Joint modeling of dizziness, drowsiness, and dropout associated with pregabalin and placebo treatment of generalized anxiety disorder
| Autor: | Matthew M. Hutmacher, Raymond Miller, Bill Frame |
|---|---|
| Rok vydání: | 2009 |
| Předmět: |
medicine.medical_specialty
Generalized anxiety disorder Patient Dropouts Time Factors Dropout (communications) Ordinal Scale Pregabalin Kaplan-Meier Estimate Ordinal regression Dizziness Models Biological Severity of Illness Index Double-Blind Method medicine Humans Multicenter Studies as Topic Computer Simulation Adverse effect gamma-Aminobutyric Acid Randomized Controlled Trials as Topic Pharmacology Models Statistical Dose-Response Relationship Drug business.industry medicine.disease Random effects model Placebo Effect Anxiety Disorders Markov Chains NONMEM Treatment Outcome Anti-Anxiety Agents Anesthesia Creatinine Physical therapy Sleep Stages business medicine.drug |
| Zdroj: | Journal of pharmacokinetics and pharmacodynamics. 36(6) |
| ISSN: | 1573-8744 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|
Full text from SpringerLink