Division of Gastroenterology, Department of Medicine, University at Buffalo School of Medicine, SUNY, Buffalo, NY 14215, USA.
Value Health. 2013 Jan-Feb;16(1):97-103. doi: 10.1016/j.jval.2012.08.2207. Epub 2012 Nov 30.
Patient-reported outcomes assessing multiple gastrointestinal symptoms are central to characterizing the therapeutic benefit of novel agents for irritable bowel syndrome (IBS). Common approaches that sum or average responses across different illness components must be unidimensional and have small unique variances to avoid aggregation bias and misinterpretation of clinical data. This study sought to evaluate the unidimensionality of the IBS Symptom Severity Scale (IBS-SSS) and to explore person-centered cluster analytic methods for characterizing multivariate-based patient profiles.
Ninety-eight Rome-diagnosed patients with IBS completed the IBS-SSS and a single, global item of symptom severity (UCLA Symptom Severity Scale) at pretreatment baseline of a clinical trial funded by the National Institutes of Health. k-means cluster analyses were performed on participants' symptom severity scores.
The IBS-SSS was not unidimensional. Exploratory cluster analyses revealed four common symptom profiles across five items of the IBS-SSS. One cluster of patients (25%) had elevated scores on pain frequency and bowel dissatisfaction, with less elevated but still high scores on life interference and low pain severity ratings. A second cluster (19%) was characterized by intermediate scores on both pain dimensions but more elevated scores on bowel dissatisfaction. A third cluster (18%) had elevated scores across all IBS-SSS subcomponents. The fourth and the most common cluster (37%) had relatively low scores on all dimensions except bowel dissatisfaction and life interference due to IBS symptoms.
Patient-reported outcome end points and research on IBS more generally relying on multicomponent assessments of symptom severity should take into account the multidimensional structure of symptoms to avoid aggregation bias and to optimize the sensitivity of detecting treatment effects.
评估多种胃肠道症状的患者报告结局是描述新型肠易激综合征（IBS）治疗药物获益的核心。汇总或平均不同疾病成分的反应的常见方法必须是单维的，并且具有较小的独特方差，以避免聚合偏差和对临床数据的误解。本研究旨在评估 IBS 症状严重程度量表（IBS-SSS）的单维性，并探索基于人群的聚类分析方法，以描述基于多变量的患者特征。
98 例经罗马诊断的 IBS 患者在一项由美国国立卫生研究院资助的临床试验的治疗前基线时完成了 IBS-SSS 和单一的、总体症状严重程度项目（UCLA 症状严重程度量表）。对参与者的症状严重程度评分进行了 k-均值聚类分析。
IBS-SSS 不是单维的。探索性聚类分析显示，在 IBS-SSS 的五个项目中存在四种常见的症状特征。一组患者（25%）的疼痛频率和肠道不满评分较高，生活干扰和低疼痛严重程度评分虽不高但仍较高。第二组（19%）的两个疼痛维度得分均处于中等水平，但肠道不满得分较高。第三组（18%）在所有 IBS-SSS 子成分上的得分均较高。第四组（最常见的组，占 37%）除了肠道不满和生活干扰导致的 IBS 症状外，在所有维度上的得分相对较低。
基于患者报告结局的终点和更广泛的 IBS 研究，依赖于症状严重程度的多成分评估，应考虑症状的多维结构，以避免聚合偏差，并优化检测治疗效果的敏感性。
