Wolverine Pharmacometrics Corporation, 5216 Pratt Rd., Ann Arbor, MI 48103, USA.
J Pharmacokinet Pharmacodyn. 2009 Dec;36(6):565-84. doi: 10.1007/s10928-009-9137-5. Epub 2009 Nov 8.
Dizziness and drowsiness are cited as being predictors of dropout from clinical trials for the medicine pregabalin. These adverse events are typically recorded daily on a four point ordinal scale (0 = none, 1 = mild, 2 = moderate, 3 = severe), with most subjects never reporting either adverse event. We modeled the dizziness, drowsiness, and dropout associated with pregabalin use in generalized anxiety disorder using piecewise Weibull distributions for the time to first non-zero dizziness or drowsiness score, after which the dizziness or drowsiness was modeled with ordinal regression with a Markovian element. Dropout was modeled with a Weibull distribution. Platykurtosis was encountered in the estimated random effects distributions for the ordinal regression models and was addressed with dynamic John-Draper transformations. The only identified predictor for the time to first non-zero dizziness or drowsiness score was daily titrated dose. Predictors for dropout included creatinine clearance and maximum daily adverse event score. Tolerance to adverse events over time was modeled by including a non-stationary component for the dizziness ordinal Markov regression while the piecewise Weibull distributions allowed a change point in the median time to first non-zero dizziness or drowsiness score.
头晕和嗜睡被认为是预测普瑞巴林药物临床试验脱落的指标。这些不良反应通常每天在四点有序量表上记录(0=无,1=轻度,2=中度,3=重度),大多数受试者从未报告过这两种不良反应。我们使用分段 Weibull 分布来建模广泛性焦虑障碍中与普瑞巴林使用相关的头晕、嗜睡和脱落,在首次非零头晕或嗜睡评分后,使用带有马尔可夫元素的有序回归来建模头晕或嗜睡,使用 Weibull 分布来建模脱落。在有序回归模型的估计随机效应分布中遇到了扁平峰度,并通过动态 John-Draper 变换解决了这个问题。首次非零头晕或嗜睡评分的时间的唯一确定预测因子是每日滴定剂量。脱落的预测因子包括肌酐清除率和最大每日不良反应评分。通过包括头晕有序马尔可夫回归中的非平稳分量来模拟随时间对不良反应的耐受性,而分段 Weibull 分布允许首次非零头晕或嗜睡评分的中位数时间的变化点。