Cost-Effectiveness Analysis of Sarcopenia Management Interventions in Iran Publisher Pubmed



Darvishi A^{1, 2} ; Shafiee G¹ ; Balajam NZ³ ; Hemami MR⁴ ; Ostovar N¹ ; Heshmat R^{1, 3}
Source: BMC Public Health Published:2023

Abstract

Objectives: Identification the optimal management intervention of sarcopenia is a concern of health systems. We aimed to analyze the cost-effectiveness of sarcopenia management strategies in Iran. Methods: We constructed a lifetime Markov model based on natural history. The strategies comparedincluded exercise training, nutritional supplements, whole body vibration (WBV), and various exercise interventions and nutritional supplement combinations. A total of 7 strategies was evaluated in addition to the non-intervention strategy. Parameter values were extracted from primary data and the literature, and the costs and Quality-adjusted life years (QALYs) were calculated for each strategy. Deterministic and probabilistic sensitivity analysis, including the expected value of perfect information (EVPI), was also performed to determine the robustness of the model. Analyses were performed using the 2020 version of TreeAge Pro software. Results: All seven strategies increased lifetime effectiveness (QALYs). The protein and Vitamin D3 (P + D) strategy had the highest effectiveness values among all strategies. After removing the dominated strategies, the estimated ICER for the P + D compared to Vitamin D3 alone (D) strategy was calculated as $131,229. Considering the cost-effectiveness threshold ($25,249), base-case results indicated that the D strategy was the most cost-effective strategy in this evaluation. Sensitivity analysis of model parameters also demonstrated the robustness of results. Also, EVPI was estimated at $273. Conclusions: Study results, as the first economic evaluation of sarcopenia management interventions, showed that despite the higher effectiveness of D + P, the D strategy was the most cost-effective. Completing clinical evidence of various intervention options can lead to more accurate results in the future. © 2023, The Author(s).