Univ Lyon, Université Lyon 1 , UMR CNRS 5558, Laboratoire de Biométrie et Biologie Évolutive, F-69100 Villeurbanne, France.
School of Architecture, Civil and Environmental Engineering ENAC, École Polytechnique Fédérale de Lausanne EPFL , Lausanne, Switzerland.
Environ Sci Technol. 2018 Feb 6;52(3):1582-1590. doi: 10.1021/acs.est.7b05464. Epub 2018 Jan 23.
Toxicokinetic-toxicodynamic (TKTD) models, as the General Unified Threshold model of Survival (GUTS), provide a consistent process-based framework compared to classical dose-response models to analyze both time and concentration-dependent data sets. However, the extent to which GUTS models (Stochastic Death (SD) and Individual Tolerance (IT)) lead to a better fitting than classical dose-response model at a given target time (TT) has poorly been investigated. Our paper highlights that GUTS estimates are generally more conservative and have a reduced uncertainty through smaller credible intervals for the studied data sets than classical TT approaches. Also, GUTS models enable estimating any x% lethal concentration at any time (LC), and provide biological information on the internal processes occurring during the experiments. While both GUTS-SD and GUTS-IT models outcompete classical TT approaches, choosing one preferentially to the other is still challenging. Indeed, the estimates of survival rate over time and LC are very close between both models, but our study also points out that the joint posterior distributions of SD model parameters are sometimes bimodal, while two parameters of the IT model seems strongly correlated. Therefore, the selection between these two models has to be supported by the experimental design and the biological objectives, and this paper provides some insights to drive this choice.
毒代动力学-毒效动力学 (TKTD) 模型,如生存的通用统一阈值模型 (GUTS),与经典剂量反应模型相比,为分析时间和浓度依赖性数据集提供了一个一致的基于过程的框架。然而,GUTS 模型(随机死亡 (SD) 和个体耐受 (IT))在给定目标时间 (TT) 下比经典剂量反应模型更好拟合的程度研究得还不够充分。我们的论文强调,与经典 TT 方法相比,GUTS 估计通常更保守,并且通过较小的置信区间减少了研究数据集的不确定性。此外,GUTS 模型能够估计任何时间 (LC) 的任何 x%致死浓度,并提供实验过程中发生的内部过程的生物学信息。虽然 GUTS-SD 和 GUTS-IT 模型都优于经典 TT 方法,但优先选择哪一种模型仍然具有挑战性。事实上,两种模型之间的生存率和 LC 随时间的估计非常接近,但我们的研究还指出,SD 模型参数的联合后验分布有时呈双峰分布,而 IT 模型的两个参数似乎强烈相关。因此,必须根据实验设计和生物学目标来支持这两种模型之间的选择,本文提供了一些见解来推动这种选择。