Cramarossa Gemma, Nguyen Janet, Zhang Liying, Chen Emily, Khan Luluel, Tsao May, Danjoux Cyril, Barnes Elizabeth, Sahgal Arjun, Holden Lori, Jon Flo, Chow Edward
Rapid Response Radiotherapy Program, Odette Cancer Centre, Sunnybrook Health Sciences Centre, University of Toronto, Canada.
World J Oncol. 2012 Feb;3(1):8-15. doi: 10.4021/wjon394w. Epub 2012 Feb 19.
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.
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.
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.
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.
在推导癌症患者症状群时使用不同的统计方法和纳入标准，是各研究中症状群不一致的促成因素。主要目的是在基线时报告简短疼痛量表（BPI）得分非零的患者亚组中提取症状群，并将这些症状群与在全部患者样本中识别出的症状群进行比较。
对非零亚组和全部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），以识别放疗后基线、1个月、2个月和3个月时的症状群。
在基线时，非零亚组和全部患者群体得出了不同的症状群。只有主成分分析识别出了相同的症状群。随着时间推移，使用三种统计方法提取的症状群各不相同，只有少数例外情况，即在特定时间点使用两种不同方法提取出了相同的症状群。在任何时候都未发现三种方法之间完全一致。简短评估工具BPI可能导致提取出过于简化的症状群。此外，由于本研究分析了非零亚组的结果，得出的症状群可能反映了预后较差的患者情况，因为这些患者经历了所有症状。
分析所有符合条件且同意参与的患者汇总的数据，可能无法在评估工具中的所有症状之间提供具有临床相关性的聚类。症状群的构成因纳入症状严重程度评分为零的患者以及所采用的统计方法而异。
