Methods: Genome-wide scan of 440 093 single-nucleotide polymorphisms (SNPs) was conducted using peripheral blood DNA to identify variants associated with response to first-line carboplatin or cisplatin plus etoposide chemotherapy in 245 patients with SCLC and the results were replicated in another set of 183 patients.

Results: By set association analysis, 20 SNPs were identified to be associated with treatment response, with odds ratios (95% confidence interval) ranging from 2.36 (1.56–3.57) to 4.38 (2.12–9.29) and these results were confirmed in the replication phase. Most of these SNPs (14/20) were clustered on chromosomes 22p11.23, 6q24.3, and 20p12.2 containing BTBD3, STXBP5, and BCR genes.

Methods: We assume that heterogeneity is due to a relatively small number of individuals whose allele frequencies differ from those of the remainder of the sample. For this situation, we propose a new method of handling heterogeneity by removing outliers in a controlled manner. In a coordinate system of the c largest principal components in multidimensional scaling (MDS), we systematically remove one after another of the most extreme outlying individuals and each time recompute the largest association test statistic. The smallest p-value obtained within M removals serves as our test statistic whose significance level is assessed in randomization samples.

Results: In power simulations of our method and three methods in current use, averaged over several different scenarios, the best method turned out to be logistic regression analysis (based on all individuals) with MDS components as covariates.

Conclusion: Our proposed method ranked closely behind logistic regression analysis with MDS components but ahead of other commonly used approaches. In analyses of real datasets our method performed best.