Hepatobiliopancreatic Surgery and Transplantation Department, Hôpital de Hautepierre, Hôpitaux Universitaires de Strasbourg.
Laboratoire ICube, UMR7357, University of Strasbourg.
Curr Opin Organ Transplant. 2020 Jun;25(3):305-309. doi: 10.1097/MOT.0000000000000752.
This review describes and questions the evolution of allocation systems from local team decisions in the 20th century to patient-oriented allocation using complex algorithm predicting transplant benefit.
The opening years of the 2000s have seen the implementation of prioritization scores aiming at increasing transparency and reducing waitlist mortality. The 2010s have underlined the necessity of drawing the upper limits of how sick a patient can be while still ensuring acceptable survival. More complex algorithms evaluating transplant benefit have been implemented in allocation systems to take this issue into account.
Allocation algorithms are becoming more and more complex, integrating numerous parameters from both donor and recipient to achieve optimal matching. The limitations of implementing these complex algorithms are represented by the evermoving waiting list demography, geographic disparities between recipients and donors, team policy adaptation to rule changes, and implicit biases within the transplant community. Survival as the only metric by which to define benefit may be seen as restrictive; quality of life may be a fruitful measure for better defining benefit in organ transplantation in the future.
本文描述并质疑了分配系统的演变过程，从 20 世纪的地方团队决策，到使用预测移植获益的复杂算法进行面向患者的分配。
进入 21 世纪的最初几年，实施了优先级评分，旨在提高透明度和降低候补名单死亡率。2010 年代强调了确定患者病情严重程度上限的必要性，同时仍要确保可接受的生存率。为了解决这个问题，分配系统中已经实施了更复杂的算法来评估移植获益。
分配算法变得越来越复杂，整合了供体和受体的众多参数，以实现最佳匹配。实施这些复杂算法的局限性在于候补名单人群的不断变化、受体和供体之间的地理差异、团队政策对规则变化的适应以及移植界的内在偏见。将生存作为定义获益的唯一指标可能会受到限制；生活质量可能是一个有益的衡量标准，有助于在未来更好地定义器官移植中的获益。
