Vodafone Foundation Chair for Children's Pain Therapy and Paediatric Palliative Care, Witten/Herdecke University, Germany German Paediatric Pain Centre, Children's Hospital Datteln, Germany.
Pain. 2013 Jan;154(1):154-159. doi: 10.1016/j.pain.2012.10.008. Epub 2012 Oct 22.
Defining cut points for mild, moderate, and severe pain intensity on the basis of differences in functional interference has an intuitive appeal. The statistical procedure to derive them proposed in 1995 by Serlin et al. has been widely used. Contrasting cut points between populations have been interpreted as meaningful differences between different chronic pain populations. We explore the variability associated with optimally defined cut points in a large sample of chronic pain patients and in homogeneous subsamples. Ratings of maximal pain intensity (0-10 numeric rating scale, NRS) and pain-related disability were collected in a sample of 2249 children with chronic pain managed in a tertiary pain clinic. First, the "optimal" cut points for the whole sample were determined. Second, the variability of these cut points was quantified by the bootstrap technique. Third, this variability was also assessed in homogeneous subsamples of 650 children with constant pain, 430 children with chronic daily headache, and 295 children with musculoskeletal pain. Our study revealed 3 main findings: (1) The optimal cut points for mild, moderate, and severe pain in the whole sample were 4 and 8 (0-10 NRS). (2) The variability of these cut points within the whole sample was very high, identifying the optimal cut points in only 40% of the time. (3) Similarly large variability was also found in subsamples of patients with a homogeneous pain etiology. Optimal cut points are strongly influenced by random fluctuations within a sample. Differences in optimal cut points between study groups may be explained by chance variation; no other substantial explanation is required. Future studies that aim to interpret differences between groups need to include measures of variability for optimal cut points.
基于功能障碍差异来定义轻度、中度和重度疼痛强度的切点具有直观的吸引力。1995 年由 Serlin 等人提出的用于得出这些切点的统计程序已被广泛应用。人群之间的对比切点被解释为不同慢性疼痛人群之间的有意义差异。我们在大量慢性疼痛患者和同质亚组中探索了与最佳定义切点相关的可变性。在一家三级疼痛诊所接受管理的 2249 名慢性疼痛儿童的样本中,收集了最大疼痛强度(0-10 数字评定量表,NRS)和与疼痛相关的残疾的评分。首先,确定了整个样本的“最佳”切点。其次,使用自举技术量化这些切点的变异性。第三,还在同质亚组中评估了这种变异性,同质亚组包括 650 名持续疼痛的儿童、430 名慢性每日头痛的儿童和 295 名肌肉骨骼疼痛的儿童。我们的研究揭示了 3 个主要发现:(1)整个样本中轻度、中度和重度疼痛的最佳切点为 4 和 8(0-10 NRS)。(2)这些切点在整个样本中的变异性非常高,仅在 40%的时间确定了最佳切点。(3)在具有同质疼痛病因的患者亚组中也发现了类似的大变异性。最佳切点受到样本内随机波动的强烈影响。研究组之间最佳切点的差异可能是由于偶然变化引起的;不需要其他实质性解释。旨在解释组间差异的未来研究需要包括最佳切点的可变性测量。