Cluster analysis of clinical data identifies fibromyalgia subgroups.
Cluster analysis of clinical data identifies fibromyalgia subgroups.
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DOI：
10.1371/journal.pone.0074873
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发表时间：
2013
期刊：
影响因子：
3.7
通讯作者：
Estivill X
中科院分区：
文献类型：
--
作者：
Docampo E;Collado A;Escaramís G;Carbonell J;Rivera J;Vidal J;Alegre J;Rabionet R;Estivill X
纤维肌痛（FM）的主要特征是广泛的疼痛和多种伴随症状，这阻碍了FM的评估和管理。为了减少FM异质性，我们将临床数据分类为用于定义FM亚组的简化维度。在1,446例符合1990年ACR FM标准的西班牙FM病例中评价了48个变量。进行分区分析以找到彼此相似的变量组。确定变量之间的相似性，并将变量分组为维度。这是在559例患者的子集中进行的，并在其余887例患者中进行了交叉验证。对于每个样本和维度，根据维度中包含的变量权重获得综合指数。最后，聚类程序应用于指数，导致FM亚组。变量聚集成三个独立的维度：“病理学”、“合并症”和“临床量表”。FM子群的构造只考虑了前两个维度。结果评分将FM样本分为三个亚组：低代谢率和合并症（第1组）、高代谢率和合并症（第2组）以及高代谢率但低合并症（第3组），显示了疾病严重程度测量的差异。我们通过对临床数据进行聚类，在一个大型FM队列中确定了FM样本的三个亚组。我们的分析强调FM合并症的家族史和个人史的重要性。此外，由此产生的患者群可能表明疾病的不同形式，与未来的研究相关，并可能对临床评估产生影响。
Fibromyalgia (FM) is mainly characterized by widespread pain and multiple accompanying symptoms, which hinder FM assessment and management. In order to reduce FM heterogeneity we classified clinical data into simplified dimensions that were used to define FM subgroups. 48 variables were evaluated in 1,446 Spanish FM cases fulfilling 1990 ACR FM criteria. A partitioning analysis was performed to find groups of variables similar to each other. Similarities between variables were identified and the variables were grouped into dimensions. This was performed in a subset of 559 patients, and cross-validated in the remaining 887 patients. For each sample and dimension, a composite index was obtained based on the weights of the variables included in the dimension. Finally, a clustering procedure was applied to the indexes, resulting in FM subgroups. Variables clustered into three independent dimensions: “symptomatology”, “comorbidities” and “clinical scales”. Only the two first dimensions were considered for the construction of FM subgroups. Resulting scores classified FM samples into three subgroups: low symptomatology and comorbidities (Cluster 1), high symptomatology and comorbidities (Cluster 2), and high symptomatology but low comorbidities (Cluster 3), showing differences in measures of disease severity. We have identified three subgroups of FM samples in a large cohort of FM by clustering clinical data. Our analysis stresses the importance of family and personal history of FM comorbidities. Also, the resulting patient clusters could indicate different forms of the disease, relevant to future research, and might have an impact on clinical assessment.
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DOI：
10.1046/j.1523-5394.1999.75008.x
发表时间：
1999-09-01
期刊：
CANCER PRACTICE
影响因子：
--
作者：
Gaston-Johansson, F;Fall-Dickson, JM;Kennedy, MJ
通讯作者：
Kennedy, MJ
影响因子：
5.8
作者：
Benito-Leon, J.;Martinez-Martin, P.;Ruiz-Martinez, I.
通讯作者：
Ruiz-Martinez, I.
影响因子：
2.3
作者：
Silverman S;Sadosky A;Evans C;Yeh Y;Alvir JM;Zlateva G
通讯作者：
Zlateva G
影响因子：
11.3
作者：
BUYSSE, DJ;REYNOLDS, CF;KUPFER, DJ
通讯作者：
KUPFER, DJ
影响因子：
--
作者：
KRUPP, LB;LAROCCA, NG;STEINBERG, AD
通讯作者：
STEINBERG, AD