Marcus James, Lasch Kathryn, Wan Yin, Yang Mei, Hsu Ching, Merante Domenico
Pharmerit International, Bethesda, MD, USA.
Pharmerit International, Boston, MA, USA.
Pain Res Manag. 2018 Jul 22;2018:2140420. doi: 10.1155/2018/2140420. eCollection 2018.
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).
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.
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).
Worst pain on the m-BPI may be used to assess clinically important improvements in DPNP studies. Findings require validation in larger studies.
以患者总体印象变化(PGIC)为锚定指标,在11点数字疼痛强度评分量表(PI-NRS)上约30%的降低被视为疼痛方面具有临床意义的差异(CID)。我们的目的是确定另一种疼痛测量指标——改良简明疼痛问卷(m-BPI)中最严重疼痛程度(WPS)项目的CID。
在这项对一项双盲、安慰剂对照的2期研究的事后分析中,452名随机分组的糖尿病性周围神经病理性疼痛(DPNP)患者被随访5周,每周收集m-BPI数据,并在治疗结束时收集PGIC数据。采用受试者工作特征(ROC)曲线(通过逻辑回归)来确定m-BPI-WPS评分的变化,该变化能最佳预测PGIC上的有序临床改善阈值(即“稍有改善”或更好)。
与PI-NRS类似,m-BPI-WPS相对于基线的变化为-3(原始分)或-33.3%时,能优化对“明显改善”或更好的PGIC阈值的预测,代表一个CID。在每个PGIC阈值下,观察到的和预测的PGIC类别之间具有高度一致性(ROC曲线下面积为0.78 - 0.82)。
m-BPI中的最严重疼痛可用于评估DPNP研究中具有临床意义的改善情况。研究结果需要在更大规模的研究中进行验证。