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Mean lifetime survival estimates following solid organ transplantation in the US and UK

医学 生存分析 比例危险模型 危险系数 人口 相对存活率 肾移植 移植 人口学 外科 内科学 流行病学 置信区间 癌症登记处 环境卫生 社会学
作者
Christopher N. Graham,Crystal Watson,Arie Barlev,Matt Stevenson,Vikas R. Dharnidharka
出处
期刊:Journal of Medical Economics [Informa]
卷期号:25 (1): 230-237 被引量:39
标识
DOI:10.1080/13696998.2022.2033050
摘要

Accurately estimating mean survival after solid organ transplant (SOT) is crucial for efficient healthcare resource allocation decisions. However, registry-based post-transplant recipient survival estimates vary greatly and are incomplete. Often, the methods used in lifetime survival extrapolation may not fit complex transplant data and therefore alternative methods are required. We aimed to explore the flexible cubic spline methodology as a meaningful alternative for estimating lifetime survival following SOT.Survival analyses were conducted in kidney, liver, heart, and lung transplant recipients. Mean survival was estimated using flexible cubic splines on the hazard scale fitted with three knots, based on where hazards changed direction, clinical advice, and best-fit curve using Akaike and Bayesian information criterion. The tail was extrapolated when data were no longer available. Extrapolation tails were compared with general population mortality, using age-matched life table hazards, and the highest hazards were taken at all times.We found that mean survival post-transplant was longest for kidney transplants (US: 22.79 years; UK: 26.58 years), followed by liver (US: 20.90 years; UK: 20.38 years), heart (US: 14.82 years; UK: 15.85 years), and lung (US: 9.28 years; UK: 9.21 years). A sensitivity analysis using two knots found differences in survival ranging from -1.30 to +4.83 years across SOTs examined.This study does not represent individual patient survival, survival by age groups, multiple-organ transplants, or assess factors that may impact overall or organ survival.Our study estimates reflect real-world survival following SOTs and demonstrate the importance of including long-term hazards in survival estimations. These lifetime survival estimates can be used by decision-makers in situations where means are preferred over medians (e.g. population projections, budgetary estimates, and cost-effectiveness models) and can thus offer a meaningful alternative to the estimates used and accepted in current practice.
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