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- W2891847667 abstract "To evaluate four models based on potential predictors for achieving a response to pregabalin treatment for neuropathic pain (NeP).In total, 46 pain studies were screened, of which 27 NeP studies met the criteria for inclusion in this analysis. Data were pooled from these 27 placebo-controlled randomized trials to assess if 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. Therapeutic response was defined as a ≥30% reduction from baseline in either pain and/or PRSI scores at week 5 with supplemental analyses to predict pain outcomes at weeks 8 and 12. Predictors of Patient Global Impression of Change (PGIC) were also evaluated. Four models were assessed: Random Forest, Logistic Regression, Naïve Bayes, and Partial Least Squares.The number of pregabalin-treated subjects in the training/test datasets, respectively, were 2818/1407 (30% pain analysis), 2812/1405 (30% sleep analysis), and 2693/1345 (PGIC analysis). All four models demonstrated consistent results, and the most important predictors of treatment outcomes at week 5 and pain outcomes at weeks 8 and 12 were the reduction in pain score and sleep score in the first 1-3 weeks. The presence or absence of the most common AEs in the first 1-3 weeks was not correlated with any treatment outcome.Subjects with an early response to pregabalin are more likely to experience an end-of-treatment response." @default.
- W2891847667 created "2018-09-27" @default.
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- W2891847667 date "2018-10-18" @default.
- W2891847667 modified "2023-10-01" @default.
- W2891847667 title "Prediction of therapeutic response to pregabalin in subjects with neuropathic pain" @default.
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- W2891847667 doi "https://doi.org/10.1080/03007995.2018.1520694" @default.
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