Predicting Responses to Pregabalin for Painful Diabetic Peripheral Neuropathy Based on Trajectory-Focused Patient Profiles Derived from the First 4 Weeks of Treatment

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Abstract

Introduction: Prediction of final clinical outcomes based on early weeks of treatment can enable more effective patient care for chronic pain. Our goal was to predict, with at least 90% accuracy, 12- to 13-week outcomes for pregabalin-treated painful diabetic peripheral neuropathy (pDPN) patients based on 4 weeks of pain and pain-related sleep interference data. Methods: We utilized active treatment data from six placebo-controlled randomized controlled trials (n = 939) designed to evaluate efficacy of pregabalin for reducing pain in patients with pDPN. We implemented a three-step, trajectory-focused analytics approach based upon patient responses collected during the first 4 weeks using monotonicity, path length, frequency domain (FD), and k-nearest neighbor (kNN) methods. The first two steps were based on combinations of baseline pain, pain at 4 weeks, weekly monotonicity and path length during the first 4 weeks, and assignment of patients to one of four responder groups (based on presence/absence of 50% or 30% reduction from baseline pain at 4 and at 12/13 weeks). The third step included agreement between prediction of logistic regression of daily FD amplitudes and assignment made from kNN analyses. Results: Step 1 correctly assigned 520/939 patients from the six studies to a responder group using a 3-metric combination approach based on unique assignment to a 50% responder group. Step 2 (applied to the remaining 419 patients) predicted an additional 121 patients, using a blend of 50% and 30% responder thresholds. Step 3 (using a combination of FD and kNN analyses) predicted 204 of the remaining 298 patients using the 50% responder threshold. Our approach correctly predicted 90.0% of all patients. Conclusion: By correctly predicting 12- to 13-week responder outcomes with 90% accuracy based on responses from the first month of treatment, we demonstrated the value of trajectory measures in predicting pDPN patient response to pregabalin. Trial Registration: www.clinicaltrials.gov identifiers, NCT00156078/NCT00159679/NCT00143156/NCT00553475. Funding: Pfizer. Plain Language Summary: Plain language summary available for this article.

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APA

Edwards, R. A., Bonfanti, G., Grugni, R., Manca, L., Parsons, B., & Alexander, J. (2018). Predicting Responses to Pregabalin for Painful Diabetic Peripheral Neuropathy Based on Trajectory-Focused Patient Profiles Derived from the First 4 Weeks of Treatment. Advances in Therapy, 35(10), 1585–1597. https://doi.org/10.1007/s12325-018-0780-3

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