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随机效应模型及其他方法在一项艾滋病临床试验多维生活质量数据分析中的应用。

Application of random effects models and other methods to the analysis of multidimensional quality of life data in an AIDS clinical trial.

作者信息

Wu A W, Gray S M, Brookmeyer R

机构信息

Department of Health Policy and Management, Johns Hopkins University, Baltimore, MD, USA.

出版信息

Med Care. 1999 Mar;37(3):249-58. doi: 10.1097/00005650-199903000-00005.

DOI:10.1097/00005650-199903000-00005
PMID:10098569
Abstract

BACKGROUND

Current analytic methods applied to multidimensional health-related quality of life (HRQOL) data do not borrow strength across analyses and do not produce summary estimates of effect.

OBJECTIVES

To compare a random effects modelling approach for the analysis of multidimensional HRQOL data to the following: (1) separate analyses for each dimension; (2) O'Brien's global test procedure; and (3) multivariate analysis of variance (MANOVA).

RESEARCH DESIGN

Randomized clinical trial comparing 3 treatments (Trimethoprim-Sulfamethoxazole [TS], Dapsone-Trimethoprim [DT], and Clindamycin-Primaquine [CP] for Pneumocystis carinii pneumonia [PCP]).

SUBJECTS

Patients with PCP enrolled in AIDS Clinical Trials Group Protocol 108.

MEASURES

A 33-item battery assessing 7 dimensions of HRQOL: physical functioning, pain, energy, general health perceptions, disability, pulmonary symptoms, and constitutional symptoms.

RESULTS

Analyses focused on changes in score from baseline to Day 7 (n = 145). Separate analyses for each dimension suggested a trend favoring CP versus TS, but using a Bonferroni correction no differences were statistically significant. O'Brien's global procedure for a test of no-treatment effect versus superiority of one treatment yielded P = 0.07. MANOVA did not reveal significant differences among treatment groups. A random effects model using fixed treatment and dimension effects and separate random effects for each person showed a significant overall treatment effect (P = 0.02); changes in scores for CP averaged 10 points greater than for TS.

CONCLUSIONS

Random-effects models provide a flexible class of models for analyzing multidimensional quality of life data and estimating treatment effects because they borrow strength across dimensions.

摘要

背景

目前应用于多维健康相关生活质量(HRQOL)数据的分析方法无法在各分析间借鉴优势,也无法得出效应的汇总估计值。

目的

将用于分析多维HRQOL数据的随机效应建模方法与以下方法进行比较:(1)对每个维度进行单独分析;(2)奥布赖恩全局检验程序;(3)多变量方差分析(MANOVA)。

研究设计

随机临床试验,比较3种治疗方法(甲氧苄啶-磺胺甲恶唑[TS]、氨苯砜-甲氧苄啶[DT]和克林霉素-伯氨喹[CP])治疗卡氏肺孢子虫肺炎(PCP)的效果。

研究对象

参与艾滋病临床试验组方案108的PCP患者。

测量指标

一套包含33个条目的问卷,评估HRQOL的7个维度:身体功能、疼痛、精力、总体健康感知、残疾、肺部症状和全身症状。

结果

分析重点为从基线到第7天的得分变化(n = 145)。对每个维度的单独分析表明,CP组与TS组相比有一定趋势,但经邦费罗尼校正后,差异无统计学意义。奥布赖恩关于无治疗效应与一种治疗方法优越性的全局检验得出P = 0.07。MANOVA未显示治疗组间有显著差异。使用固定治疗和维度效应以及每个人单独的随机效应的随机效应模型显示出显著的总体治疗效应(P = 0.02);CP组得分变化平均比TS组高10分。

结论

随机效应模型为分析多维生活质量数据和估计治疗效应提供了一类灵活的模型,因为它们能在各维度间借鉴优势。

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