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@article{Vollert:2017:10.1097/j.pain.0000000000000935,
author = {Vollert, J and Maier, C and Attal, N and Bennett, DLH and Bouhassira, D and Enax-Krumova, EK and Finnerup, NB and Freynhagen, R and Gierthmuehlen, J and Haanpaa, M and Hansson, P and Hullemann, P and Jensen, TS and Magerl, W and Ramirez, JD and Rice, ASC and Schuh-Hofer, S and Segerdahl, M and Serra, J and Shillo, PR and Sindrup, S and Tesfaye, S and Themistocleous, AC and Toelle, TR and Treede, R-D and Baron, RJ},
doi = {10.1097/j.pain.0000000000000935},
journal = {PAIN},
pages = {1446--1455},
title = {Stratifying patients with peripheral neuropathic pain based on sensory profiles: algorithm and sample size recommendations},
url = {http://dx.doi.org/10.1097/j.pain.0000000000000935},
volume = {158},
year = {2017}
}

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TY  - JOUR
AB  - In a recent cluster analysis, it has been shown that patients with peripheral neuropathic pain can be grouped into 3 sensory phenotypes based on quantitative sensory testing profiles, which are mainly characterized by either sensory loss, intact sensory function and mild thermal hyperalgesia and/or allodynia, or loss of thermal detection and mild mechanical hyperalgesia and/or allodynia. Here, we present an algorithm for allocation of individual patients to these subgroups. The algorithm is nondeterministic—ie, a patient can be sorted to more than one phenotype—and can separate patients with neuropathic pain from healthy subjects (sensitivity: 78%, specificity: 94%). We evaluated the frequency of each phenotype in a population of patients with painful diabetic polyneuropathy (n = 151), painful peripheral nerve injury (n = 335), and postherpetic neuralgia (n = 97) and propose sample sizes of study populations that need to be screened to reach a subpopulation large enough to conduct a phenotype-stratified study. The most common phenotype in diabetic polyneuropathy was sensory loss (83%), followed by mechanical hyperalgesia (75%) and thermal hyperalgesia (34%, note that percentages are overlapping and not additive). In peripheral nerve injury, frequencies were 37%, 59%, and 50%, and in postherpetic neuralgia, frequencies were 31%, 63%, and 46%. For parallel study design, either the estimated effect size of the treatment needs to be high (>0.7) or only phenotypes that are frequent in the clinical entity under study can realistically be performed. For crossover design, populations under 200 patients screened are sufficient for all phenotypes and clinical entities with a minimum estimated treatment effect size of 0.5.
AU  - Vollert,J
AU  - Maier,C
AU  - Attal,N
AU  - Bennett,DLH
AU  - Bouhassira,D
AU  - Enax-Krumova,EK
AU  - Finnerup,NB
AU  - Freynhagen,R
AU  - Gierthmuehlen,J
AU  - Haanpaa,M
AU  - Hansson,P
AU  - Hullemann,P
AU  - Jensen,TS
AU  - Magerl,W
AU  - Ramirez,JD
AU  - Rice,ASC
AU  - Schuh-Hofer,S
AU  - Segerdahl,M
AU  - Serra,J
AU  - Shillo,PR
AU  - Sindrup,S
AU  - Tesfaye,S
AU  - Themistocleous,AC
AU  - Toelle,TR
AU  - Treede,R-D
AU  - Baron,RJ
DO  - 10.1097/j.pain.0000000000000935
EP  - 1455
PY  - 2017///
SN  - 0304-3959
SP  - 1446
TI  - Stratifying patients with peripheral neuropathic pain based on sensory profiles: algorithm and sample size recommendations
T2  - PAIN
UR  - http://dx.doi.org/10.1097/j.pain.0000000000000935
UR  - http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000406932300008&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
UR  - http://hdl.handle.net/10044/1/52006
VL  - 158
ER  -

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