Background

The Lung Allocation Score (LAS) is used in the U.S. to prioritize lung transplant candidates. Selection bias, induced by dependent censoring of waitlisted candidates and prediction of posttransplant survival among surviving, transplanted patients only, is only partially addressed by the LAS. Recently, a modified LAS (mLAS) was designed to mitigate such bias. Here, we estimate the clinical impact of replacing the LAS with the mLAS.

Methods

We considered lung transplant candidates waitlisted during 2016 and 2017. LAS and mLAS scores were computed for each registrant at each observed organ offer date; individuals were ranked accordingly. Patient characteristics associated with better priority under the mLAS were investigated via logistic regression and generalized linear mixed models. We also determined whether differences in rank were explained more by changes in predicted pre- or posttransplant survival. Simulations examined how 1-year waitlist, posttransplant, and overall survival might change under the mLAS.

Results

Diagnosis group, 6-minute walk distance, continuous mechanical ventilation, functional status, and age demonstrated the highest impact on differential allocation. Differences in rank were explained more by changes in predicted pretransplant survival than changes in predicted posttransplant survival, suggesting that selection bias has more impact on estimates of waitlist urgency. Simulations suggest that for every 1000 waitlisted individuals, 12.8 (interquartile range: 5.2-24.3) fewer waitlist deaths per year would occur under the mLAS, without compromising posttransplant and overall survival.

Conclusions

Implementing a mLAS that mitigates selection bias into clinical practice can lead to important differences in allocation and possibly modest improvement in waitlist survival.

中文翻译：

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减轻选择偏倚的改良肺分配评分的临床影响

背景

美国使用肺分配评分 (LAS) 来优先考虑肺移植候选者。LAS 仅部分解决了由对候补候选人的依赖性审查和仅在存活的移植患者中预测移植后存活率引起的选择偏差。最近，修改后的 LAS (mLAS) 旨在减轻这种偏差。在这里，我们估计用 mLAS 替换 LAS 的临床影响。

方法

我们考虑了 2016 年和 2017 年期间列入候补名单的肺移植候选人。相应地对个人进行排名。通过逻辑回归和广义线性混合模型研究与 mLAS 下更好优先级相关的患者特征。我们还确定了排名差异是否更多地通过预测的移植前或移植后存活率的变化来解释。模拟检查了 1 年候补名单、移植后和总体生存率在 mLAS 下可能发生的变化。

结果

诊断组、6 分钟步行距离、连续机械通气、功能状态和年龄对差异分配的影响最大。排名差异更多地是由预测的移植前存活率的变化而不是预测的移植后存活率的变化来解释的，这表明选择偏差对候补名单紧迫性的估计有更大的影响。模拟表明，对于每 1000 名等待名单上的人，在 mLAS 下，每年等待名单上的死亡人数将减少 12.8（四分位间距：5.2-24.3），而不会影响移植后和总体生存。

结论

在临床实践中实施可减少选择偏倚的 mLAS 可能会导致分配方面的重大差异，并可能适度改善候补名单的存活率。