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首页> 外文期刊>Journal of the royal statistical society >Bayesian non-parametric survival regression for optimizing precision dosing of intravenous busulfan in allogeneic stem cell transplantation
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Bayesian non-parametric survival regression for optimizing precision dosing of intravenous busulfan in allogeneic stem cell transplantation

机译：贝叶斯非参数生存回归用于优化异基因干细胞移植中静脉注射白消安的精确剂量

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摘要

Allogeneic stem cell transplantation is now part of standard care for acute leukaemia. To reduce toxicity of the pretransplant conditioning regimen, intravenous busulfan is usually used as a preparative regimen for acute leukaemia patients undergoing allogeneic stem cell transplantation. Systemic busulfan exposure, characterized by the area under the plasma concentration versus time curve, AUC, is strongly associated with clinical outcome. An AUC that is too high is associated with severe toxicities, whereas an AUC that is too low carries increased risks of recurrence of disease and failure to engraft. Consequently, an optimal AUC-interval needs to be determined for therapeutic use. To address the possibility that busulfan pharmacokinetics and pharmacodynamics vary significantly with patients' characteristics, we propose a tailored approach to determine optimal covariate-specific AUC-intervals. To estimate these personalized AUC-intervals, we apply a flexible Bayesian non-parametric regression model based on a dependent Dirichlet process and Gaussian process. Our analyses of a data set of 151 patients identified optimal therapeutic intervals for AUC that varied substantively with age and whether the patient was in complete remission or had active disease at transplant. Extensive simulations to evaluate the dependent Dirichlet process-Gaussian process model in similar settings showed that its performance compares favourably with alternative methods. We provide an R package, DDPGPSurv, that implements the dependent Dirichlet process-Gaussian process model for a broad range of survival regression analyses.
机译：异基因干细胞移植现已成为急性白血病标准治疗的一部分。为了降低移植前预处理方案的毒性，通常将静脉内白消安用作接受异体干细胞移植的急性白血病患者的制备方案。以血浆浓度对时间的曲线下面积AUC为特征的全身白硫丹暴露与临床结局密切相关。太高的AUC与严重的毒性相关，而太低的AUC则增加了疾病复发和无法植入的风险。因此，需要确定用于治疗用途的最佳AUC间隔。为了解决白消安药代动力学和药效学随患者特征而显着变化的可能性，我们提出了一种量身定制的方法来确定最佳的协变量特异性AUC间隔。为了估计这些个性化的AUC间隔，我们基于相关的Dirichlet过程和高斯过程应用了灵活的贝叶斯非参数回归模型。我们对151例患者的数据集的分析确定了AUC的最佳治疗间隔，该间隔随着年龄的增长以及患者是否完全缓解或移植时是否患有活动性疾病而显着不同。在相似的环境下，对依赖的Dirichlet过程-高斯过程模型进行了广泛的仿真，结果表明其性能优于其他方法。我们提供了R程序包DDPGPSurv，该程序包实现了相关的Dirichlet过程-高斯过程模型，以进行广泛的生存回归分析。

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