Astrup Guro Lindviksmoen, Hofsø Kristin, Bjordal Kristin, Guren Marianne Grønlie, Vistad Ingvild, Cooper Bruce, Miaskowski Christine, Rustøen Tone
a Department of Oncology, Division of Cancer Medicine , Oslo University Hospital , Oslo , Norway.
b Institute of Clinical Medicine, Faculty of Medicine, University of Oslo , Oslo , Norway.
Acta Oncol. 2017 Mar;56(3):462-470. doi: 10.1080/0284186X.2016.1273546. Epub 2017 Jan 12.
Reviews of the literature on symptoms in oncology patients undergoing curative treatment, as well as patients receiving palliative care, suggest that they experience multiple, co-occurring symptoms and side effects.
The purposes of this study were to determine if subgroups of oncology patients could be identified based on symptom occurrence rates and if these subgroups differed on a number of demographic and clinical characteristics, as well as on quality of life (QoL) outcomes.
Latent class analysis (LCA) was used to identify subgroups (i.e. latent classes) of patients with distinct symptom experiences based on the occurrence rates for the 13 most common symptoms from the Memorial Symptom Assessment Scale.
In total, 534 patients with breast, head and neck, colorectal, or ovarian cancer participated. Four latent classes of patients were identified based on probability of symptom occurrence: all low class [i.e. low probability for all symptoms (n = 152)], all high class (n = 149), high psychological class (n = 121), and low psychological class (n = 112). Patients in the all high class were significantly younger compared with patients in the all low class. Furthermore, compared to the other three classes, patients in the all high class had lower functional status and higher comorbidity scores, and reported poorer QoL scores. Patients in the high and low psychological classes had a moderate probability of reporting physical symptoms. Patients in the low psychological class reported a higher number of symptoms, a lower functional status, and poorer physical and total QoL scores.
Distinct subgroups of oncology patients can be identified based on symptom occurrence rates. Patient characteristics that are associated with these subgroups can be used to identify patients who are at greater risk for multiple co-occurring symptoms and diminished QoL, so that these patients can be offered appropriate symptom management interventions.
对接受根治性治疗的肿瘤患者以及接受姑息治疗的患者的文献综述表明，他们会经历多种同时出现的症状和副作用。
本研究的目的是确定是否可以根据症状发生率识别肿瘤患者亚组，以及这些亚组在一些人口统计学和临床特征以及生活质量（QoL）结果方面是否存在差异。
基于纪念症状评估量表中13种最常见症状的发生率，使用潜在类别分析（LCA）来识别具有不同症状体验的患者亚组（即潜在类别）。
共有534例乳腺癌、头颈癌、结直肠癌或卵巢癌患者参与。根据症状发生概率确定了四类潜在患者：全低类[即所有症状发生概率低（n = 152）]、全高类（n = 149）、高心理类（n = 121）和低心理类（n = 112）。与全低类患者相比，全高类患者明显更年轻。此外，与其他三类相比，全高类患者的功能状态较低，合并症评分较高，生活质量评分较差。高心理类和低心理类患者报告身体症状的概率中等。低心理类患者报告的症状数量较多，功能状态较低，身体和总体生活质量评分较差。
可以根据症状发生率识别不同的肿瘤患者亚组。与这些亚组相关的患者特征可用于识别同时出现多种症状和生活质量下降风险较高的患者，以便为这些患者提供适当的症状管理干预措施。
