In clinical trials of therapies for acute respiratory distress syndrome (ARDS), the average treatment effect in the study population may be attenuated because individual patient responses vary widely. This inflates sample size requirements and increases the cost and difficulty of conducting successful clinical trials. One solution is to enrich the study population with patients most likely to benefit, based on predicted patient response to treatment (predictive enrichment). In this perspective, we apply the precision medicine paradigm to the emerging use of extracorporeal CO₂ removal (ECCO₂R) for ultraprotective ventilation in ARDS. ECCO₂R enables reductions in tidal volume and driving pressure, key determinants of ventilator-induced lung injury. Using basic physiological concepts, we demonstrate that dead space and static compliance determine the effect of ECCO₂R on driving pressure and mechanical power. This framework might enable prediction of individual treatment responses to ECCO₂R. Enriching clinical trials by selectively enrolling patients with a significant predicted treatment response can increase treatment effect size and statistical power more efficiently than conventional enrichment strategies that restrict enrollment according to the baseline risk of death. To support this claim, we simulated the predicted effect of ECCO₂R on driving pressure and mortality in a preexisting cohort of patients with ARDS. Our computations suggest that restricting enrollment to patients in whom ECCO₂R allows driving pressure to be decreased by 5 cm H₂O or more can reduce sample size requirement by more than 50% without increasing the total number of patients to be screened. We discuss potential implications for trial design based on this framework.

中文翻译：

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在生理学中将精密医学应用于试验设计。急性呼吸窘迫综合征的体外CO ₂去除

在急性呼吸窘迫综合征（ARDS）疗法的临床试验中，由于个体患者的反应差异很大，因此在研究人群中的平均治疗效果可能会减弱。这增加了样本量的要求，并增加了进行成功的临床试验的成本和难度。一种解决方案是根据预测的患者对治疗的反应（预测性富集），用最可能受益的患者富集研究人群。从这个角度来看，我们将精确医学范例应用于体外CO ₂去除（ECCO ₂ R）在ARDS中进行超防护通气的新兴应用。ECCO ₂R可减少潮气量和驱动压力，这是呼吸机引起的肺损伤的关键决定因素。使用基本的生理概念，我们证明了死角和静态顺应性决定了ECCO ₂ R对驱动压力和机械功率的影响。该框架可能能够预测对ECCO ₂ R的个别治疗反应。通过选择性地招募具有显着预期治疗反应的患者来进行丰富的临床试验，可以比根据根据基线风险限制入组的常规富集策略更有效地增加治疗效果的大小和统计功效。死亡。为了支持这一说法，我们模拟了ECCO ₂的预期效果关于ARDS患者既往队列中的驾驶压力和死亡率的研究。我们的计算表明，仅对ECCO ₂ R使驱动压力降低5 cm H ₂ O或更多的患者入组，可以在不增加待筛选患者总数的情况下将样本量要求降低50％以上。我们讨论了基于此框架的试验设计的潜在含义。