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. 2021 Mar;68(1):44-51.
doi: 10.1002/jmrs.416. Epub 2020 Jul 7.

Individualised selection of left-sided breast cancer patients for proton therapy based on cost-effectiveness

Affiliations

Individualised selection of left-sided breast cancer patients for proton therapy based on cost-effectiveness

Annabelle M Austin et al. J Med Radiat Sci. 2021 Mar.

Abstract

Introduction: The significantly greater cost of proton therapy compared with X-ray therapy is frequently justified by the expected reduction in normal tissue toxicity. This is often true for indications such as paediatric and skull base cancers. However, the benefit is less clear for other more common indications such as breast cancer, and it is possible that the degree of benefit may vary widely between these patients. The aim of this work was to demonstrate a method of individualised selection of left-sided breast cancer patients for proton therapy based on cost-effectiveness of treatment.

Methods: 16 left-sided breast cancer patients had a treatment plan generated for the delivery of intensity-modulated proton therapy (IMPT) and of intensity-modulated photon therapy (IMRT) with the deep inspiration breath-hold (DIBH) technique. The resulting dosimetric data was used to predict probabilities of tumour control and toxicities for each patient. These probabilities were used in a Markov model to predict costs and the number of quality-adjusted life years expected as a result of each of the two treatments.

Results: IMPT was not cost-effective for the majority of patients but was cost-effective where there was a greater risk reduction of second malignancies with IMPT.

Conclusion: The Markov model predicted that IMPT with DIBH was only cost-effective for selected left-sided breast cancer patients where IMRT resulted in a significantly greater dose to normal tissue. The presented model may serve as a means of evaluating the cost-effectiveness of IMPT on an individual patient basis.

Keywords: Markov model; breast cancer; cost-effectiveness; proton therapy; radiobiological models.

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Conflict of interest statement

Scott Penfold works part‐time for Commercial & General. The other authors have no conflicts to disclose.

Figures

Figure 1
Figure 1
The Markov state transition diagram showing the allowed transitions between states. ‘Well’ represents perfect health. ‘Cancer’ represents the situation where the patient still has the initial primary breast cancer, ‘SPC’ represents a second primary cancer, ‘Pneum’ refers to pneumonitis and ‘HD’ represent heart disease.

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