Cox, Nancy J.

Statistical analyses are a crucial component of the biomedical research process and are necessary to draw inferences from biomedical research data. The application of sound statistical methodology is a prerequisite for publication in the American Heart Association (AHA) journal portfolio. The objective of this document is to summarize key aspects of statistical reporting that might be most relevant to the authors, reviewers, and readership of AHA journals. The AHA Scientific Publication Committee convened a task force to inventory existing statistical standards for publication in biomedical journals and to identify approaches suitable for the AHA journal portfolio. The experts on the task force were selected by the AHA Scientific Publication Committee, who identified 12 key topics that serve as the section headers for this document. For each topic, the members of the writing group identified relevant references and evaluated them as a resource to make the standards summarized herein. Each section was independently reviewed by an expert reviewer who was not part of the task force. Expert reviewers were also permitted to comment on other sections if they chose. Differences of opinion were adjudicated by consensus. The standards presented in this report are intended to serve as a guide for high-quality reporting of statistical analyses methods and results.

Background: Coronary heart disease (CHD) is a leading cause of death globally. Although therapy with statins decreases circulating levels of low-density lipoprotein cholesterol and the incidence of CHD, additional events occur despite statin therapy in some individuals. The genetic determinants of this residual cardiovascular risk remain unknown. Methods: We performed a 2-stage genome-wide association study of CHD events during statin therapy. We first identified 3099 cases who experienced CHD events (defined as acute myocardial infarction or the need for coronary revascularization) during statin therapy and 7681 controls without CHD events during comparable intensity and duration of statin therapy from 4 sites in the Electronic Medical Records and Genomics Network. We then sought replication of candidate variants in another 160 cases and 1112 controls from a fifth Electronic Medical Records and Genomics site, which joined the network after the initial genome-wide association study. Finally, we performed a phenome-wide association study for other traits linked to the most significant locus. Results: The meta-analysis identified 7 single nucleotide polymorphisms at a genome-wide level of significance within the LPA/PLG locus associated with CHD events on statin treatment. The most significant association was for an intronic single nucleotide polymorphism within LPA/PLG (rs10455872; minor allele frequency, 0.069; odds ratio, 1.58; 95% confidence interval, 1.35–1.86; P =2.6×10 − 10 ). In the replication cohort, rs10455872 was also associated with CHD events (odds ratio, 1.71; 95% confidence interval, 1.14–2.57; P =0.009). The association of this single nucleotide polymorphism with CHD events was independent of statin-induced change in low-density lipoprotein cholesterol (odds ratio, 1.62; 95% confidence interval, 1.17–2.24; P =0.004) and persisted in individuals with low-density lipoprotein cholesterol ≤70 mg/dL (odds ratio, 2.43; 95% confidence interval, 1.18–4.75; P =0.015). A phenome-wide association study supported the effect of this region on coronary heart disease and did not identify noncardiovascular phenotypes. Conclusions: Genetic variations at the LPA locus are associated with CHD events during statin therapy independently of the extent of low-density lipoprotein cholesterol lowering. This finding provides support for exploring strategies targeting circulating concentrations of lipoprotein(a) to reduce CHD events in patients receiving statins.

AbstractOver the past several years, genome‐wide association studies (GWAS) have succeeded in identifying hundreds of genetic markers associated with common diseases. However, most of these markers confer relatively small increments of risk and explain only a small proportion of familial clustering. To identify obstacles to future progress in genetic epidemiology research and provide recommendations to NIH for overcoming these barriers, the National Cancer Institute sponsored a workshop entitled “Next Generation Analytic Tools for Large‐Scale Genetic Epidemiology Studies of Complex Diseases” on September 15–16, 2010. The goal of the workshop was to facilitate discussions on (1) statistical strategies and methods to efficiently identify genetic and environmental factors contributing to the risk of complex disease; and (2) how to develop, apply, and evaluate these strategies for the design, analysis, and interpretation of large‐scale complex disease association studies in order to guide NIH in setting the future agenda in this area of research. The workshop was organized as a series of short presentations covering scientific (gene‐gene and gene‐environment interaction, complex phenotypes, and rare variants and next generation sequencing) and methodological (simulation modeling and computational resources and data management) topic areas. Specific needs to advance the field were identified during each session and are summarized.Genet. Epidemiol. 36 : 22–35, 2012. © 2011 Wiley Periodicals, Inc.

Abstract Background and Aims: Cancer and Leukemia Group B 80303 was a randomized, phase III study in patients with advanced pancreatic cancer treated with gemcitabine plus either bevacizumab or placebo. We prospectively collected germline DNA and conducted a genome-wide association study (GWAS) using overall survival (OS) as the endpoint. Experimental Design: DNA from 351 patients was genotyped for more than 550,000 single-nucleotide polymorphisms (SNP). Associations between OS and SNPs were investigated using the log-linear 2-way multiplicative Cox proportional hazards model. The subset of 294 genetically European patients was used for the primary analysis. Results: A nonsynonymous SNP in interleukin (IL)17F (rs763780, H161R) and an intronic SNP in strong linkage disequilibrium (rs7771466) were associated with OS using genome-wide criteria (P ≤ 10−7). Median OS was significantly shorter (P = 2.61 × 10−8) for the rs763780 heterozygotes [3.1 months; 95% confidence interval (CI), 2.3–4.3] than for the patients without this variant (6.8 months; 95% CI, 5.8–7.3). After adjustment by stratification factors, the P value for the association was 9.51 × 10−7. Conclusions: The variant 161R form of IL-17F is a natural antagonist of the antiangiogenic effects of wild-type 161H IL-17F, and angiogenesis may play an important role in the metastatic spread of pancreatic cancer. In this preliminary study, we hypothesize that the angiogenetic potential of pancreatic cancers in patients with variant IL-17F is higher than that of tumors in patients with wild-type IL-17F, conferring worse prognosis. This exploratory GWAS may provide the foundation for testing the biology and clinical effects of novel genes and their heritable variants through mechanistic and confirmatory studies in pancreatic cancer. Clin Cancer Res; 18(2); 577–84. ©2011 AACR.

Abstract Purpose: Cell-based approaches were used to identify genetic markers predictive of patients' risk for poor response prior to chemotherapy. Experimental Design: We conducted genome-wide association studies (GWAS) to identify single-nucleotide polymorphisms (SNP) associated with cellular sensitivity to carboplatin through their effects on mRNA expression using International HapMap lymphoblastoid cell lines (LCL) and replicated them in additional LCLs. SNPs passing both stages of the cell-based study were tested for association with progression-free survival (PFS) in patients. Phase 1 validation was based on 377 ovarian cancer patients receiving at least four cycles of carboplatin and paclitaxel from the Australian Ovarian Cancer Study (AOCS). Positive associations were then assessed in phase 2 validation analysis of 1,326 patients from the Ovarian Cancer Association Consortium and The Cancer Genome Atlas. Results: In the initial GWAS, 342 SNPs were associated with carboplatin-induced cytotoxicity, of which 18 unique SNPs were retained after assessing their association with gene expression. One SNP (rs1649942) was replicated in an independent LCL set (Bonferroni adjusted P < 0.05). It was found to be significantly associated with decreased PFS in phase 1 AOCS patients (Pper-allele = 2 × 10−2), with a stronger effect in the subset of women with optimally debulked tumors (Pper-allele = 4 × 10−3). rs1649942 was also associated with poorer overall survival in women with optimally debulked tumors (Pper-allele = 9 × 10−3). However, this SNP was not significant in phase 2 validation analysis with patients from numerous cohorts. Conclusion: This study shows the potential of cell-based, genome-wide approaches to identify germline predictors of treatment outcome and highlights the need for extensive validation in patients to assess their clinical effect. Clin Cancer Res; 17(16); 5490–500. ©2011 AACR.