BACKGROUND & AIMS:
: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.
背景与目标:
: 在最近的聚类分析中,已经表明,根据定量感觉测试图谱,周围神经性疼痛患者可以分为3种感觉表型,其主要特征是感觉丧失,完整的感觉功能和轻度的热痛觉过敏和/或异常性疼痛,或失去热检测和轻度机械痛觉过敏和/或异常性疼痛。在这里,我们提出了一种将单个患者分配到这些亚组的算法。该算法是不确定的-即,可以将患者分类为多个表型-并且可以将患有神经性疼痛的患者与健康受试者分开 (敏感性: 78%,特异性: 94%)。我们评估了患有糖尿病性多发性神经病 (n = 151),周围神经损伤 (n = 335),和带状疱疹后神经痛 (n = 97),并提出需要筛选的研究人群的样本量,以达到足以进行表型分层研究的亚群。糖尿病多发性神经病中最常见的表型是感觉丧失 (83%),其次是机械痛觉过敏 (75%) 和热痛觉过敏 (34%,注意百分比是重叠的而不是累加的)。在周围神经损伤中,频率为37%,59% 和50%,在带状疱疹后神经痛中,频率为31%,63% 和46%。对于平行研究设计,治疗的估计效果大小需要高 (>0.7),或者仅可以实际执行在所研究的临床实体中频繁出现的表型。对于交叉设计,筛选的200患者人群足以满足所有表型和临床实体,最小估计治疗效果大小为0.5。