An ordinal logistic regression model with misclassification of the outcome variable and categorical covariate

Ordinal outcomes are frequently employed in diagnosis and clinical trials. Clinical trials of Alzheimer's disease (AD) treatments are a case in point using the status of mild, moderate or severe disease as outcome measures. As in many other outcome oriented studies, the disease status may be misclassified. This study estimates the extent of misclassification in an ordinal outcome such as disease status. Also, this study estimates the extent of misclassification of a predictor variable such as genotype status. An ordinal logistic regression model is commonly used to model the relationship between disease status, the effect of treatment, and other predictive factors. A simulation study was done. First, data based on a set of hypothetical parameters and hypothetical rates of misclassification was created. Next, the maximum likelihood method was employed to generate likelihood equations accounting for misclassification. The Nelder-Mead Simplex method was used to solve for the misclassification and model parameters. Finally, this method was applied to an AD dataset to detect the amount of misclassification present. The estimates of the ordinal regression model parameters were close to the hypothetical parameters. β1 was hypothesized at 0.50 and the mean estimate was 0.488, β2 was hypothesized at 0.04 and the mean of the estimates was 0.04. Although the estimates for the rates of misclassification of X1 were not as close as β1 and β2, they validate this method. X 1 0-1 misclassification was hypothesized as 2.98% and the mean of the simulated estimates was 1.54% and, in the best case, the misclassification of k from high to medium was hypothesized at 4.87% and had a sample mean of 3.62%. In the AD dataset, the estimate for the odds ratio of X 1 of having both copies of the APOE 4 allele changed from an estimate of 1.377 to an estimate 1.418, demonstrating that the estimates of the odds ratio changed when the analysis includes adjustment for misclassification. ^

Survival of gastrointestinal and stromal tumor patients at UT M.D. Anderson Cancer Center

Objective. Gastrointestinal Stromal Tumors (GISTs) are rare mesenchymal tumors of the gastrointestinal (GI) tract with spindled cell, epithelioid, or occasionally pleomorphic morphology. The primary objective of this paper is to describe the demographic and clinical characteristics and survival among GIST patients registered at the University of Texas M.D. Anderson Cancer Center (MDACC). ^ Methods. This cohort study includes 783 consecutive patients diagnosed with GIST from 1995 to 2007. Demographic, clinical and survival information were obtained from the MDACC cancer registry. ^ Statistical Analysis. Kaplan-Meier survival curves, univariate and multivariate Cox proportional hazards analysis were conducted to estimate survival and identify prognostic clinical factors associated with survival. Results. The age at diagnosis of MDACC GIST cases ranged from 17 to 91 with a mean of 57 years and a male-to-female ratio of 1.3:1. The racial distribution was whites 77%, African-Americans 9.5%, Hispanics 9.3% and other races 4.2%. Fifty per cent of the GISTs arose from stomach, 35% small intestine, 7% retroperitoneal space, 6% colorectal and 2% were omentum and mesentery. About half of the tumors were less than 10 cm in size. Fifty eight per cent of the tumors were localized whereas 36% were metastatic. MDACC GIST patients were generally comparable to SEER patients, but, on the average, were 7 years younger than SEER patients and were predominantly whites. ^ Stratification of 783 GIST cases by year of diagnosis based on the introduction of imatinib treatment in 2000 revealed that 60% of the GIST cases were first diagnosed between 2000 and 2007 whereas, 40% were first diagnosed between 1995 and 1999. There was a significant difference between the two cohorts in the distribution of race, GIST symptom, tumor size, tumor site, and stage of the tumor at diagnosis. The 1- and 5-year survival was 93% and 59% in the 1995–2007 cohort. Multivariate Cox regression analysis identified age at diagnosis (p<0.001), female sex (p=0.047), tumor size (p=0.07), multiple cancers (p=0.002), and GIST diagnosed between 2000 and 2007 (p<0.001) were significantly associated with survival. Approximately, 58% of the cases were treated with imatinib whereas 42% did not receive imatinib in 2000–2005 cohort. There was a significant difference in survival between imatinib and non-imatinib groups and in the distribution of tumor size categories, stage of the tumor at diagnosis and cancers before the diagnosis of GIST. The 1- and 5-year survival for imatinib patients was 99% and 73% and was 91% and 63% for non-imatinib patients. Multivariate Cox regression analysis of the 2000–2007 cohort identified, age at diagnosis and tumor stage as possible prognostic factors associated with survival.^

Perspectives on the public health implications of global climate change and the epidemiology of vector-borne disease

Global climate change is becoming an increasing concern among the public health community. Some researchers believe the earth is rapidly undergoing changes in temperature, sea level, population movement, and extreme weather phenomenon. With these geographic, meteorological, and social changes come increased threats to human health. One of these threats is the spread of vector-borne infectious diseases. The changes mentioned above are believed to contribute to increased arthropod survival, transmission, and habitation. These changes, in turn, lead to increased incidence among neighboring human populations. It is also argued that human action may play more of a role than climate change. This systematic review served to determine whether or not climate change poses a significant risk to human exposure and increased incidence of vector-borne disease. ^

Genetic variations in the PI3K-AKT-mTOR pathway and bladder cancer susceptibility and clinical outcomes

Bladder cancer is the fourth most common cancer in men in the United States. There is compelling evidence supporting that genetic variations contribute to the risk and outcomes of bladder cancer. The PI3K-AKT-mTOR pathway is a major cellular pathway involved in proliferation, invasion, inflammation, tumorigenesis, and drug response. Somatic aberrations of PI3K-AKT-mTOR pathway are frequent events in several cancers including bladder cancer; however, no studies have investigated the role of germline genetic variations in this pathway in bladder cancer. In this project, we used a large case control study to evaluate the associations of a comprehensive catalogue of SNPs in this pathway with bladder cancer risk and outcomes. Three SNPs in RAPTOR were significantly associated with susceptibility: rs11653499 (OR: 1.79, 95%CI: 1.24–2.60), rs7211818 (OR: 2.13, 95%CI: 1.35–3.36), and rs7212142 (OR: 1.57, 95%CI: 1.19–2.07). Two haplotypes constructed from these 3 SNPs were also associated with bladder cancer risk. In combined analysis, a significant trend was observed for increased risk with an increase in the number of unfavorable genotypes (P for trend<0.001). Classification and regression tree analysis identified potential gene-environment interactions between RPS6KA5 rs11653499 and smoking. In superficial bladder cancer, we found that PTEN rs1234219 and rs11202600, TSC1 rs7040593, RAPTOR rs901065, and PIK3R1 rs251404 were significantly associated with recurrence in patients receiving BCG. In muscle invasive and metastatic bladder cancer, AKT2 rs3730050, PIK3R1 rs10515074, and RAPTOR rs9906827 were associated with survival. Survival tree analysis revealed potential gene-gene interactions: patients carrying the unfavorable genotypes of PTEN rs1234219 and TSC1 rs704059 exhibited a 5.24-fold (95% CI: 2.44–11.24) increased risk of recurrence. In combined analysis, with the increasing number of unfavorable genotypes, there was a significant trend of higher risk of recurrence and death (P for trend<0.001) in Cox proportional hazard regression analysis, and shorter event (recurrence and death) free survival in Kaplan-Meier estimates (P log rank<0.001). This study strongly suggests that genetic variations in PI3K-AKT-mTOR pathway play an important role in bladder cancer development. The identified SNPs, if validated in further studies, may become valuable biomarkers in assessing an individual's cancer risk, predicting prognosis and treatment response, and facilitating physicians to make individualized treatment decisions. ^

HPV vaccine coverage in Texas counties: An application of multilevel, small area estimation

Health departments, research institutions, policy-makers, and healthcare providers are often interested in knowing the health status of their clients/constituents. Without the resources, financially or administratively, to go out into the community and conduct health assessments directly, these entities frequently rely on data from population-based surveys to supply the information they need. Unfortunately, these surveys are ill-equipped for the job due to sample size and privacy concerns. Small area estimation (SAE) techniques have excellent potential in such circumstances, but have been underutilized in public health due to lack of awareness and confidence in applying its methods. The goal of this research is to make model-based SAE accessible to a broad readership using clear, example-based learning. Specifically, we applied the principles of multilevel, unit-level SAE to describe the geographic distribution of HPV vaccine coverage among females aged 11-26 in Texas.^ Multilevel (3 level: individual, county, public health region) random-intercept logit models of HPV vaccination (receipt of ≥ 1 dose Gardasil® ) were fit to data from the 2008 Behavioral Risk Factor Surveillance System (outcome and level 1 covariates) and a number of secondary sources (group-level covariates). Sampling weights were scaled (level 1) or constructed (levels 2 & 3), and incorporated at every level. Using the regression coefficients (and standard errors) from the final models, I simulated 10,000 datasets for each regression coefficient from the normal distribution and applied them to the logit model to estimate HPV vaccine coverage in each county and respective demographic subgroup. For simplicity, I only provide coverage estimates (and 95% confidence intervals) for counties.^ County-level coverage among females aged 11-17 varied from 6.8-29.0%. For females aged 18-26, coverage varied from 1.9%-23.8%. Aggregated to the state level, these values translate to indirect state estimates of 15.5% and 11.4%, respectively; both of which fall within the confidence intervals for the direct estimates of HPV vaccine coverage in Texas (Females 11-17: 17.7%, 95% CI: 13.6, 21.9; Females 18-26: 12.0%, 95% CI: 6.2, 17.7).^ Small area estimation has great potential for informing policy, program development and evaluation, and the provision of health services. Harnessing the flexibility of multilevel, unit-level SAE to estimate HPV vaccine coverage among females aged 11-26 in Texas counties, I have provided (1) practical guidance on how to conceptualize and conduct modelbased SAE, (2) a robust framework that can be applied to other health outcomes or geographic levels of aggregation, and (3) HPV vaccine coverage data that may inform the development of health education programs, the provision of health services, the planning of additional research studies, and the creation of local health policies.^

Genetic variants in the mammalian target of rapamycin (mTOR) signaling pathway as predictors of survival and clinical response in women with ovarian cancer

Background. The mTOR pathway is commonly altered in human tumors and promotes cell survival and proliferation. Preliminary evidence suggests this pathway's involvement in chemoresistance to platinum and taxanes, first line therapy for epithelial ovarian cancer. A pathway-based approach was used to identify individual germline single nucleotide polymorphisms (SNPs) and cumulative effects of multiple genetic variants in mTOR pathway genes and their association with clinical outcome in women with ovarian cancer. ^ Methods. The case-series was restricted to 319 non-Hispanic white women with high grade ovarian cancer treated with surgery and platinum-based chemotherapy. 135 SNPs in 20 representative genes in the mTOR pathway were genotyped. Hazard ratios (HRs) for death and Odds ratios (ORs) for failure to respond to primary therapy were estimated for each SNP using the multivariate Cox proportional hazards model and multivariate logistic regression model, respectively, while adjusting for age, stage, histology and treatment sequence. A survival tree analysis of SNPs with a statistically significant association (p<0.05) was performed to identify higher order gene-gene interactions and their association with overall survival. ^ Results. There was no statistically significant difference in survival by tumor histology or treatment regimen. The median survival for the cohort was 48.3 months. Seven SNPs were significantly associated with decreased survival. Compared to those with no unfavorable genotypes, the HR for death increased significantly with the increasing number of unfavorable genotypes and women in the highest risk category had HR of 4.06 (95% CI 2.29–7.21). The survival tree analysis also identified patients with different survival patterns based on their genetic profiles. 13 SNPs on five different genes were found to be significantly associated with a treatment response, defined as no evidence of disease after completion of primary therapy. Rare homozygous genotype of SNP rs6973428 showed a 5.5-fold increased risk compared to the wild type carrying genotypes. In the cumulative effect analysis, the highest risk group (individuals with ≥8 unfavorable genotypes) was significantly less likely to respond to chemotherapy (OR=8.40, 95% CI 3.10–22.75) compared to the low risk group (≤4 unfavorable genotypes). ^ Conclusions. A pathway-based approach can demonstrate cumulative effects of multiple genetic variants on clinical response to chemotherapy and survival. Therapy targeting the mTOR pathway may modify outcome in select patients.^

Performance of HbA1c for classifying diabetes and diagnostic threshold for diabetes among the Mexican American border community

Objective. In 2009, the International Expert Committee recommended the use of HbA1c test for diagnosis of diabetes. Although it has been recommended for the diagnosis of diabetes, its precise test performance among Mexican Americans is uncertain. A strong “gold standard” would rely on repeated blood glucose measurement on different days, which is the recommended method for diagnosing diabetes in clinical practice. Our objective was to assess test performance of HbA1c in detecting diabetes and pre-diabetes against repeated fasting blood glucose measurement for the Mexican American population living in United States-Mexico border. Moreover, we wanted to find out a specific and precise threshold value of HbA1c for Diabetes Mellitus (DM) and pre-diabetes for this high-risk population which might assist in better diagnosis and better management of patient diabetes. ^ Research design and methods. We used CCHC dataset for our study. In 2004, the Cameron County Hispanic Cohort (CCHC), now numbering 2,574, was established drawn from randomly selected households on the basis of 2000 Census tract data. The CCHC study randomly selected a subset of people (aged 18-64 years) in CCHC cohort households to determine the influence of SES on diabetes and obesity. Among the participants in Cohort-2000, 67.15% are female; all are Hispanic. ^ Individuals were defined as having diabetes mellitus (Fasting plasma glucose [FPG] ≥ 126 mg/dL or pre-diabetes (100 ≤ FPG < 126 mg/dL). HbA1c test performance was evaluated using receiver operator characteristic (ROC) curves. Moreover, change-point models were used to determine HbA1c thresholds compatible with FPG thresholds for diabetes and pre-diabetes. ^ Results. When assessing Fasting Plasma Glucose (FPG) is used to detect diabetes, the sensitivity and specificity of HbA1c≥ 6.5% was 75% and 87% respectively (area under the curve 0.895). Additionally, when assessing FPG to detect pre-diabetes, the sensitivity and specificity of HbA1c≥ 6.0% (ADA recommended threshold) was 18% and 90% respectively. The sensitivity and specificity of HbA1c≥ 5.7% (International Expert Committee recommended threshold) for detecting pre-diabetes was 31% and 78% respectively. ROC analyses suggest HbA1c as a sound predictor of diabetes mellitus (area under the curve 0.895) but a poorer predictor for pre-diabetes (area under the curve 0.632). ^ Conclusions. Our data support the current recommendations for use of HbA1c in the diagnosis of diabetes for the Mexican American population as it has shown reasonable sensitivity, specificity and accuracy against repeated FPG measures. However, use of HbA1c may be premature for detecting pre-diabetes in this specific population because of the poor sensitivity with FPG. It might be the case that HbA1c is differentiating the cases more effectively who are at risk of developing diabetes. Following these pre-diabetic individuals for a longer-term for the detection of incident diabetes may lead to more confirmatory result.^

Data quality in trauma transfusion studies and the impact of missing data on predicting massive transfusion

Maximizing data quality may be especially difficult in trauma-related clinical research. Strategies are needed to improve data quality and assess the impact of data quality on clinical predictive models. This study had two objectives. The first was to compare missing data between two multi-center trauma transfusion studies: a retrospective study (RS) using medical chart data with minimal data quality review and the PRospective Observational Multi-center Major Trauma Transfusion (PROMMTT) study with standardized quality assurance. The second objective was to assess the impact of missing data on clinical prediction algorithms by evaluating blood transfusion prediction models using PROMMTT data. RS (2005-06) and PROMMTT (2009-10) investigated trauma patients receiving ≥ 1 unit of red blood cells (RBC) from ten Level I trauma centers. Missing data were compared for 33 variables collected in both studies using mixed effects logistic regression (including random intercepts for study site). Massive transfusion (MT) patients received ≥ 10 RBC units within 24h of admission. Correct classification percentages for three MT prediction models were evaluated using complete case analysis and multiple imputation based on the multivariate normal distribution. A sensitivity analysis for missing data was conducted to estimate the upper and lower bounds of correct classification using assumptions about missing data under best and worst case scenarios. Most variables (17/33=52%) had <1% missing data in RS and PROMMTT. Of the remaining variables, 50% demonstrated less missingness in PROMMTT, 25% had less missingness in RS, and 25% were similar between studies. Missing percentages for MT prediction variables in PROMMTT ranged from 2.2% (heart rate) to 45% (respiratory rate). For variables missing >1%, study site was associated with missingness (all p≤0.021). Survival time predicted missingness for 50% of RS and 60% of PROMMTT variables. MT models complete case proportions ranged from 41% to 88%. Complete case analysis and multiple imputation demonstrated similar correct classification results. Sensitivity analysis upper-lower bound ranges for the three MT models were 59-63%, 36-46%, and 46-58%. Prospective collection of ten-fold more variables with data quality assurance reduced overall missing data. Study site and patient survival were associated with missingness, suggesting that data were not missing completely at random, and complete case analysis may lead to biased results. Evaluating clinical prediction model accuracy may be misleading in the presence of missing data, especially with many predictor variables. The proposed sensitivity analysis estimating correct classification under upper (best case scenario)/lower (worst case scenario) bounds may be more informative than multiple imputation, which provided results similar to complete case analysis.^

Evidence-Based Practice in PubMed: Are Shared Filters Useful to Health Sciences Academic Users?

Objectives In April 2010, the Université de Montréal’s Health Sciences Library has implemented shared filters in its institutional PubMed account. Most of these filters are designed to highlight resources for evidence-based practice, such as Clinical Queries, Systematic Reviews and Evidence-based Synopsis. We now want to measure how those filters are perceived and used by our users. Methods For one month, data was gathered through an online questionnaire proposed to users of Université de Montréal’s PubMed account. A print version was also distributed to participants in information literacy workshops given by the health sciences librarians. Respondents were restricted to users affiliated to Université de Montréal’s faculties of Medicine, Dentistry, Veterinary Sciences, Nursing and Pharmacy. Basic user information such as year/program of study or department affiliation was also collected. The questionnaire allowed users to identify the filters they use, assess the relevance of filters, and also suggest new ones. Results Survey results showed that the shared filters of Université de Montreal’s PubMed account were found useful by the majority of respondents. Filters allowing rapid access to secondary resources ranked among the most relevant (Reviews, Systematic Reviews, Cochrane Database of Systematic Reviews, Practice Guidelines and Clinical Evidence). For Clinical Study Queries, Randomized Controlled Trial (Therapy/Narrow) was considered the most useful. Some new shared filters have been suggested by respondents. Finally, 18% of the respondents indicated that they did not quite understand the relevance of filters. Conclusion Based on the survey results, shared filters considered most useful will be kept, some will be enhanced and others removed so that suggested ones could be added. The fact that some respondents did not understand well the relevance of filters could potentially be addressed through our PubMed workshops, online library guides or by renaming some filters in a more meaningful way.

Integrating information literacy in health sciences curricula: a case study from Québec

Objective: To portray an information literacy programme demonstrating a high level of integration in health sciences curricula and a teaching orientation aiming towards the development of lifelong learning skills. The setting is a French-speaking North American university. Methods: The offering includes standard workshops such as MEDLINE searching and specialised sessions such as pharmaceutical patents searching. A contribution to an international teaching collaboration in Haiti where workshops had to be thoroughly adapted to the clientele is also presented. Online guides addressing information literacy topics complement the programme. Results and evaluation: A small team of librarians and technicians taught 276 hours of library instruction during the 2011-2012 academic year. Methods used for evaluating information skills include scoring features of literature searches and user satisfaction surveys. Discussion: Privileged contacts between librarians and faculty resulting from embedded library instruction as well as from active participation in library committees result in a growing reputation of library services across academic departments and bring forth collaboration opportunities. Sustainability and evolution of the library instruction programme is warranted by frequent communication with partners in the clinical field, active involvement in academic networks and health library associations, and reflective professional strategies.

Genomic architecture of sickle cell disease clinical variation in children from West Africa : a case-control study design

Contexte : L’anémie falciforme ou drépanocytose est un problème de santé important, particulièrement pour les patients d’origine africaine. La variation phénotypique de l’anémie falciforme est problématique pour le suivi et le traitement des patients. L’architecture génomique responsable de cette variabilité est peu connue. Principe : Mieux saisir la contribution génétique de la variation clinique de cette maladie facilitera l’identification des patients à risque de développer des phénotypes sévères, ainsi que l’adaptation des soins. Objectifs : L’objectif général de cette thèse est de combler les lacunes relatives aux connaissances sur l’épidémiologie génomique de l’anémie falciforme à l’aide d’une cohorte issue au Bénin. Les objectifs spécifiques sont les suivants : 1) caractériser les profils d’expressions génomiques associés à la sévérité de l’anémie falciforme ; 2) identifier des biomarqueurs de la sévérité de l’anémie falciforme ; 3) identifier la régulation génétique des variations transcriptionelles ; 4) identifier des interactions statistiques entre le génotype et le niveau de sévérité associé à l’expression ; 5) identifier des cibles de médicaments pour améliorer l’état des patients atteints d’anémie falciforme. Méthode : Une étude cas-témoins de 250 patients et 61 frères et soeurs non-atteints a été menée au Centre de Prise en charge Médical Intégré du Nourrisson et de la Femme Enceinte atteints de Drépanocytose, au Bénin entre février et décembre 2010. Résultats : Notre analyse a montré que des profils d’expressions sont associés avec la sévérité de l’anémie falciforme. Ces profils sont enrichis de génes des voies biologiques qui contribuent à la progression de la maladie : l’activation plaquettaire, les lymphocytes B, le stress, l’inflammation et la prolifération cellulaire. Des biomarqueurs transcriptionnels ont permis de distinguer les patients ayant des niveaux de sévérité clinique différents. La régulation génétique de la variation de l’expression des gènes a été démontrée et des interactions ont été identifiées. Sur la base de ces résultats génétiques, des cibles de médicaments sont proposées. Conclusion: Ce travail de thèse permet de mieux comprendre l’impact de la génomique sur la sévérité de l’anémie falciforme et ouvre des perspectives de développement de traitements ciblés pour améliorer les soins offerts aux patients.

A Interview with Professor Carl May, Head of Research, Faculty of Health Sciences

13 minute interview in which Professor May discusses his thoughts on the purpose of clinical research.

DNA nucleotide excision repair gene single nucleotide polymorphisms and hereditary nonpolyposis colorectal cancer

Hereditary nonpolyposis colorectal cancer (HNPCC) is an autosomal dominant disease caused by germline mutations in DNA mismatch repair(MMR) genes. The nucleotide excision repair(NER) pathway plays a very important role in cancer development. We systematically studied interactions between NER and MMR genes to identify NER gene single nucleotide polymorphism (SNP) risk factors that modify the effect of MMR mutations on risk for cancer in HNPCC. We analyzed data from polymorphisms in 10 NER genes that had been genotyped in HNPCC patients that carry MSH2 and MLH1 gene mutations. The influence of the NER gene SNPs on time to onset of colorectal cancer (CRC) was assessed using survival analysis and a semiparametric proportional hazard model. We found the median age of onset for CRC among MMR mutation carriers with the ERCC1 mutation was 3.9 years earlier than patients with wildtype ERCC1(median 47.7 vs 51.6, log-rank test p=0.035). The influence of Rad23B A249V SNP on age of onset of HNPCC is age dependent (likelihood ratio test p=0.0056). Interestingly, using the likelihood ratio test, we also found evidence of genetic interactions between the MMR gene mutations and SNPs in ERCC1 gene(C8092A) and XPG/ERCC5 gene(D1104H) with p-values of 0.004 and 0.042, respectively. An assessment using tree structured survival analysis (TSSA) showed distinct gene interactions in MLH1 mutation carriers and MSH2 mutation carriers. ERCC1 SNP genotypes greatly modified the age onset of HNPCC in MSH2 mutation carriers, while no effect was detected in MLH1 mutation carriers. Given the NER genes in this study play different roles in NER pathway, they may have distinct influences on the development of HNPCC. The findings of this study are very important for elucidation of the molecular mechanism of colon cancer development and for understanding why some mutation carriers of the MSH2 and MLH1 gene develop CRC early and others never develop CRC. Overall, the findings also have important implications for the development of early detection strategies and prevention as well as understanding the mechanism of colorectal carcinogenesis in HNPCC. ^

Association between glycemic index and glycemic load and the risk of incident coronary heart disease among whites and African Americans with and without type 2 diabetes: The Atherosclerosis Risk in Communities study

Several studies have examined the association between high glycemic index (GI) and glycemic load (GL) diets and the risk for coronary heart disease (CHD). However, most of these studies were conducted primarily on white populations. The primary aim of this study was to examine whether high GI and GL diets are associated with increased risk for developing CHD in whites and African Americans, non-diabetics and diabetics, and within stratifications of body mass index (BMI) and hypertension (HTN). Baseline and 17-year follow-up data from ARIC (Atherosclerosis Risk in Communities) study was used. The study population (13,051) consisted of 74% whites, 26% African Americans, 89% non-diabetics, 11% diabetics, 43% male, 57% female aged 44 to 66 years at baseline. Data from the ARIC food frequency questionnaire at baseline were analyzed to provide GI and GL indices for each subject. Increases of 25 and 30 units for GI and GL respectively were used to describe relationships on incident CHD risk. Adjusted hazard ratios for propensity score with 95% confidence intervals (CI) were used to assess associations. During 17 years of follow-up (1987 to 2004), 1,683 cases of CHD was recorded. Glycemic index was associated with 2.12 fold (95% CI: 1.05, 4.30) increased incident CHD risk for all African Americans and GL was associated with 1.14 fold (95% CI: 1.04, 1.25) increased CHD risk for all whites. In addition, GL was also an important CHD risk factor for white non-diabetics (HR=1.59; 95% CI: 1.33, 1.90). Furthermore, within stratum of BMI 23.0 to 29.9 in non-diabetics, GI was associated with an increased hazard ratio of 11.99 (95% CI: 2.31, 62.18) for CHD in African Americans, and GL was associated with 1.23 fold (1.08, 1.39) increased CHD risk in whites. Body mass index modified the effect of GI and GL on CHD risk in all whites and white non-diabetics. For HTN, both systolic blood pressure and diastolic blood pressure modified the effect on GI and GL on CHD risk in all whites and African Americans, white and African American non-diabetics, and white diabetics. Further studies should examine other factors that could influence the effects of GI and GL on CHD risk, including dietary factors, physical activity, and diet-gene interactions. ^