Stratification of Patients Based on the Neuropathic Pain Symptom Inventory

Development and Validation of a New Algorithm

Didier Bouhassira; Samuel Branders; Nadine Attal; Ana Mercia Fernandes; Dominique Demolle; Julio Barbour; Daniel Ciampi de Andrade; Alvaro Pereira

Disclosures

Pain. 2021;162(4):1038-1046. 

In This Article

Abstract and Introduction

Abstract

The personalization of neuropathic pain treatment could be improved by identifying specific sensory phenotypes (ie, specific combinations of symptoms and signs) predictive of the response to different classes of drugs. A simple and reliable phenotyping method is required for such a strategy. We investigated the utility of an algorithm for stratifying patients into clusters corresponding to specific combinations of neuropathic symptoms assessed with the Neuropathic Pain Symptom Inventory (NPSI). Consistent with previous results, we first confirmed, in a cohort of 628 patients, the existence of a structure consisting of 3 clusters of patients characterized by higher NPSI scores for: pinpointed pain (cluster 1), evoked pain (cluster 2), or deep pain (cluster 3). From these analyses, we derived a specific algorithm for assigning each patient to one of these 3 clusters. We then assessed the clinical relevance of this algorithm for predicting treatment response, through post hoc analyses of 2 previous controlled trials of the effects of subcutaneous injections of botulinum toxin A. Each of the 97 patients with neuropathic pain included in these studies was individually allocated to one cluster, by applying the algorithm to their baseline NPSI responses. We found significant effects of botulinum toxin A relative to placebo in clusters 2 and 3, but not in cluster 1, suggesting that this approach was, indeed, relevant. Finally, we developed and performed a preliminary validation of a web-based version of the NPSI and algorithm for the stratification of patients in both research and daily practice.

Introduction

Neuropathic pain remains an unmet clinical need, with less than 50% of patients achieving partial pain relief with the drug treatments currently recommended.[3,19,27] This poor therapeutic outcome is probably related to multiple factors, including the possibility that the drugs currently used do not act on the most relevant pathophysiological targets. It may also reflect an inadequate definition of clinical indications because the current recommendations do not take into account the heterogeneity of neuropathic pain syndromes. Pain experts have, therefore, advocated a more personalized therapeutic approach to neuropathic pain, based on clinical profiles consisting of specific combinations of symptoms and signs that may reflect pathophysiological mechanisms.[1,2,4,6,7,11,12,15,18,34] However, there is no consensus regarding the optimal stratification method. Several approaches have been used, including standardized bedside examination,[21] quantitative sensory testing (QST),[7] and questionnaires.[8,13,21] Specific neuropathic questionnaires and QST, which, unlike standardized bedside examination, have been formally validated, are potentially the most useful approaches. In a recent study in a large cohort of patients with peripheral neuropathic pain, 3 clusters, characterized by sensory loss, thermal hyperalgesia, and mechanical hyperalgesia, respectively, were identified on the basis of their QST profiles.[7] The authors of this study then performed a complementary study in which they developed a specific algorithm for allocating patients to these clusters, which could be used for the stratification of patients in clinical trials.[33] These studies were based on the comprehensive QST battery developed by the DFNS (German Research Network on Neuropathic Pain), including 13 sensory parameters.[31] This QST protocol provides a detailed assessment of the patient's sensory profile, based on the quantification of sensory deficits and evoked pain (ie, allodynia and/or hyperalgesia). However, one of the main limitations of this approach is that it does not assess spontaneous pain, which is, by far, the most frequent complaint among patients. In addition, this DFNS QST battery is time consuming and requires expensive devices and special training. We therefore decided to develop a complementary approach based on simple neuropathic pain assessment questionnaires. The Neuropathic Pain Symptom Inventory (NPSI) is a self-administered questionnaire including 10 pain descriptors pertaining to 5 distinct clinically relevant neuropathic pain dimensions.[10] The NPSI has been shown to be sensitive to several treatments, with differential effects on the various neuropathic pain dimensions.[5,13,26] In addition, 3 subgroups of patients (clusters) have already been characterized on the basis of specific combinations of NPSI items in a large cohort of patients.[21]

The main objectives of this study were to confirm the existence of 3 clinically relevant clusters in a large cohort of patients from our internal data base with neuropathic pain of different etiologies and to develop an algorithm for assigning individual patients to one of these clusters on the basis of their individual responses to the NPSI. We then assessed the clinical relevance of this algorithm, in terms of treatment response, using the pooled results from 2 previous studies of the effects of botulinum toxin injections in patients with peripheral neuropathic pain.[5,29] Finally, we developed and tested an electronic version (e-version) of the NPSI classification algorithm, which would be easy to use for the assignment of each patient to a cluster, in both everyday clinical practice and in research settings.

Comments

3090D553-9492-4563-8681-AD288FA52ACE

processing....