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首页> 外文期刊>World Journal of Oncology >Symptom Clusters in Patients With Bone Metastases: A Sub-Analysis of Patients Reporting Exclusively Non-Zero BPI Scores
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Symptom Clusters in Patients With Bone Metastases: A Sub-Analysis of Patients Reporting Exclusively Non-Zero BPI Scores

机译：骨转移患者的症状群：仅报告非零BPI得分的患者的亚分析

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Background: The use of different statistical methods and inclusion criteria when deriving symptom clusters in cancer patients are contributing factors in cluster inconsistencies across studies. Primary objective was to extract symptom clusters in a subgroup of patients reporting non-zero Brief Pain Inventory (BPI) scores at baseline, and to compare clusters with those identified in the total patient sample. Methods: Principal Component Analysis (PCA), Hierarchical Cluster Analysis (HCA) and Exploratory Factor Analysis (EFA) were performed on the non-zero subgroup and total patient sample to identify symptom clusters at baseline and 1, 2 and 3 months following radiotherapy. Results: At baseline, different symptom clusters were derived from the non-zero subgroup and the total patient population. Only PCA identified identical clusters. Over time, clusters extracted using the three statistical methods varied, with a few exceptions where the same clusters were extracted using two different methods at a specific time point. A complete consensus between all three methods was not noted at any time. The BPI, which is a short assessment tool, may lead to the extraction of oversimplified clusters. In addition, since this study analyzed results in the non-zero subgroup, clusters derived may be reflective of patients with poorer prognosis as these patients experienced all symptoms. Conclusion: Analyzing data compiled from all eligible consenting patients may not provide clinically relevant clustering among all symptoms in the assessment tool. The composition of symptom clusters varied with the inclusion of patients with zero symptom severity scores and with the statistical method employed.doi:10.4021/wjon394w
机译：背景：在推导癌症患者的症状簇时使用不同的统计方法和纳入标准是导致整个研究中簇不一致的因素。主要目标是在基线时报告非零简短疼痛清单（BPI）分数的患者亚组中提取症状簇，并将其与总患者样本中识别出的症状簇进行比较。方法：对非零亚组和总患者样本进行主成分分析（PCA），层次聚类分析（HCA）和探索性因子分析（EFA），以识别基线，放疗后1、2和3个月的症状群。结果：在基线时，从非零亚组和患者总数中得出了不同的症状群。只有PCA标识相同的群集。随着时间的流逝，使用三种统计方法提取的聚类发生变化，只有少数例外，其中在特定时间点使用两种不同的方法提取相同的聚类。任何时候都没有注意到这三种方法之间的完全共识。 BPI是一种简短的评估工具，可能会导致提取过于简化的聚类。此外，由于本研究分析了非零亚组的结果，因此得出的聚类可能反映了预后较差的患者，因为这些患者经历了所有症状。结论：分析所有符合条件的同意患者收集的数据可能无法在评估工具的所有症状之间提供临床相关的聚类。症状群的组成随症状严重程度评分为零的患者的纳入和采用的统计学方法而异。doi：10.4021 / wjon394w

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