COST-UTILITY ANALYSIS OF ERIBULIN VERSUS DACARBAZINE IN ADVANCED LIPOSARCOMA IN INDIA: A MARKOV MODEL-BASED ECONOMIC EVALUATION
Author(s)
Norah E. Shynu, PharmD1, Shruthi Ashok Kumar, PharmD2, Arathi Viswam, PharmD3, Anna Ankita, PharmD3, Adusumilli Pramod Kumar, PhD3.
1Student, M S Ramaiah University Of Applied Sciences, Bengaluru, India, 2M S Ramaiah University Of Applied Sciences, Bengaluru, India, 3M S Ramaiah University Of Applied Sciences, Bangalore, India.
1Student, M S Ramaiah University Of Applied Sciences, Bengaluru, India, 2M S Ramaiah University Of Applied Sciences, Bengaluru, India, 3M S Ramaiah University Of Applied Sciences, Bangalore, India.
OBJECTIVES: To evaluate the cost-effectiveness of eribulin compared with dacarbazine in patients with advanced liposarcoma using a Markov model from the Indian healthcare perspective.
METHODS: A three-state Markov model consisting of progression-free survival (PFS), progressed disease (PD), and death was developed using published clinical data.. The model employed a 3-week cycle length and a 10-year time horizon. Direct medical costs, including treatment, monitoring, adverse-event management, and supportive care, were incorporated. Health outcomes were expressed as quality-adjusted life years (QALYs). Future costs and outcomes were discounted at 3% annually. Incremental costs, incremental QALYs, and incremental cost-effectiveness ratios (ICERs) were estimated. Model uncertainty was explored through sensitivity analyses.
RESULTS: Over the 10-year time horizon, eribulin generated 0.5255 QALYs at a total cost of ₹2,692,497.52 (€25,039.23), whereas dacarbazine generated 0.3916 QALYs at a total cost of ₹581,255.69 (€5,405.79). Eribulin resulted in an incremental gain of 0.1340 QALYs and an additional cost of ₹2,111,241.83 (€19,633.45). The corresponding ICER was ₹15,760,808 per QALY gained (€146,575.35 per QALY gained). Sensitivity analyses identified treatment acquisition costs and survival outcomes as the primary drivers of cost-effectiveness. Probabilistic sensitivity analysis demonstrated that eribulin remained unlikely to be cost-effective in the majority of simulations despite providing improved health outcomes.
CONCLUSIONS: Eribulin provided additional quality-adjusted survival compared with dacarbazine but required substantially higher expenditure. Based on current pricing, the treatment is unlikely to represent a cost-effective option within commonly referenced Indian willingness-to-pay thresholds.
METHODS: A three-state Markov model consisting of progression-free survival (PFS), progressed disease (PD), and death was developed using published clinical data.. The model employed a 3-week cycle length and a 10-year time horizon. Direct medical costs, including treatment, monitoring, adverse-event management, and supportive care, were incorporated. Health outcomes were expressed as quality-adjusted life years (QALYs). Future costs and outcomes were discounted at 3% annually. Incremental costs, incremental QALYs, and incremental cost-effectiveness ratios (ICERs) were estimated. Model uncertainty was explored through sensitivity analyses.
RESULTS: Over the 10-year time horizon, eribulin generated 0.5255 QALYs at a total cost of ₹2,692,497.52 (€25,039.23), whereas dacarbazine generated 0.3916 QALYs at a total cost of ₹581,255.69 (€5,405.79). Eribulin resulted in an incremental gain of 0.1340 QALYs and an additional cost of ₹2,111,241.83 (€19,633.45). The corresponding ICER was ₹15,760,808 per QALY gained (€146,575.35 per QALY gained). Sensitivity analyses identified treatment acquisition costs and survival outcomes as the primary drivers of cost-effectiveness. Probabilistic sensitivity analysis demonstrated that eribulin remained unlikely to be cost-effective in the majority of simulations despite providing improved health outcomes.
CONCLUSIONS: Eribulin provided additional quality-adjusted survival compared with dacarbazine but required substantially higher expenditure. Based on current pricing, the treatment is unlikely to represent a cost-effective option within commonly referenced Indian willingness-to-pay thresholds.
Conference/Value in Health Info
2026-11, ISPOR Europe 2026, Vienna, Austria
Value in Health, Volume 29, Issue 12S
Code
CO211
Topic
Clinical Outcomes, Economic Evaluation, Epidemiology & Public Health
Topic Subcategory
Comparative Effectiveness or Efficacy
Disease
No Additional Disease & Conditions/Specialized Treatment Areas, Oncology, Personalized & Precision Medicine