Department of Biostatistics and Bioinformatics, Duke University, Durham, North Carolina 27710, USA.
Genet Epidemiol. 2012 Sep;36(6):538-48. doi: 10.1002/gepi.21645. Epub 2012 Jun 8.
For many clinical studies in cancer, germline DNA is prospectively collected for the purpose of discovering or validating single-nucleotide polymorphisms (SNPs) associated with clinical outcomes. The primary clinical endpoint for many of these studies are time-to-event outcomes such as time of death or disease progression which are subject to censoring mechanisms. The Cox score test can be readily employed to test the association between a SNP and the outcome of interest. In addition to the effect and sample size, and censoring distribution, the power of the test will depend on the underlying genetic risk model and the distribution of the risk allele. We propose a rigorous account for power and sample size calculations under a variety of genetic risk models without resorting to the commonly used contiguous alternative assumption. Practical advice along with an open-source software package to design SNP association studies with survival outcomes are provided.
对于许多癌症临床研究，前瞻性地收集种系 DNA 是为了发现或验证与临床结果相关的单核苷酸多态性 (SNP)。其中许多研究的主要临床终点是时间事件结果，如死亡时间或疾病进展，这些结果受到删失机制的影响。Cox 评分检验可用于检验 SNP 与感兴趣的结果之间的关联。除了效应和样本量以及删失分布外，检验的功效还取决于潜在的遗传风险模型和风险等位基因的分布。我们提出了一种在多种遗传风险模型下进行功效和样本量计算的严格方法，而无需诉诸于常用的连续替代假设。我们还提供了实用建议和一个开源软件包，用于设计带有生存结果的 SNP 关联研究。
