Pharmacoeconomic Evaluation of Abiraterone Acetate Versus Cabazitaxel in the Treatment of Metastatic Castration-Resistant Prostate Cancer in Kazakhstan

Abstract

is associated with decreased quality of life, and poorer health outcomes. Therefore, there may be considerable gains in the adequate treatment of depression in oncology patients. We explored the cost-effectiveness of a collaborative care intervention specifically developed for the treatment of depression in cancer patients compared to usual practice. Methods: A cost-effectiveness analysis comparing a collaborative care intervention for depression management, Depression Care for People with Cancer (DCPC), in addition to usual care with usual care alone, based on data from the second Symptom Management Research Trials in Oncology (SMaRT-2). SMaRT-2 was a large (n= 500), multicentre study, in depressed patients with a relatively good cancer prognosis, in a secondary care setting. Outcomes included costs expressed as UK sterling in 2010-11 prices and health outcomes in quality-adjusted life-years (QALYs), estimated from a National Health Service and Personal Social Services perspective. Scenario analyses were performed to determine the impact on cost-effectiveness of alternative costing assumptions, and uncertainty was characterised through cost-effectiveness acceptability curves and probabilities of cost-effectiveness at key cost-effectiveness thresholds. Results: DCPC in addition to usual care was associated with greater costs, but also improved health outcomes. DCPC was found to be cost-effective at accepted cost-effectiveness thresholds. Results were robust across alternative scenarios, with probabilities of cost-effectiveness higher than 90% for cost-effectiveness thresholds ranging between £20,000-30,000 per QALY. ConClusions: Compared to usual care, DCPC in addition to usual care is likely to be cost-effective at current UK cost-effectiveness thresholds. This contributes to the growing evidence on the cost-effectiveness of collaborative care interventions for the treatment of comorbid depression. Future research will use a decision modelling approach to extrapolate trial-based results across a longer time horizon, and incorporate other relevant sources of evidence.