Long-Term Outcomes in Hemophilia: The Impact of the Pettersson Score on Cost-Effectiveness Modelling

OBJECTIVES: The Pettersson score (PS) is a radiological scoring system used to assess the severity of joint damage in individuals with haemophilia resulting from repeated joint bleeding episodes. The PS has been used in several cost-effectiveness models (CEMs) across Health technology assessments submissions and in published literature to capture the impact of joint health in haemophilia patients. The purpose of this research is to assess the impact of the PS on long-term cost-effectiveness outcomes in haemophilia.

METHODS: A landscaping review was conducted to assess the methods used in CEMs examining technologies in haemophilia. Seven CEMs met the criteria, three of which involved the PS. A de novo Markov model was then developed, informed by the approaches taken in the identified submissions, to estimating the cost and utility implications of the PS. The CEM used four primary health states (non-joint bleeds, joint bleeds, no bleeds, and death) and included an option to transition among secondary joint-health states, quantified by the PS based on the number of accumulated joint bleeds. Hypothetical technologies were tested, with bleeding profiles informed by published results of existing novel technologies. The PS health states expressed quality of life and cost associated with deteriorating joint-health. The impact of the PS sub-model on the overall cost-effectiveness result were assessed.

RESULTS: The PS sub-model was shown to have a limited impact on the long-term cost-effectiveness outcomes in haemophilia, with an average change in incremental QALYs 10% over the tested scenarios. Incremental costs were estimated to be negligibly affected by the inclusion of the PS. This was primarily due to low number annualised joint bleed events, given the protection of novel technologies.

CONCLUSIONS: The PS, while being a useful clinical measure, has been shown to have a limited impact in cost-effectiveness results while considerably increasing the complexity and uncertainty with CEMs.