Exposure‐Response Analyses of the Effects of Pregabalin in Patients With Fibromyalgia Using Daily Pain Scores and Patient Global Impression of Change

Abstract

Data from 4 phase 2/3 studies were pooled to characterize the exposure response of daily pregabalin (150-600 mg) in patients with fibromyalgia using self-assessed daily pain scores (PAIN) and end-of-treatment patient global impression of change (PGIC). The exposure responses of both endpoints were characterized by an Emax model using nonlinear mixed-effects modeling (NONMEM). Drug effect on PAIN relative to placebo was significant with additional maximum effect of 1.51 points on the logit scale and EC50 of 1.54 ng/mL (dose of 174 mg) and a rapid onset (half-life of 11 hours), consistent with the half-life of the drug. The decrease in PAIN with placebo occurred more slowly, reaching maximum response (1.52 points on the logit scale) after 1 month. Drug response in fibromyalgia was dependent on age and sex, with greater PAIN reduction in older patients, in addition to the effect of creatinine clearance, and in females. For PGIC, administration of pregabalin resulted in an increase in the proportion of patients reporting improvement with an ED50 of 228 mg. The analyses support the recommended dose of pregabalin in patients with fibromyalgia of 300 to 450 mg/d.

Population pharmacokinetic modeling and simulation for assessing renal impairment effect on the pharmacokinetics of mirogabalin

“…Similar observations have been reported for a number of drugs that are predominantly eliminated in the urine . Similar to pregabalin, the effect of mirogabalin on chronic pain reduction is most likely to be driven by the overall systemic exposure (ie., AUC ss or average concentration over a dosing interval) rather than C max,ss . Hence, the predicted modestly lower C max,ss in subjects with moderate or severe renal impairment because of dose reduction is not expected to lead to reduced clinical efficacy of mirogabalin.…”

Population Pharmacokinetic/Pharmacodynamic Analysis of Nociceptive Pain Models Following an Oral Pregabalin Dose Administration to Healthy Subjects

“…A previously performed study by Byon et al 28 studied the effects of pregabalin on self-assessed daily pain scores and the end-of-treatment patient global impression of change in patients with fibromyalgia. In that study, pregabalin was able to significantly lower the pain scores compared to placebo.…”

“…The disadvantage of the use of these pain scores is the limited improvement (1.5 point decrease on a 10-point scale) and the long duration of studies (>100 days), which is needed in order to assess the successful analgesic effects. 28 Incorporating results from a battery of pain models in early clinical development may link the short-term analgesic effects with long-term drug response in patients. The developed population PK/PD models on the PTT of the cold pressor and the electrical stimulation test gives additional insight in the quantification of the analgesic concentration-effect of pregabalin that could not be obtained using solely a mixed model analysis of variance.…”

Likert Pain Score Modeling: A Markov Integer Model and an Autoregressive Continuous Model

“…As compared with previous analyses of Likert data, 20 , 21 a Poisson‐based model is a new approach, as it is traditionally used for unconstrained outcome variables. Theoretically, the truncation can be performed for any number of categories; practically, it may be limited by the size of the model file.…”

“…These models are a relatively evident choice considering the size of the scales, but they have limitations with respect to intermediate‐size scales such as 11‐point scales because of the continuity assumption and the need for supporting information for a large number of parameters, respectively. Only a few studies treated daily reported 11‐point‐scale data, with a fractional E max continuous model 20 or a 10‐parameter ordered categorical base model 21 . Other studies discuss data transformation accounting for the constraints inherent in this type of so‐called bounded outcome score in the frame of, for example, a coarsened latent variable approach, 22 , 23 , 24 exhibiting, among other advantages, high flexibility with regard to J‐ or U‐shaped distributions.…”