clinically acceptable, had target coverage equally adequate as the clinical plans, but prioritised sparing of organs at risk (OAR) related to toxicities and symptoms that had the highest impact on QOL. NTCP was reduced for, e.g., dysphagia (−6.1% for ≥grade 2/−7.6% for ≥grade 3) and moderate-to-severe fatigue/speech problems/hoarseness (−0.7%/−1.5%/−2.5%) at 6 months, respectively. Concurrently, the average NTCP of toxicities related to salivary function increased with +0.4% to +5.7%. QOL-weighted NTCP-guided plans were produced in less time, were less dependent on the treatment planner experience and yielded more consistent results. The average predicted QOL improved by 0.7, 0.9, 1.0, and 1.1 points on a 0–100 scale (p < 0.001) at 6, 12, 18, and 24 months, respectively, compared to the clinical plans. Semi-automatic QOL-weighted NTCP-guided VMAT treatment plan optimisation is feasible. It prioritised sparing of OARs related to high-impact toxicities and symptoms and resulted in a systematic improvement of predicted QOL compared to conventional VMAT. [ABSTRACT FROM AUTHOR]