Department of Psychiatry, Dalhousie University, Halifax, Nova Scotia, Canada.
Faculty of Computer Science, Dalhousie University, Halifax, Nova Scotia, Canada.
PLoS One. 2024 Feb 2;19(2):e0297708. doi: 10.1371/journal.pone.0297708. eCollection 2024.
Our objective is to propose a method capable of disentangling the magnitude, the speed, and the duration or decay rate of the time course of response to rapid antidepressant therapies. To this end, we introduce a computational model of the time course of response to a single treatment with a rapid antidepressant. Numerical simulation is used to evaluate whether model parameters can be accurately estimated from observed data. Finally, we compare our computational modelling-based approach with linear mixed effects modelling in terms of their ability to detect changes in the magnitude and time-course of response to rapid antidepressant therapies in simulated randomized trials. Simulation experiments show that the parameters of our computational model can be accurately recovered using nonlinear least squares. Parameter estimation accuracy is stable over noise levels reaching as high as 25% of the true antidepressant effect magnitude. Comparison of our approach to mixed effects modelling using simulated randomized controlled trial data demonstrates an inability of linear mixed models to disentangle effect magnitude and time course, while our computational model accurately separates these response components. Our modelling approach may accurately identify the (A) magnitude, (B) speed, and (C) durability or decay rate of response to rapid antidepressant therapies. Future studies should fit this model to data from real clinical trials, and use resulting parameter estimates to uncover predictors and causes of different elements of the temporal course of antidepressant response.
我们的目标是提出一种能够区分快速抗抑郁治疗反应时程的幅度、速度和持续时间或衰减率的方法。为此，我们引入了一个快速抗抑郁治疗反应时程的计算模型。数值模拟用于评估模型参数是否可以从观测数据中准确估计。最后，我们比较了我们基于计算建模的方法与线性混合效应建模在模拟随机试验中检测快速抗抑郁治疗反应幅度和时程变化的能力。模拟实验表明，我们的计算模型的参数可以使用非线性最小二乘法准确恢复。参数估计的准确性在噪声水平达到真实抗抑郁效应幅度的 25%时仍然稳定。使用模拟随机对照试验数据比较我们的方法与混合效应建模表明，线性混合模型无法区分效应幅度和时程，而我们的计算模型可以准确分离这些反应成分。我们的建模方法可以准确识别快速抗抑郁治疗反应的（A）幅度、（B）速度和（C）耐久性或衰减率。未来的研究应该将该模型拟合到真实临床试验数据中，并使用所得的参数估计值来揭示抗抑郁反应时间过程中不同元素的预测因子和原因。
