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Published in: Advances in Therapy 10/2018

Open Access 01-10-2018 | Original Research

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

Authors: Roger A. Edwards, Gianluca Bonfanti, Roberto Grugni, Luigi Manca, Bruce Parsons, Joe Alexander

Published in: Advances in Therapy | Issue 10/2018

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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.
Appendix
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Metadata
Title
Predicting Responses to Pregabalin for Painful Diabetic Peripheral Neuropathy Based on Trajectory-Focused Patient Profiles Derived from the First 4 Weeks of Treatment
Authors
Roger A. Edwards
Gianluca Bonfanti
Roberto Grugni
Luigi Manca
Bruce Parsons
Joe Alexander
Publication date
01-10-2018
Publisher
Springer Healthcare
Published in
Advances in Therapy / Issue 10/2018
Print ISSN: 0741-238X
Electronic ISSN: 1865-8652
DOI
https://doi.org/10.1007/s12325-018-0780-3

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