Investigating chemotherapy adverse events : incidence, costs and consequences
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Background: In Australia, economic evaluation is an important tool in prioritising healthcare spending. Adverse events of chemotherapy affect patients’ physical health and quality of life; however, they are often excluded from chemotherapy economic evaluations. This thesis explores the incidence, costs and consequences of chemotherapy adverse events and the implications for cost-effectiveness. Key Objectives: 1. Examine how adverse events are incorporated into models of chemotherapy cost-effectiveness. 2. Develop Australia-based models of costs and consequences of four common adverse events. 3. Estimate incidence of adverse events in clinical practice. 4. Estimate costs of adverse events in clinical practice. 5. Compare rates of adverse events in clinical practice with rates reported in clinical trials. Methods: There are four components to this research. The first is a systematic review examining how adverse events are incorporated into existing models of chemotherapy cost-effectiveness (Objective 1). The second is the use of decision analytic modelling to develop models of the costs and consequences of diarrhoea, nausea/vomiting, anaemia and neutropoenia. These can then become standard components of future models of chemotherapy cost effectiveness (Objective 2). The third is the use of regression to estimate the incidence and costs of adverse events (Objectives 3 and 4) in an administrative dataset linked to routinely collected data on pharmaceutical and medical service use. Finally, an analysis of a prospective cohort of 482 individuals undergoing chemotherapy examines the frequency of adverse events (Objective 3) in comparison with those reported in clinical trials (Objective 5). Results: The systematic review revealed that adverse events are not included in models of chemotherapy cost-effectiveness in any rigorous way. The models developed demonstrate that rigorous, systematic consideration of the key costs and consequences of adverse events is possible, and provide a standard way to include adverse events in future models. Older or sicker individuals in the administrative dataset were more likely to experience adverse events, although incidence was low. Mean healthcare costs significantly increased with treatment for nausea, anaemia or neutropoenia but not diarrhoea. The prospective cohort study identified higher rates of adverse events than reported in clinical trials, with low-severity events particularly common. Conclusions: In exploring the incidence, costs and consequences of chemotherapy adverse events, this thesis demonstrates that it is possible to model the key costs and consequences of chemotherapy adverse events, and that clinical practice data may reduce bias in these models. This is a significant contribution to determining true chemotherapy costs and consequences.
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