Ed Whalen

TL;DR: In this paper, the authors evaluated four models based on potential predictors for achieving a response to pregabalin treatment for neuropathic pain (NeP), including baseline characteristics (including mean pain and pain-related sleep interference [PRSI] scores), early clinical response during weeks 1-3 of treatment (change from baseline in pain and PRSI scores), and presence of treatment-emergent adverse events (AEs) were predictive of therapeutic response.

TL;DR: The magnitude of response to pregabalin in terms of changes in pain may depend on age, pain, and sleep levels at baseline in patients with fibromyalgia.

TL;DR: A hierarchical cluster analysis to identify patient clusters in the Observational Study to which RCT patients could be matched using the coarsened exact matching (CEM) technique, thereby creating a matched dataset, and autoregressive moving average models (ARMAXs) to estimate weekly pain scores for pregabalin-treated patients in each cluster in the matched dataset using the maximum likelihood method.

TL;DR: In patients who received pregabalin for neuropathic or non-neuropathic chronic pain, those who experienced Euphoria events may have better early treatment responses than those who did not report euphoria events.