STATISTICAL PERSPECTIVES ON SUBGROUP ANALYSIS: TESTING FOR HETEROGENEITY AND EVALUATING ERROR RATE FOR THE COMPLEMENTARY SUBGROUP

被引：11

作者：

Alosh, Mohamed ^{[1
]}

Huque, Mohammad F. ^{[2
]}

Koch, Gary G. ^{[3
]}

机构：

[1] US FDA, Div Biometr 3, Off Biostat, OTS,CDER, Silver Spring, MD 20993 USA

[2] US FDA, OTS, Off Biostat, CDER, Silver Spring, MD 20993 USA

[3] Univ N Carolina, Dept Biostat, Chapel Hill, NC USA

来源：

JOURNAL OF BIOPHARMACEUTICAL STATISTICS | 2015年 / 25卷 / 06期

关键词：

Complementary subgroup error rate; Supportive assessment; Targeted subgroup; Testing for interaction; QUALITATIVE INTERACTIONS; CLINICAL-TRIALS; POWER;

D O I：

10.1080/10543406.2014.971169

中图分类号：

R9 [药学];

学科分类号：

1007 ;

摘要：

Substantial heterogeneity in treatment effects across subgroups can cause significant findings in the overall population to be driven predominantly by those of a certain subgroup, thus raising concern on whether the treatment should be prescribed for the least benefitted subgroup. Because of its low power, a nonsignificant interaction test can lead to incorrectly prescribing treatment for the overall population. This article investigates the power of the interaction test and its implications. Also, it investigates the probability of prescribing the treatment to a nonbenefitted subgroup on the basis of a nonsignificant interaction test and other recently proposed criteria.

引用

页码：1161 / 1178

页数：18

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