Academic journal article Applied Health Economics and Health Policy

Cost Effectiveness of Chemoprevention for Prostate Cancer with Dutasteride in a High-Risk Population Based on Results from the REDUCE Clinical Trial

Academic journal article Applied Health Economics and Health Policy

Cost Effectiveness of Chemoprevention for Prostate Cancer with Dutasteride in a High-Risk Population Based on Results from the REDUCE Clinical Trial

Article excerpt


In attempts to reduce the clinical, economic and patient burden of prostate cancer (PCa), 5-alpha reductase inhibitors (5ARIs) have been studied and have shown promising results.[1,2] Finasteride has been shown to reduce incidence of PCa by 24.8% in men with prostate-specific antigen (PSA) <3.0 ng/mL in the Prostate Cancer Prevention Trial.[1] In a recent international, double-blind, placebo-controlled, multicentre, clinical trial (REDUCE [Reduction by Dutasteride of Prostatic Cancer Events]), dutasteride (0.5 mg/day) was shown to reduce the risk of PCa by 22.8% compared with placebo, without a significant increase in high-grade PCa in men with a negative biopsy and PSA >2.5 ng/mL at baseline.[2]

Preventive treatments have more upfront costs than disease treatment methods. Thus, it is important to understand the value a preventive agent can provide in offsetting these upfront drug costs. However, due to expense, few head-to-head, real-world economic studies are conducted to explore this. Decision-analytic modelling can be conducted to estimate the impact on outcomes until these data become available. In this study, we developed a decision-analytic model, based on prior 5ARI models for PCa prevention, to compare costs and outcomes associated with the use of dutasteride in the US for chemoprevention of PCa based on REDUCE in a population at increased risk.


We developed a Markov model (figure 1) in Microsoft® Excel to compare costs and outcomes of chemoprevention with dutasteride compared with placebo along with usual care of no pharmacological treatment in men at increased risk for PCa.

Fig. 1 Schematic representation of the Markov model. 1 Patients can progress to death from any health state. 2 Patients in this health state progress through a series of ten tunnel states to account for time-dependent risk of recurrence. Reproduced from Earnshaw et al.,[3] with permission from Adis, a Wolters Kluwer business (© Adis Data Information BV [2010]. All rights reserved). BPH = benign prostate hyperplasia; PCa = prostate cancer. [Figure omitted.]

Healthy (no PCa or benign prostate hyperplasia [BPH]) men at increased risk for PCa enter the model, where they receive usual care, with either dutasteride or placebo, and progress annually through a number of health states. Based on treatment, men can remain cancer free, develop BPH symptoms, develop PCa or die. Men progressing to BPH experience symptoms and may experience other BPH-related issues such as acute urinary retention (AUR) and BPH-related surgeries. Men progressing to PCa develop either low- or high-grade PCa and receive the appropriate treatment for their cancer. Patients who respond to PCa treatment either have an immediate recurrence or move to an at risk for recurrence health state. A man's risk of recurrence depends on the number of years he has been in remission.[1] As a result, men may progress through a series of ten 'at risk for recurrence' tunnel states. Men having a recurrence move to the 'recurrence' health state and receive treatment for their recurrent PCa. Patients with PCa who continue to be in remission after 10 years and men who have had a recurrence progress to the 'post-recurrence' health state. Death is an absorbing state to which men may progress from any health state at any time. Details of this model are provided in Earnshaw et al.[3]

Men were simulated to be followed annually over 4-, 10-year and lifetime time horizons to estimate patient outcomes. A time horizon of 10 years was thought to be a timeframe during which men would realistically continue to take dutasteride and was considered to be the base-case time horizon. To populate the model, efficacy data were taken from published clinical trials. Resource use, utilities and cost data were drawn from published literature and standard US costing sources. Costs and outcomes were discounted at 3% per annum. The analysis was performed from a payer perspective. …

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