Reese Jennifer Barsky, Blackford Amanda, Sussman Jonathan, Okuyama Toru, Akechi Tatsuo, Bainbridge Daryl, Howell Doris, Snyder Claire F
Department of Psychiatry and Behavioral Sciences, Johns Hopkins School of Medicine, 5510 Nathan Shock Dr., Suite 100, Baltimore, MD, 21224, USA,
Qual Life Res. 2015 Jan;24(1):135-46. doi: 10.1007/s11136-014-0629-4. Epub 2014 Jan 31.
Patient-reported outcomes (PROs) are an umbrella term covering a range of outcomes, including symptoms, functioning, health-related quality of life, and supportive care needs. Research regarding the appropriate PRO questionnaires to use is informative. A previously published latent class analysis (LCA) examined patterns of function, symptoms, and supportive care needs in a sample of US cancer patients. The current analysis investigated whether the findings from the original study were replicated in new samples from different countries and whether a larger sample combining all the data would affect the classes identified.
This secondary analysis of data from 408 Japanese and 189 Canadian cancer patients replicated the methods used in the original LCA using data from 117 US cancer patients. In all samples, subjects completed the EORTC-QLQ-C30 and Supportive Care Needs Survey Short Form-34 (SCNS-SF34). We first dichotomized individual function, symptom, and need domain scores. We then performed LCA to investigate the patterns of domains for each of the outcomes, both in the individual country samples and then combining the data from all three samples.
Across all analyses, class assignment was made by level of function, symptoms, or needs. In individual samples, only two-class models ("high" vs. "low") were generally identifiable while in the combined sample, three-class models ("high" vs. "moderate" vs. "low") best fit the data for all outcomes.
In this analysis, the level of burden experienced by patients was the key factor in defining classes.
患者报告结局（PROs）是一个涵盖一系列结局的统称，包括症状、功能、健康相关生活质量和支持性护理需求。关于使用何种合适的PRO问卷的研究具有参考价值。先前发表的一项潜在类别分析（LCA）研究了美国癌症患者样本中的功能、症状和支持性护理需求模式。当前的分析调查了原研究的结果在来自不同国家的新样本中是否能得到重复，以及合并所有数据的更大样本是否会影响所确定的类别。
对408名日本癌症患者和189名加拿大癌症患者的数据进行的二次分析，采用了与原LCA相同的方法，使用了来自117名美国癌症患者的数据。在所有样本中，受试者均完成了欧洲癌症研究与治疗组织生活质量核心问卷（EORTC-QLQ-C30）和支持性护理需求调查问卷简表34（SCNS-SF34）。我们首先将个体功能、症状和需求领域得分进行二分法处理。然后进行LCA，以研究每个结局在各个国家样本以及合并所有三个样本数据后的领域模式。
在所有分析中，类别划分是根据功能、症状或需求水平进行的。在各个样本中，通常只能识别出两类模型（“高”与“低”），而在合并样本中，三类模型（“高”与“中”与“低”）最能拟合所有结局的数据。
在本分析中，患者所经历的负担水平是定义类别的关键因素。
