Center for Populations Health Research, Department of Quantitative Health Sciences and.
Lerner College of Medicine, Case Western Reserve University, Cleveland, Ohio; and.
Am J Respir Crit Care Med. 2023 Nov 1;208(9):983-989. doi: 10.1164/rccm.202306-0968OC.
U.S. lung transplant mortality risk models do not account for patients' disease progression as time accrues between mandated clinical parameter updates. To investigate the effects of accrued waitlist (WL) time on mortality in lung transplant candidates and recipients beyond those expressed by worsening clinical status and to present a new framework for conceptualizing mortality risk in end-stage lung disease. Using Scientific Registry of Transplant Recipients data (2015-2020, = 12,616), we modeled transitions among multiple clinical states over time: WL, posttransplant, and death. Using cause-specific and ordinary Cox regression to estimate trajectories of composite 1-year mortality risk as a function of time from waitlisting to transplantation, we quantified the predictive accuracy of these estimates. We compared multistate model-derived candidate rankings against composite allocation score (CAS) rankings. There were 11.5% of candidates whose predicted 1-year mortality risk increased by >10% by day 30 on the WL. The multistate model ascribed lower numerical rankings (i.e., higher priority) than CAS for those who died while on the WL (multistate mean; median [interquartile range] ranking at death, 227; 154 [57-334]; CAS median [interquartile range] ranking at death, 329; 162 [11-668]). Patients with interstitial lung disease were more likely to have increasing risk trajectories as a function of time accrued on the WL compared with other lung diagnoses. Incorporating the effects of time accrued on the WL for lung transplant candidates and recipients in donor lung allocation systems may improve the survival of patients with end-stage lung diseases on the individual and population levels.
美国肺移植死亡率风险模型并未考虑到患者在强制性临床参数更新之间的等待名单时间的累积对疾病进展的影响。本研究旨在调查肺移植候选者和受者在等待名单上的时间累积对死亡率的影响,超出了临床状态恶化所表达的影响,并提出了一个新的框架来概念化终末期肺病患者的死亡风险。利用移植受者科学注册处(2015-2020 年,n=12616)的数据,我们对多个临床状态在时间上的转变进行建模:等待名单、移植后和死亡。使用特异性和普通 Cox 回归来估计从等待名单到移植的时间作为复合 1 年死亡率风险的函数的轨迹,我们量化了这些估计的预测准确性。我们比较了多状态模型衍生的候选者排名与复合分配评分(CAS)排名。有 11.5%的候选者在等待名单上的第 30 天,其预测的 1 年死亡率风险增加了>10%。多状态模型对那些在等待名单上死亡的人赋予了比 CAS 更低的数值排名(即更高的优先级)(多状态平均值;中位数[四分位距]在死亡时的排名,227;154[57-334];CAS 中位数[四分位距]在死亡时的排名,329;162[11-668])。与其他肺部诊断相比,间质性肺疾病患者的风险轨迹随着在等待名单上的时间累积而增加的可能性更大。在供肺分配系统中纳入肺移植候选者和受者在等待名单上的时间累积的影响,可能会提高个体和人群层面终末期肺病患者的生存率。