首页> 外文期刊>Pain research & management: the journal of the Canadian Pain Society = journal de la socie?te? canadienne pour le traitement de la douleur >An Assessment of Clinically Important Differences on the Worst Pain Severity Item of the Modified Brief Pain Inventory in Patients with Diabetic Peripheral Neuropathic Pain
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An Assessment of Clinically Important Differences on the Worst Pain Severity Item of the Modified Brief Pain Inventory in Patients with Diabetic Peripheral Neuropathic Pain

机译:糖尿病周围神经性疼痛患者经修订的简短疼痛调查表中最严重疼痛程度项目的临床重要差异的评估

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Objectives. Using patient global impression of change (PGIC) as an anchor, an approximately 30% reduction on an 11-point numeric pain intensity rating scale (PI-NRS) is considered a clinically important difference (CID) in pain. Our objective was to define the CID for another pain measure, the worst pain severity (WPS) item of the modified Brief Pain Inventory (m-BPI). Methods. In this post hoc analysis of a double-blind, placebo-controlled, phase 2 study, 452 randomized patients with diabetic peripheral neuropathic pain (DPNP) were followed over 5 weeks, with m-BPI data collected weekly and PGIC at treatment conclusion. Receiver operating characteristic (ROC) curves (via logistic regression) were used to determine the changes in the m-BPI-WPS score that best predicted ordinal clinical improvement thresholds (i.e., “minimally improved” or better) on the PGIC. Results. Similar to the PI-NRS, a change of ?3 (raw) or ?33.3% from the baseline on the m-BPI-WPS optimized prediction for the “much improved” or better PGIC threshold and represents a CID. There was a high correspondence between observed and predicted PGIC categories at each PGIC threshold (ROC AUCs were 0.78–0.82). Conclusions. Worst pain on the m-BPI may be used to assess clinically important improvements in DPNP studies. Findings require validation in larger studies.
机译:目标。使用患者的整体变化印象(PGIC)作为锚点,将11点数字疼痛强度等级量表(PI-NRS)降低大约30%被认为是疼痛的临床重要差异(CID)。我们的目标是为另一种疼痛测量方法定义CID,即修改后的简短疼痛清单(m-BPI)中的最严重疼痛程度(WPS)项目。方法。在这项对双盲,安慰剂对照的2期研究的事后分析中,对452名随机分组的糖尿病周围神经性疼痛(DPNP)患者进行了为期5周的随访,每周收集m-BPI数据,并在治疗结束时进行PGIC。接收者操作特征(ROC)曲线(通过逻辑回归)用于确定PGIC上最能预测序贯临床改善阈值(即“最小改善”或更好)的m-BPI-WPS分数的变化。结果。与PI-NRS相似,m-BPI-WPS优化预测的基线相对于基线的变化为π3(原始)或约为33.3%,代表“大大改善”或更好的PGIC阈值,代表了CID。在每个PGIC阈值处,观察到的和预测的PGIC类别之间都具有很高的对应性(ROC AUC为0.78–0.82)。结论。 m-BPI上最严重的疼痛可用于评估DPNP研究中临床上重要的改善。研究结果需要在较大的研究中进行验证。

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