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Abstract：
BACKGROUND: The relative scale has been used for decades in analysing binary data in epidemiology. In contrast, there has been a long tradition of carrying out meta-analyses of continuous outcomes on the absolute, original measurement, scale. The biological rationale for using the relative scale in the analysis of binary outcomes is that it adjusts for baseline variations; however, similar baseline variations can occur in continuous outcomes and relative effect scale may therefore be often useful also for continuous outcomes. The aim of this study was to determine whether the relative scale is more consistent with empirical data on treating the common cold than the absolute scale.
METHODS: Individual patient data was available for 2 randomized trials on zinc lozenges for the treatment of the common cold. Mossad (Ann Intern Med 125:81-8, 1996) found 4.0 days and 43% reduction, and Petrus (Curr Ther Res 59:595-607, 1998) found 1.77 days and 25% reduction, in the duration of colds. In both trials, variance in the placebo group was significantly greater than in the zinc lozenge group. The effect estimates were applied to the common cold distributions of the placebo groups, and the resulting distributions were compared with the actual zinc lozenge group distributions.
RESULTS: When the absolute effect estimates, 4.0 and 1.77 days, were applied to the placebo group common cold distributions, negative and zero (i.e., impossible) cold durations were predicted, and the high level variance remained. In contrast, when the relative effect estimates, 43 and 25%, were applied, impossible common cold durations were not predicted in the placebo groups, and the cold distributions became similar to those of the zinc lozenge groups.
CONCLUSIONS: For some continuous outcomes, such as the duration of illness and the duration of hospital stay, the relative scale leads to a more informative statistical analysis and more effective communication of the study findings. The transformation of continuous data to the relative scale is simple with a spreadsheet program, after which the relative scale data can be analysed using standard meta-analysis software. The option for the analysis of relative effects of continuous outcomes directly from the original data should be implemented in standard meta-analysis programs.
METHODS: Individual patient data was available for 2 randomized trials on zinc lozenges for the treatment of the common cold. Mossad (Ann Intern Med 125:81-8, 1996) found 4.0 days and 43% reduction, and Petrus (Curr Ther Res 59:595-607, 1998) found 1.77 days and 25% reduction, in the duration of colds. In both trials, variance in the placebo group was significantly greater than in the zinc lozenge group. The effect estimates were applied to the common cold distributions of the placebo groups, and the resulting distributions were compared with the actual zinc lozenge group distributions.
RESULTS: When the absolute effect estimates, 4.0 and 1.77 days, were applied to the placebo group common cold distributions, negative and zero (i.e., impossible) cold durations were predicted, and the high level variance remained. In contrast, when the relative effect estimates, 43 and 25%, were applied, impossible common cold durations were not predicted in the placebo groups, and the cold distributions became similar to those of the zinc lozenge groups.
CONCLUSIONS: For some continuous outcomes, such as the duration of illness and the duration of hospital stay, the relative scale leads to a more informative statistical analysis and more effective communication of the study findings. The transformation of continuous data to the relative scale is simple with a spreadsheet program, after which the relative scale data can be analysed using standard meta-analysis software. The option for the analysis of relative effects of continuous outcomes directly from the original data should be implemented in standard meta-analysis programs.
摘要：
背景：相对量表已经在分析流行病学中的二元数据中使用了数十年。相比之下,有一个长期的传统进行荟萃分析的连续结果的绝对，原始测量，规模。在二元结果分析中使用相对量表的生物学原理是它根据基线变化进行调整；然而，在连续结局中可能出现类似的基线变化,因此相对效应量表通常也可用于连续结局.这项研究的目的是确定相对量表是否比绝对量表更符合治疗普通感冒的经验数据。
方法：2项关于锌锭剂治疗普通感冒的随机试验提供了个体患者数据。Mossad(AnnInternMed125:81-8,1996)发现4.0天和43%的减少，和Petrus(CurrTherRes59:595-607,1998)发现1.77天和25%的减少，在感冒期间。在两个试验中,安慰剂组的方差显著大于锌锭剂组.效应估计应用于安慰剂组的普通感冒分布，并将所得分布与实际的锌锭剂组分布进行比较。
结果：当绝对效应估计时，4.0和1.77天，适用于安慰剂组普通感冒分布，负和零(即，不可能)预测了冷持续时间，高水平的差异仍然存在。相比之下,当相对效应估计时，43%和25%，被应用，安慰剂组没有预测不可能的普通感冒持续时间，冷分布变得与锌锭剂组相似。
结论：对于一些连续的结果，如疾病持续时间和住院时间，相对量表导致更翔实的统计分析和更有效的研究结果沟通。用电子表格程序将连续数据转换为相对比例很简单，之后，可以使用标准荟萃分析软件分析相对比例数据。直接从原始数据中分析连续结果的相对影响的选项应在标准的荟萃分析程序中实施。
方法：2项关于锌锭剂治疗普通感冒的随机试验提供了个体患者数据。Mossad(AnnInternMed125:81-8,1996)发现4.0天和43%的减少，和Petrus(CurrTherRes59:595-607,1998)发现1.77天和25%的减少，在感冒期间。在两个试验中,安慰剂组的方差显著大于锌锭剂组.效应估计应用于安慰剂组的普通感冒分布，并将所得分布与实际的锌锭剂组分布进行比较。
结果：当绝对效应估计时，4.0和1.77天，适用于安慰剂组普通感冒分布，负和零(即，不可能)预测了冷持续时间，高水平的差异仍然存在。相比之下,当相对效应估计时，43%和25%，被应用，安慰剂组没有预测不可能的普通感冒持续时间，冷分布变得与锌锭剂组相似。
结论：对于一些连续的结果，如疾病持续时间和住院时间，相对量表导致更翔实的统计分析和更有效的研究结果沟通。用电子表格程序将连续数据转换为相对比例很简单，之后，可以使用标准荟萃分析软件分析相对比例数据。直接从原始数据中分析连续结果的相对影响的选项应在标准的荟萃分析程序中实施。
