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Updated: Jun 10, 2025

Retzius-Sparing Robot-Assisted Radical Prostatectomy
Published on: May 19, 2022
Economic evaluations of robot-assisted radical prostatectomy and the factors affecting its cost-effectiveness: a
Qing-Qiang Lei1, Hai-Nan Li1, Jin Zhao1
1School of Public Health, Fudan University, Shanghai, 200032, China.
Abstract:
This systematic review aims to summarize the progress made in the study of the cost-effectiveness of robot-assisted radical prostatectomy (RARP) worldwide and to analyze the economic factors influencing this, in an attempt to provide methodological guidance for conducting economic evaluation studies in a domestic context, and to put forward suggestions for improving the cost-effectiveness of RARP in emerging markets. We conducted a systematic literature review and analysis of studies published worldwide from January 2000 to July 2024 concerning the economic evaluation of RARP compared with laparoscopic radical prostatectomy (LRP) or open radical prostatectomy (ORP). A total of 16 papers were included. The literature was generally of good quality. Methodological approaches. varied among studies, leading to inconsistent economic findings. The choice of research settings, including the perspective of the study and time horizon, as well as differences in parameters such as surgical volumes and cost of equipment purchases, were the main factors that affected the cost-effectiveness of RARP. Based on the methodology used in the included studies, we suggest that short-term, localized economic evaluations should be carried out first, based on follow-up studies in emerging markets, whereas long-term economic evaluations can be performed when sufficient data are available. Referring to the analysis of the economic factors influencing cost-effectiveness in the included studies, we suggest that different research settings should be chosen according to the purpose for which policymakers allocate public funds, and that the cost-effectiveness of RARP can be enhanced through technical improvements and resource optimization.
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