Inserm U987, APHP, UVSQ, Paris-Saclay University, CHU Ambroise Pare, Boulogne-Billancourt, France.
Tools4Patients, Jumet, Belgium.
Pain. 2021 Apr 1;162(4):1038-1046. doi: 10.1097/j.pain.0000000000002130.
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.
通过识别对不同类别的药物反应有预测作用的特定感觉表型（即特定症状和体征的组合），可以改善神经病理性疼痛治疗的个体化。这种策略需要一种简单可靠的表型方法。我们研究了一种算法在将患者分层为对应于使用神经性疼痛症状量表（NPSI）评估的特定神经性症状组合的聚类中的效用。与之前的结果一致，我们首先在 628 名患者的队列中证实了存在一种结构，该结构由具有更高 NPSI 评分的 3 组患者组成：点状疼痛（第 1 组）、诱发疼痛（第 2 组）或深部疼痛（第 3 组）。从这些分析中，我们得出了一种将每个患者分配到这 3 个聚类之一的特定算法。然后，我们通过对皮下注射肉毒杆菌毒素 A 的两项先前对照试验的事后分析来评估该算法对预测治疗反应的临床相关性。在这些研究中，每个患有神经性疼痛的 97 名患者均通过将算法应用于其基线 NPSI 反应单独分配到一个聚类中。我们发现肉毒杆菌毒素 A 相对于安慰剂在聚类 2 和 3 中具有显著的效果，但在聚类 1 中没有，这表明这种方法确实是相关的。最后，我们开发并初步验证了基于网络的 NPSI 和算法的版本，用于在研究和日常实践中对患者进行分层。
