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在癌症患者群体中使用创新的多元回归程序(第1部分):检测和探究常见相互作用症状(疼痛、疲劳/虚弱、睡眠问题)之间的关系,以此作为发现有影响力的症状对和症状群的策略。

Using an innovative multiple regression procedure in a cancer population (Part 1): detecting and probing relationships of common interacting symptoms (pain, fatigue/weakness, sleep problems) as a strategy to discover influential symptom pairs and clusters.

作者信息

Francoeur Richard B

机构信息

School of Social Work and the Center for Health Innovation, Adelphi University, Garden City, NY, USA ; Center for the Psychosocial Study of Health and Illness, Columbia University, New York, NY, USA.

出版信息

Onco Targets Ther. 2014 Dec 22;8:45-56. doi: 10.2147/OTT.S66465. eCollection 2015.

Abstract

BACKGROUND

The majority of patients with advanced cancer experience symptom pairs or clusters among pain, fatigue, and insomnia. Improved methods are needed to detect and interpret interactions among symptoms or diesease markers to reveal influential pairs or clusters. In prior work, I developed and validated sequential residual centering (SRC), a method that improves the sensitivity of multiple regression to detect interactions among predictors, by conditioning for multicollinearity (shared variation) among interactions and component predictors.

MATERIALS AND METHODS

Using a hypothetical three-way interaction among pain, fatigue, and sleep to predict depressive affect, I derive and explain SRC multiple regression. Subsequently, I estimate raw and SRC multiple regressions using real data for these symptoms from 268 palliative radiation outpatients.

RESULTS

Unlike raw regression, SRC reveals that the three-way interaction (pain × fatigue/weakness × sleep problems) is statistically significant. In follow-up analyses, the relationship between pain and depressive affect is aggravated (magnified) within two partial ranges: 1) complete-to-some control over fatigue/weakness when there is complete control over sleep problems (ie, a subset of the pain-fatigue/weakness symptom pair), and 2) no control over fatigue/weakness when there is some-to-no control over sleep problems (ie, a subset of the pain-fatigue/weakness-sleep problems symptom cluster). Otherwise, the relationship weakens (buffering) as control over fatigue/weakness or sleep problems diminishes.

CONCLUSION

By reducing the standard error, SRC unmasks a three-way interaction comprising a symptom pair and cluster. Low-to-moderate levels of the moderator variable for fatigue/weakness magnify the relationship between pain and depressive affect. However, when the comoderator variable for sleep problems accompanies fatigue/weakness, only frequent or unrelenting levels of both symptoms magnify the relationship. These findings suggest that a countervailing mechanism involving depressive affect could account for the effectiveness of a cognitive behavioral intervention to reduce the severity of a pain, fatigue, and sleep disturbance cluster in a previous randomized trial.

摘要

背景

大多数晚期癌症患者在疼痛、疲劳和失眠之间存在症状组合或症状群。需要改进方法来检测和解释症状或疾病标志物之间的相互作用,以揭示有影响的组合或群集。在之前的工作中,我开发并验证了顺序残差中心化(SRC)方法,该方法通过对相互作用和组成预测因子之间的多重共线性(共享变异)进行校正,提高了多元回归检测预测因子之间相互作用的灵敏度。

材料与方法

利用疼痛、疲劳和睡眠之间假设的三向相互作用来预测抑郁情绪,我推导并解释了SRC多元回归。随后,我使用来自268名姑息性放疗门诊患者的这些症状的真实数据估计原始和SRC多元回归。

结果

与原始回归不同,SRC显示三向相互作用(疼痛×疲劳/虚弱×睡眠问题)具有统计学意义。在后续分析中,疼痛与抑郁情绪之间的关系在两个部分范围内加剧(放大):1)当对睡眠问题有完全控制时(即疼痛-疲劳/虚弱症状组合的一个子集),对疲劳/虚弱有完全到部分控制;2)当对睡眠问题有部分到无控制时(即疼痛-疲劳/虚弱-睡眠问题症状群集的一个子集),对疲劳/虚弱无控制。否则,随着对疲劳/虚弱或睡眠问题的控制减弱,这种关系会减弱(缓冲)。

结论

通过降低标准误差,SRC揭示了一个由症状组合和群集组成的三向相互作用。疲劳/虚弱调节变量的低至中等水平会放大疼痛与抑郁情绪之间的关系。然而,当睡眠问题的共同调节变量与疲劳/虚弱同时出现时,只有两种症状频繁或持续出现才会放大这种关系。这些发现表明,在之前的一项随机试验中,涉及抑郁情绪的一种抵消机制可能解释了认知行为干预减轻疼痛、疲劳和睡眠障碍群集严重程度的有效性。

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