Biomarker studies and other difficult inferential problems: Statistical caveats

被引：5

作者：

Berry, Donald A. ^{[1
]}

机构：

[1] Univ Texas, MD Anderson Canc Ctr, Houston, TX 77030 USA

来源：

SEMINARS IN ONCOLOGY | 2007年 / 34卷 / 02期

关键词：

D O I：

10.1053/j.seminoncol.2007.03.014

中图分类号：

R73 [肿瘤学];

学科分类号：

100214 ;

摘要：

The inferential issues associated with biomarker studies are enormously complex. False-positive conclusions are rampant in the literature. It is wonderful to have many potential biomarkers in trying to explain the heterogeneity of cancer and outcomes of its treatment. But a large number of biomarkers give rise to statistical headaches. False-positives proliferate. A useful approach is to reduce many biomarkers into a single dimension, and to then attempt to confirm the prognostic or predictive value of the single-dimensional quantity. This is not a panacea for all statistical and scientific ailments, but it minimizes some of the problems. A related concern is subset analysis. I give a statistical argument that estrogen-receptor status is predictive of the benefits of chemotherapy in node-positive breast cancer. © 2007 Elsevier Inc. All rights reserved.

引用

页码：S17 / S22

页数：6

共 6 条

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