Eerola Verner, Sallinen Ville, Lyden Grace, Snyder Jon, Lempinen Marko, Helanterä Ilkka
Department of Transplantation and Liver Surgery, Helsinki University Hospital, University of Helsinki, Helsinki, Finland.
Department of Health Services and Organ Transplantation, Hennepin Healthcare Research Institute, Minneapolis, MN.
Transplant Direct. 2024 May 16;10(6):e1636. doi: 10.1097/TXD.0000000000001636. eCollection 2024 Jun.
A large proportion of potential organ donors are not utilized for kidney transplantation out of risk of early allograft loss because of donor-related characteristics. These can be summarized using kidney donor profile index (KDPI). Because KDPI affects the choice of the recipient, the predictive ability of KDPI is tied to recipient attributes. These have been questioned to explain most of the predictive ability of KDPI. This study aims to quantify the effect of the donor on early graft loss (EGL) by accounting for nonrandom allocation.
This study included patients undergoing kidney transplantation from deceased donors between 2014 and 2020 from the Scientific Registry of Transplantation Recipients. EGL, defined as a return to dialysis or retransplantation during the first posttransplant year, was the primary endpoint. Nonrandom allocation and donor-recipient matching by KDPI necessitated the use of inverse probability treatment weighting, which served to assess the effect of KDPI and mitigate selection bias in a weighted Cox regression model.
The study comprised 89 290 transplantations in 88 720 individual patients. Inverse probability treatment weighting resulted in a good balance of recipient covariates across values of continuous KDPI. Weighted analysis showed KDPI to be a significant predictor for short-term outcomes. A comparable (in terms of age, time on dialysis, previous transplants, gender, diabetes status, computed panel-reactive antibodies, and HLA mismatches) average recipient, receiving a kidney from a donor with KDPI 40-60 had a 3.5% risk of EGL increased to a risk of 7.5% if received a kidney from a KDPI >95 donor (hazard ratio, 2.3; 95% confidence interval, 1.9-2.7). However, for all-cause survival KDPI was less influential.
The predictive ability of KDPI does not stem from recipient confounding alone. In this large sample-sized study, modeling methods accounting for nonindependence of recipient selection verify graft quality to effectively predict short-term transplantation outcomes.
由于供体相关特征导致早期移植肾丢失风险，很大一部分潜在器官供体未被用于肾移植。这些特征可用肾脏供体特征指数（KDPI）进行总结。由于KDPI会影响受者的选择，KDPI的预测能力与受者属性相关。有人质疑这些属性能否解释KDPI的大部分预测能力。本研究旨在通过考虑非随机分配来量化供体对早期移植肾丢失（EGL）的影响。
本研究纳入了2014年至2020年期间在移植受者科学登记处接受已故供体肾移植的患者。EGL定义为移植后第一年内恢复透析或再次移植，是主要终点。KDPI导致的非随机分配和供体-受者匹配需要使用逆概率处理加权，这有助于在加权Cox回归模型中评估KDPI的影响并减轻选择偏倚。
该研究包括88720例个体患者的89290次移植。逆概率处理加权使连续KDPI值的受者协变量达到良好平衡。加权分析显示KDPI是短期结局的重要预测指标。一个可比的（在年龄、透析时间、既往移植、性别、糖尿病状态、计算的群体反应性抗体和HLA错配方面）平均受者，接受KDPI为40 - 60的供体的肾脏时，EGL风险为3.5%，如果接受KDPI>95的供体的肾脏，EGL风险则增加到7.5%（风险比，2.3；95%置信区间，1.9 - 2.7）。然而，对于全因生存，KDPI的影响较小。
KDPI的预测能力并非仅源于受者混杂因素。在这项大样本量研究中，考虑受者选择非独立性的建模方法验证了移植肾质量可有效预测短期移植结局。
