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药学研究中的交叉设计。

Crossover design in pharmacy research.

作者信息

Cody R L, Slack M K

机构信息

Indian Health Service, Fort Defiance Service Unit, AZ.

出版信息

Ann Pharmacother. 1992 Mar;26(3):327-33. doi: 10.1177/106002809202600303.

DOI:10.1177/106002809202600303
PMID:1532519
Abstract

OBJECTIVE

Reports of pharmacy research using crossover designs were reviewed to determine if the studies adequately consider interaction effects and use appropriate statistical analyses.

DATA SOURCES

All crossover studies published in DICP, The Annals of Pharmacotherapy during 1988 and 1989 were analyzed.

STUDY SELECTION

Reports of crossover studies were included only if at least two treatments were applied in a different order to two or more groups of subjects.

DATA EXTRACTION

The principal characteristics of crossover studies and the critical design variables were listed and each study analyzed according to these variables. The critical design variables included consideration of period, sequence, and carryover effects as well as the presentation of data by groups and the use of multivariate statistical analysis. The analysis was conducted independently by each author and conflicts were discussed until consensus was obtained.

RESULTS

A total of 11 crossover studies were identified: 6 were bioavailability trials, 3 were treatment comparisons, and 2 had multiple objectives. The possibility of period, sequence, or carryover effects was less with bioavailability studies than with treatment comparisons. Only 1 study presented data by group and only 4 studies used multivariate analysis.

CONCLUSIONS

The crossover design appears more appropriate for bioavailability trials than for treatment trials in pharmacy research. Analysis of data from crossover designs could be improved by presenting the data for each treatment group and using multivariate statistical analysis.

摘要

目的

回顾使用交叉设计的药学研究报告,以确定这些研究是否充分考虑了交互作用并使用了适当的统计分析方法。

数据来源

分析了1988年和1989年发表在《药物情报与临床药学》(DICP,《药物治疗学年鉴》)上的所有交叉研究。

研究选择

仅纳入至少两种治疗方法以不同顺序应用于两组或更多组受试者的交叉研究报告。

数据提取

列出交叉研究的主要特征和关键设计变量,并根据这些变量对每项研究进行分析。关键设计变量包括对周期、顺序和残留效应的考虑,以及按组呈现数据和使用多变量统计分析。分析由每位作者独立进行,存在的分歧进行讨论,直至达成共识。

结果

共确定了11项交叉研究:6项为生物利用度试验,3项为治疗比较,2项有多个目标。生物利用度研究中出现周期、顺序或残留效应的可能性低于治疗比较研究。只有1项研究按组呈现数据,只有4项研究使用了多变量分析。

结论

在药学研究中,交叉设计似乎更适用于生物利用度试验而非治疗试验。通过呈现每个治疗组的数据并使用多变量统计分析,可以改进交叉设计数据的分析。

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Ann Pharmacother. 1992 Mar;26(3):327-33. doi: 10.1177/106002809202600303.
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