Normal tissue complication probability (NTCP) models can guide clinical decision making in radiotherapy. In recent years, they have been used for patient selection for proton beam therapy (PBT) for some anatomical tumour sites. This review synthesizes the published evidence regarding the use of NTCP models to predict the toxicity of PBT, for different end points in patients with brain tumours. A search of Medline and Embase using the Patients, Intervention, Comparison, Outcome (PICO) criteria was undertaken. In total, 37 articles were deemed relevant and were reviewed in detail. Nineteen articles on NTCP modelling of toxicity end points were included. Of these, 11 were comparative NTCP studies of PBT versus conventional photon radiotherapy (XRT), which evaluated differences in plan dosimetry and then assumed that XRT-derived literature estimates of NTCP would be applicable to both. Seven papers derived NTCP models based on PBT outcome data, two of which provided model parameters. Among analysed end points, the reduced risk of secondary tumours with PBT as compared with XRT is estimated - through modelling studies - to be considerable and was highlighted by most authors. For other analysed end points, the clinical benefit of PBT mainly depends on tumour location in relation to organs at risk as well as prescription doses. NTCP models can be useful tools for treatment plan comparison. However, most published toxicity data were derived from XRT cohorts; this review has highlighted the need for further studies relating dose-volume parameters to observed toxicity in PBT-treated patients. Specifically, there is a need for PBT-specific NTCP models that can be implemented in the clinical practice. NTCP models built on robust clinical data for the most common radiotherapy toxicities in the brain would potentially redefine the current indications for PBT.
Keywords: Clinical implementation of normal tissue complication probability models; normal tissue complication probability models for patient selection in proton therapy to the brain; normal tissue complication probability models for toxicity prediction in proton beam therapy; proton beam therapy in brain malignancies; radiation-induced secondary tumours.
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