A Comparison Of Markov Cohort And Discrete Event Simulation Models In Cost-Effectiveness Analysis Of Sorafenib And Everolimus In 3rd Line Metastatic Renal-Cell Carcinoma In The Czech Republic

OBJECTIVES: Markov cohort (MC) and discrete-event simulation (DES) models are inherently different. Therefore, they are rarely used in economic evaluation of the same disease. Sorafenib and everolimus are cornerstones of current metastatic renal-cell carcinoma (mRCC) treatment in 2nd line, however,...

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Veröffentlicht in:Value in health 2017-10, Vol.20 (9), p.A752-A753
Hauptverfasser: Mlcoch, T, Lamblova, K, Ornstova, E, Dolezal, T
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Lamblova, K
Ornstova, E
Dolezal, T
description OBJECTIVES: Markov cohort (MC) and discrete-event simulation (DES) models are inherently different. Therefore, they are rarely used in economic evaluation of the same disease. Sorafenib and everolimus are cornerstones of current metastatic renal-cell carcinoma (mRCC) treatment in 2nd line, however, there are limited effectiveness/efficacy and cost-effectiveness studies in 3rd line. The first objective was to compare MC and DES models in oncology, and the second to assess the cost-effectiveness of sorafenib versus everolimus in 3rd line mRCC. METHODS: We developed two mirror life-time cost-utility models using a) Markovian and b) DES approaches, which projected quality-adjusted life-years (QALYs) and costs from healthcare payers' perspective. In MC, we used weekly cycle length and three states, i.e. progression-free, progression, death. In DES, there were progression/death events instead of states. Transition probabilities, utilities and costs were derived from published literature/sources. Costs and outcomes were discounted by 3%. Probabilistic sensitivity analysis (PSA; 10,000 simulations) was performed with Czech willingness-to-pay threshold (WTP) equal to 645,000. RESULTS: Over a lifetime horizon, sorafenib is less costly but also slightly less effective than everolimus. In MC, sorafenib is less costly by €2,045 (€11,558 vs. €13,603) and slightly less effective by 0.0028 QALYs (0.7815 vs. 0.7843). In DES, sorafenib is less costly by €2,320 (€11,326 vs. €13,646) and slightly less effective by 0.0027 QALYs (0.7927 vs. 0.7954). The ICERs, expressed as savings per QALY lost, are equal to €792,646 (MC) and €874,585 (DES). The results of PSA showed that sorafenib is cost-effective with probability of 95% (MC) and 85% (DES) at the WTR CONCLUSIONS: Despite their differences, MC and DES models yields almost identical results in simple oncologic model. The slight disparity might be due to computational differences, half-cycle correction or cycle length. Finally, sorafenib clearly proved that it is a cost-effective intervention in 3rd line therapy of mRCC.
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Therefore, they are rarely used in economic evaluation of the same disease. Sorafenib and everolimus are cornerstones of current metastatic renal-cell carcinoma (mRCC) treatment in 2nd line, however, there are limited effectiveness/efficacy and cost-effectiveness studies in 3rd line. The first objective was to compare MC and DES models in oncology, and the second to assess the cost-effectiveness of sorafenib versus everolimus in 3rd line mRCC. METHODS: We developed two mirror life-time cost-utility models using a) Markovian and b) DES approaches, which projected quality-adjusted life-years (QALYs) and costs from healthcare payers' perspective. In MC, we used weekly cycle length and three states, i.e. progression-free, progression, death. In DES, there were progression/death events instead of states. Transition probabilities, utilities and costs were derived from published literature/sources. Costs and outcomes were discounted by 3%. Probabilistic sensitivity analysis (PSA; 10,000 simulations) was performed with Czech willingness-to-pay threshold (WTP) equal to 645,000. RESULTS: Over a lifetime horizon, sorafenib is less costly but also slightly less effective than everolimus. In MC, sorafenib is less costly by €2,045 (€11,558 vs. €13,603) and slightly less effective by 0.0028 QALYs (0.7815 vs. 0.7843). In DES, sorafenib is less costly by €2,320 (€11,326 vs. €13,646) and slightly less effective by 0.0027 QALYs (0.7927 vs. 0.7954). The ICERs, expressed as savings per QALY lost, are equal to €792,646 (MC) and €874,585 (DES). The results of PSA showed that sorafenib is cost-effective with probability of 95% (MC) and 85% (DES) at the WTR CONCLUSIONS: Despite their differences, MC and DES models yields almost identical results in simple oncologic model. The slight disparity might be due to computational differences, half-cycle correction or cycle length. 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Sorafenib and everolimus are cornerstones of current metastatic renal-cell carcinoma (mRCC) treatment in 2nd line, however, there are limited effectiveness/efficacy and cost-effectiveness studies in 3rd line. The first objective was to compare MC and DES models in oncology, and the second to assess the cost-effectiveness of sorafenib versus everolimus in 3rd line mRCC. METHODS: We developed two mirror life-time cost-utility models using a) Markovian and b) DES approaches, which projected quality-adjusted life-years (QALYs) and costs from healthcare payers' perspective. In MC, we used weekly cycle length and three states, i.e. progression-free, progression, death. In DES, there were progression/death events instead of states. Transition probabilities, utilities and costs were derived from published literature/sources. Costs and outcomes were discounted by 3%. Probabilistic sensitivity analysis (PSA; 10,000 simulations) was performed with Czech willingness-to-pay threshold (WTP) equal to 645,000. RESULTS: Over a lifetime horizon, sorafenib is less costly but also slightly less effective than everolimus. In MC, sorafenib is less costly by €2,045 (€11,558 vs. €13,603) and slightly less effective by 0.0028 QALYs (0.7815 vs. 0.7843). In DES, sorafenib is less costly by €2,320 (€11,326 vs. €13,646) and slightly less effective by 0.0027 QALYs (0.7927 vs. 0.7954). The ICERs, expressed as savings per QALY lost, are equal to €792,646 (MC) and €874,585 (DES). The results of PSA showed that sorafenib is cost-effective with probability of 95% (MC) and 85% (DES) at the WTR CONCLUSIONS: Despite their differences, MC and DES models yields almost identical results in simple oncologic model. The slight disparity might be due to computational differences, half-cycle correction or cycle length. 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Therefore, they are rarely used in economic evaluation of the same disease. Sorafenib and everolimus are cornerstones of current metastatic renal-cell carcinoma (mRCC) treatment in 2nd line, however, there are limited effectiveness/efficacy and cost-effectiveness studies in 3rd line. The first objective was to compare MC and DES models in oncology, and the second to assess the cost-effectiveness of sorafenib versus everolimus in 3rd line mRCC. METHODS: We developed two mirror life-time cost-utility models using a) Markovian and b) DES approaches, which projected quality-adjusted life-years (QALYs) and costs from healthcare payers' perspective. In MC, we used weekly cycle length and three states, i.e. progression-free, progression, death. In DES, there were progression/death events instead of states. Transition probabilities, utilities and costs were derived from published literature/sources. Costs and outcomes were discounted by 3%. Probabilistic sensitivity analysis (PSA; 10,000 simulations) was performed with Czech willingness-to-pay threshold (WTP) equal to 645,000. RESULTS: Over a lifetime horizon, sorafenib is less costly but also slightly less effective than everolimus. In MC, sorafenib is less costly by €2,045 (€11,558 vs. €13,603) and slightly less effective by 0.0028 QALYs (0.7815 vs. 0.7843). In DES, sorafenib is less costly by €2,320 (€11,326 vs. €13,646) and slightly less effective by 0.0027 QALYs (0.7927 vs. 0.7954). The ICERs, expressed as savings per QALY lost, are equal to €792,646 (MC) and €874,585 (DES). The results of PSA showed that sorafenib is cost-effective with probability of 95% (MC) and 85% (DES) at the WTR CONCLUSIONS: Despite their differences, MC and DES models yields almost identical results in simple oncologic model. The slight disparity might be due to computational differences, half-cycle correction or cycle length. 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subjects Cancer
Cohort analysis
Comparable worth
Computer applications
Cost analysis
Death & dying
Efficacy
Health care
Kidney cancer
Kidney diseases
Markov analysis
Metastases
Metastasis
Oncology
Quality adjusted life years
Renal cell carcinoma
Savings
Sensitivity analysis
Simulation
Targeted cancer therapy
Willingness to pay
title A Comparison Of Markov Cohort And Discrete Event Simulation Models In Cost-Effectiveness Analysis Of Sorafenib And Everolimus In 3rd Line Metastatic Renal-Cell Carcinoma In The Czech Republic
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