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基于患者报告结局和客观结局的癌症相关疲劳分层系统:癌症相关疲劳门诊指数。

Cancer-related fatigue stratification system based on patient-reported outcomes and objective outcomes: A cancer-related fatigue ambulatory index.

机构信息

Department of Physiotherapy, Faculty of Health Sciences, Universidad de Malaga, Málaga, Spain.

Institute of Biomedical Research in Málaga, Málaga, Spain.

出版信息

PLoS One. 2019 Apr 22;14(4):e0215662. doi: 10.1371/journal.pone.0215662. eCollection 2019.

Abstract

Although breast cancer mortality is decreasing, morbidity following treatment remains a significant issue, as patients face symptoms such as cancer-related fatigue (CRF). The aim of the present study is to develop a classification system that monitors fatigue via integration of an objective clinical assessment with patient self-report. Forty-three women participated in this research. Participants were post-treatment breast cancer survivors who had been surgically treated for their primary tumour with no evidence of neoplastic disease at the time of recruitment. Self-perceived fatigue was assessed with the Spanish version of the Piper Fatigue Scale-Revised (R-PFS). Objective fatigue was assessed by the 30 second Sit-to-Stand (30-STS) test. Confirmatory factor analysis was done with Maximum Likelihood Extraction (MLE). Internal consistency was obtained by Cronbach's α coefficients. Bivariate correlation showed that 30-STS performance was negatively-inversely associated with R-PFS. The MANOVA model explained 54.3% of 30-STS performance variance. Using normalized scores from the MLE, a classification system was developed based on the quartiles. This study integrated objective and subjective measures of fatigue to better allow classification of patient CRF experience. Results allowed development of a classification index to classify CRF severity in breast cancer survivors using the relationship between 30-STS and R-PFS scores. Future research must consider the patient-perceived and clinically measurable components of CRF to better understand this multidimensional issue.

摘要

尽管乳腺癌死亡率正在下降,但治疗后的发病率仍然是一个重大问题,因为患者面临着诸如与癌症相关的疲劳(CRF)等症状。本研究的目的是开发一种分类系统,通过将客观的临床评估与患者自我报告相结合来监测疲劳。共有 43 名女性参与了这项研究。参与者为接受过手术治疗的乳腺癌治疗后幸存者,在招募时没有肿瘤疾病的证据。自我感知的疲劳用西班牙语版 Piper 疲劳量表修订版(R-PFS)进行评估。客观疲劳通过 30 秒坐立测试(30-STS)进行评估。使用最大似然提取(MLE)进行验证性因素分析。内部一致性通过 Cronbach's α 系数获得。双变量相关显示,30-STS 表现与 R-PFS 呈负相关。MANOVA 模型解释了 30-STS 表现方差的 54.3%。使用 MLE 的归一化分数,根据四分位数开发了一种分类系统。本研究综合了疲劳的客观和主观测量,以更好地对患者 CRF 体验进行分类。结果允许使用 30-STS 和 R-PFS 分数之间的关系开发一种分类指数,以对乳腺癌幸存者的 CRF 严重程度进行分类。未来的研究必须考虑到患者感知和临床可测量的 CRF 成分,以更好地理解这个多维问题。

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