Continuous safety screens for randomized controlled clinical trials with blinded treatment information

Standard methods for testing safety data are needed to ensure the safe conduct of clinical trials. In particular, objective rules for reliably identifying unsafe treatments need to be put into place to help protect patients from unnecessary harm. DMCs are uniquely qualified to evaluate accumulating unblinded data and make recommendations about the continuing safe conduct of a trial. However, it is the trial leadership who must make the tough ethical decision about stopping a trial, and they could benefit from objective statistical rules that help them judge the strength of evidence contained in the blinded data. We design early stopping rules for harm that act as continuous safety screens for randomized controlled clinical trials with blinded treatment information, which could be used by anyone, including trial investigators (and trial leadership). A Bayesian framework, with emphasis on the likelihood function, is used to allow for continuous monitoring without adjusting for multiple comparisons. Close collaboration between the statistician and the clinical investigators will be needed in order to design safety screens with good operating characteristics. Though the math underlying this procedure may be computationally intensive, implementation of the statistical rules will be easy and the continuous screening provided will give suitably early warning when real problems were to emerge. Trial investigators and trial leadership need these safety screens to help them to effectively monitor the ongoing safe conduct of clinical trials with blinded data.^

Persisting abdominal symptoms after travelers' diarrhea: Is there a genetic predisposition?

Functional gastrointestinal disorders (FGIDs) are defined as ailments of the mid or lower gastrointestinal tract which are not attributable to any discernable anatomic or biochemical defects.1 FGIDs include functional bowel disorders, also known as persisting abdominal symptoms (PAS). Irritable bowel syndrome (IBS) is one of the most common illnesses classified under PAS.2,3 This is the first prospective study that looks at the etiology and pathogenesis of post-infectious PAS in the context of environmental exposure and genetic susceptibility in a cohort of US travelers to Mexico. Our objective was to identify infectious, genetic and environmental factors that predispose to post infectious PAS. ^ Methods. This is a secondary data analysis of a prospective study on a cohort of 704 healthy North American tourists to Cuernavaca, Morelos and Guadalajara, Jalisco in Mexico. The subjects at risk for Travelers' diarrhea were assessed for chronic abdominal symptoms on enrollment and six months after the return to the US. ^ Outcomes. PAS was defined as disturbances of mid and lower gastrointestinal system without any known pathological or radiological abnormalities, or infectious, or metabolic causes. It refers to functional bowel disease, category C of functional gastrointestinal diseases as defined by the Rome II criterion. PAS was sub classified into Irritable bowel syndrome (IBS) and functional abdominal disease (FAD). ^ IBS is defined as recurrent abdominal pain or discomfort present at least 25% and associated with improvement with defecation, change in frequency and form of stool. FAD encompasses other abdominal symptoms of chronic nature that do not meet the criteria for IBS. It includes functional diarrhea, functional constipation, functional bloating: and unspecified bowel symptoms. ^ Results. Among the 704 travelers studied, there were 202 cases of PAS. The PAS cases included 175 cases of FAD and 27 cases of IBS. PAS was more frequent among subjects who developed traveler's diarrhea in Mexico compared to travelers who remained healthy during the short term visit to Mexico (52 vs. 38; OR = 1.8; CI, 1.3–2.5, P < 0.001). A statistically significant difference was noted in the mean age of subjects with PAS compared to healthy controls (28 vs. 34 yrs; OR = 0.97, CI, 0.95–0.98; P < 0.001). Travelers who experienced multiple episodes, a later onset of diarrhea in Mexico and passed greater numbers of unformed stools were more likely to be identified in PAS group at six months. Participants who developed TD caused by enterotoxigenic E.coli in Mexico showed a 2.6 times higher risk of developing FAD (P = 0.003). Infection with Providencia ssp. also demonstrated a greater risk to developing PAS. Subjects who sought treatment for diarrhea while in Mexico also displayed a significantly lower frequency of IBS at six months follow up (OR = 0.30; CI, 0.10–0.80; P = 0.02). ^ Forty six SNPs belonging to 14 genes were studied. Seven SNPs were associated with PAS at 6 months. These included four SNPs from the Caspase Recruitment Domain-Containing Protein 15 gene (CARD15), two SNPs from Surfactant Pulmonary-Associated Protein D gene (SFTPD) and one from Decay-Accelerating Factor For Complement gene (CD55). A genetic risk score (GRS) was composed based on the 7 SNPs that showed significant association with PAS. A 20% greater risk for PAS was noted for every unit increase in GRS. The risk increased by 30% for IBS. The mean GRS was high for IBS (2.2) and PAS (1.1) compared to healthy controls (0.51). These data suggests a role for these genetic polymorphisms in defining the susceptibility to PAS. ^ Conclusions. The study allows us to identify individuals at risk for developing post infectious IBS (PI-IBS) and persisting abdominal symptoms after an episode of TD. The observations in this study will be of use in developing measures to prevent and treat post-infectious irritable bowel syndrome among travelers including pre-travel counseling, the use of vaccines, antibiotic prophylaxis or the initiation of early antimicrobial therapy. This study also provides insights into the pathogenesis of post infectious PAS and IBS. (Abstract shortened by UMI.)^

The information bottleneck method for genome-wide association studies

In population studies, most current methods focus on identifying one outcome-related SNP at a time by testing for differences of genotype frequencies between disease and healthy groups or among different population groups. However, testing a great number of SNPs simultaneously has a problem of multiple testing and will give false-positive results. Although, this problem can be effectively dealt with through several approaches such as Bonferroni correction, permutation testing and false discovery rates, patterns of the joint effects by several genes, each with weak effect, might not be able to be determined. With the availability of high-throughput genotyping technology, searching for multiple scattered SNPs over the whole genome and modeling their joint effect on the target variable has become possible. Exhaustive search of all SNP subsets is computationally infeasible for millions of SNPs in a genome-wide study. Several effective feature selection methods combined with classification functions have been proposed to search for an optimal SNP subset among big data sets where the number of feature SNPs far exceeds the number of observations. ^ In this study, we take two steps to achieve the goal. First we selected 1000 SNPs through an effective filter method and then we performed a feature selection wrapped around a classifier to identify an optimal SNP subset for predicting disease. And also we developed a novel classification method-sequential information bottleneck method wrapped inside different search algorithms to identify an optimal subset of SNPs for classifying the outcome variable. This new method was compared with the classical linear discriminant analysis in terms of classification performance. Finally, we performed chi-square test to look at the relationship between each SNP and disease from another point of view. ^ In general, our results show that filtering features using harmononic mean of sensitivity and specificity(HMSS) through linear discriminant analysis (LDA) is better than using LDA training accuracy or mutual information in our study. Our results also demonstrate that exhaustive search of a small subset with one SNP, two SNPs or 3 SNP subset based on best 100 composite 2-SNPs can find an optimal subset and further inclusion of more SNPs through heuristic algorithm doesn't always increase the performance of SNP subsets. Although sequential forward floating selection can be applied to prevent from the nesting effect of forward selection, it does not always out-perform the latter due to overfitting from observing more complex subset states. ^ Our results also indicate that HMSS as a criterion to evaluate the classification ability of a function can be used in imbalanced data without modifying the original dataset as against classification accuracy. Our four studies suggest that Sequential Information Bottleneck(sIB), a new unsupervised technique, can be adopted to predict the outcome and its ability to detect the target status is superior to the traditional LDA in the study. ^ From our results we can see that the best test probability-HMSS for predicting CVD, stroke,CAD and psoriasis through sIB is 0.59406, 0.641815, 0.645315 and 0.678658, respectively. In terms of group prediction accuracy, the highest test accuracy of sIB for diagnosing a normal status among controls can reach 0.708999, 0.863216, 0.639918 and 0.850275 respectively in the four studies if the test accuracy among cases is required to be not less than 0.4. On the other hand, the highest test accuracy of sIB for diagnosing a disease among cases can reach 0.748644, 0.789916, 0.705701 and 0.749436 respectively in the four studies if the test accuracy among controls is required to be at least 0.4. ^ A further genome-wide association study through Chi square test shows that there are no significant SNPs detected at the cut-off level 9.09451E-08 in the Framingham heart study of CVD. Study results in WTCCC can only detect two significant SNPs that are associated with CAD. In the genome-wide study of psoriasis most of top 20 SNP markers with impressive classification accuracy are also significantly associated with the disease through chi-square test at the cut-off value 1.11E-07. ^ Although our classification methods can achieve high accuracy in the study, complete descriptions of those classification results(95% confidence interval or statistical test of differences) require more cost-effective methods or efficient computing system, both of which can't be accomplished currently in our genome-wide study. We should also note that the purpose of this study is to identify subsets of SNPs with high prediction ability and those SNPs with good discriminant power are not necessary to be causal markers for the disease.^

Micro RNA expression alterations in patients with glioblastoma

Glioblastoma, also known as glioblastoma multiform or GBM, is the most common and most malignant primary brain tumor. The clinical history of patients with glioblastoma is short, usually less than 3 months in more than 50% of cases after diagnosis. Currently, the methods of glioblastoma treatment are chemotherapy, radiotherapy and surgery. Even with the more effective treatment options, patients with glioblastoma most likely have a median survival time of 10 to 12 months. It is necessary to seek other treatment methods, including gene-targeted treatment. The success of gene-targeted treatment depends critically on the knowledge of genes that may be the cause of, or contribute to disease. To establish a correlate between glioblastoma survival timeline and micro RNA expression alteration, a study of 91 glioblastoma patients was conducted at the University of Texas M. D. Anderson Cancer Center. These 91 glioblastoma patients were newly diagnosed from 2002 to 2007. Statistical analysis was conducted to test the association of miRNA expression alteration between long-term survival and short-term survival glioblastoma. The completion of this proposed study will provide a better understanding of the regulatory role of miRNA in glioblastoma progression.^

Performance evaluation in Bayesian adaptive randomization

Bayesian adaptive randomization (BAR) is an attractive approach to allocate more patients to the putatively superior arm based on the interim data while maintains good statistical properties attributed to randomization. Under this approach, patients are adaptively assigned to a treatment group based on the probability that the treatment is better. The basic randomization scheme can be modified by introducing a tuning parameter, replacing the posterior estimated response probability, setting a boundary to randomization probabilities. Under randomization settings comprised of the above modifications, operating characteristics, including type I error, power, sample size, imbalance of sample size, interim success rate, and overall success rate, were evaluated through simulation. All randomization settings have low and comparable type I errors. Increasing tuning parameter decreases power, but increases imbalance of sample size and interim success rate. Compared with settings using the posterior probability, settings using the estimated response rates have higher power and overall success rate, but less imbalance of sample size and lower interim success rate. Bounded settings have higher power but less imbalance of sample size than unbounded settings. All settings have better performance in the Bayesian design than in the frequentist design. This simulation study provided practical guidance on the choice of how to implement the adaptive design. ^

Gastric cancer survival amongst Hispanics- A Hispanic paradox? A case series study using the SEER 1973--2005 data registry

Stomach cancer is the fourth most common cancer in the world, and ranked 16th in the US in 2008. The age-adjusted rates among Hispanics were 2.8 times that of non-Hispanic Whites in 1998-2002. In spite of that, previous research has found that Hispanics with non-cardia adenocarcinoma of the stomach have a slightly better survival than non-Hispanic Whites. However, such previous research did not include a comparison with African-Americans, and it was limited to data released for the years 1973-2000 in the nine original Surveillance, Epidemiology, and End Results Cancer Registries. This finding was interpreted as related to the Hispanic Paradox, a phenomenon that refers to the fact that Hispanics in the USA tend to paradoxically have substantially better health than other ethnic groups in spite of what their aggregate socio-economic indicators would predict. We extended such research to the SEER 17 Registry, 1973-2005, with varying years of diagnosis per registry, and compared the survival of non-cardia adenocarcinoma of the stomach according to ethnicity (Hispanics, non-Hispanic Whites and African-Americans), while controlling for age, gender, marital status, stage of disease and treatment using Cox regression survival analysis. We found that Hispanic ethnicity by itself did not confer an advantage on survival from non-cardia adenocarcinoma of the stomach, but that being born abroad was independently associated with the apparent 'Hispanic Paradox' previously reported, and that such advantage was seen among foreign born persons across all race/ethnic groups.^

Genome-wide gene-gene interaction analysis for cardiovascular disease

Numerous studies have been carried out to try to better understand the genetic predisposition for cardiovascular disease. Although it is widely believed that multifactorial diseases such as cardiovascular disease is the result from effects of many genes which working alone or interact with other genes, most genetic studies have been focused on identifying of cardiovascular disease susceptibility genes and usually ignore the effects of gene-gene interactions in the analysis. The current study applies a novel linkage disequilibrium based statistic for testing interactions between two linked loci using data from a genome-wide study of cardiovascular disease. A total of 53,394 single nucleotide polymorphisms (SNPs) are tested for pair-wise interactions, and 8,644 interactions are found to be significant with p-values less than 3.5×10-11. Results indicate that known cardiovascular disease susceptibility genes tend not to have many significantly interactions. One SNP in the CACNG1 (calcium channel, voltage-dependent, gamma subunit 1) gene and one SNP in the IL3RA (interleukin 3 receptor, alpha) gene are found to have the most significant pair-wise interactions. Findings from the current study should be replicated in other independent cohort to eliminate potential false positive results.^

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.^

A multivariate frailty model for disease recurrences and survival

A multivariate frailty hazard model is developed for joint-modeling of three correlated time-to-event outcomes: (1) local recurrence, (2) distant recurrence, and (3) overall survival. The term frailty is introduced to model population heterogeneity. The dependence is modeled by conditioning on a shared frailty that is included in the three hazard functions. Independent variables can be included in the model as covariates. The Markov chain Monte Carlo methods are used to estimate the posterior distributions of model parameters. The algorithm used in present application is the hybrid Metropolis-Hastings algorithm, which simultaneously updates all parameters with evaluations of gradient of log posterior density. The performance of this approach is examined based on simulation studies using Exponential and Weibull distributions. We apply the proposed methods to a study of patients with soft tissue sarcoma, which motivated this research. Our results indicate that patients with chemotherapy had better overall survival with hazard ratio of 0.242 (95% CI: 0.094 - 0.564) and lower risk of distant recurrence with hazard ratio of 0.636 (95% CI: 0.487 - 0.860), but not significantly better in local recurrence with hazard ratio of 0.799 (95% CI: 0.575 - 1.054). The advantages and limitations of the proposed models, and future research directions are discussed. ^

Ethnic differences in tumor characteristics, treatment and survival in glioma patients

Purpose. A descriptive analysis of glioma patients by race was carried out in order to better elucidate potential differences between races in demographics, treatment, characteristics, prognosis and survival. ^ Patients and Methods. Among 1,967 patients ≥ 18 years diagnosed with glioma seen between July 2000 and September 2006 at The University of Texas M.D. Anderson Cancer Center (UTMDACC). Data were collated from the UTMDACC Patient History Database (PHDB) and the UTMDACC Tumor Registry Database (TRDB). Chi-square analysis, uni- /multivariate Cox proportional hazards modeling and survival analysis were used to analyze differences by race. ^ Results. Demographic, treatment and histologic differences exist between races. Though risk differences were seen between races, race was not found to be a significant predictor in multivariate regression analysis after accounting for age, surgery, chemotherapy, radiation, tumor type as stratified by WHO tumor grade. Age was the most consistent predictor in risk for death. Overall survival by race was significantly different (p=0.0049) only in low-grade gliomas after adjustment for age although survival differences were very slight. ^ Conclusion. Among this cohort of glioma patients, age was the strongest predictor for survival. It is likely that survival is more influenced by age, time to treatment, tumor grade and surgical expertise rather than racial differences. However, age at diagnosis, gender ratios, histology and history of cancer differed significantly between race and genetic differences to this effect cannot be excluded. ^

Involvement of lipocalin 2 in leukemia and breast cancer

Human lipocalin 2 is described as the neutrophil gelatinase-associated lipocalin (NGAL). The lipocalin 2 gene encodes a small, secreted glycoprotein that possesses a variety of functions, of which the best characterized function is organic iron binding activity. Elevated NGAL expression has been observed in many human cancers including breast, colorectal, pancreatic and ovarian cancers. I focused on the characterization of NGAL function in chronic myelogenous leukemia (CML) and breast cancer. Using the leukemic xenograft mouse model, we demonstrated that over-expression of NGAL in K562 cells, a leukemic cell line, led to a higher apoptotic rate and an atrophy phenotype in the spleen of inoculated mice compared to K562 cells alone. These results indicate that NGAL plays a primary role in suppressing hematopoiesis by inducing apoptosis within normal hematopoietic cells. In the breast cancer project, we analyzed two microarray data sets of breast cancer cell lines ( n = 54) and primary breast cancer samples (n = 318), and demonstrated that high NGAL expression is significantly correlated with several tumor characteristics, including negative estrogen receptor (ER) status, positive HER2 status, high tumor grade, and lymph node metastasis. Ectopic NGAL expression in non-aggressive (ZR75.1 and MCF7) cells led to aggressive tumor phenotypes in vitro and in vivo. Conversely, knockdown of NGAL expression in various breast cancer cell lines by shRNA lentiviral infection significantly decreased migration, invasion, and metastasis activities of tumor cells both in vitro and in vivo . It has been previously reported that transgenic mice with a mutation in the region of trans-membrane domain (V664E) of HER2 develop mammary tumors that progress to lung metastasis. However, we observed that genetic deletion of the 24p3 gene, a mouse homolog of NGAL, in HER2 transgenic mice by breeding with 24p3-null mice resulted in a significant delay of mammary tumor formation and reduction of lung metastasis. Strikingly, we also found that treatment with affinity purified 24p3 antibodies in the 4T1 breast cancer mice strongly reduced lung metastasis. Our studies provide evidence that NGAL plays a critical role in breast cancer development and progression, and thus NGAL has potential as a new therapeutic target in breast cancer.^

Systematic review of genetic risk score in coronary heart disease and other diseases

In order to better take advantage of the abundant results from large-scale genomic association studies, investigators are turning to a genetic risk score (GRS) method in order to combine the information from common modest-effect risk alleles into an efficient risk assessment statistic. The statistical properties of these GRSs are poorly understood. As a first step toward a better understanding of GRSs, a systematic analysis of recent investigations using a GRS was undertaken. GRS studies were searched in the areas of coronary heart disease (CHD), cancer, and other common diseases using bibliographic databases and by hand-searching reference lists and journals. Twenty-one independent case-control studies, cohort studies, and simulation studies (12 in CHD, 9 in other diseases) were identified. The underlying statistical assumptions of the GRS using the experience of the Framingham risk score were investigated. Improvements in the construction of a GRS guided by the concept of composite indicators are discussed. The GRS will be a promising risk assessment tool to improve prediction and diagnosis of common diseases.^

Variance of familial dietary intake

Although many family-based genetic studies have collected dietary data, very few have used the dietary information in published findings. No single solution has been presented or discussed in the literature to deal with the problem of using factor analyses for the analyses of dietary data from several related individuals from a given household. The standard statistical approach of factor analysis cannot be applied to the VIVA LA FAMILIA Study diet data to ascertain dietary patterns since this population consists of three children from each family, thus the dietary patterns of the related children may be correlated and non-independent. Addressing this problem in this project will enable us to describe the dietary patterns in Hispanic families and to explore the relationships between dietary patterns and childhood obesity. ^ In the VIVA LA FAMILIA Study, an overweight child was first identified and then his/her siblings and parents were brought in for data collection which included 24 hour recalls and food frequency questionnaire (FFQ). Dietary intake data were collected using FFQ and 24 hour recalls on 1030 Hispanic children from 319 families. ^ The design of the VIVA LA FAMILIA Study has important and unique statistical considerations since its participants are related to each other, the majority form distinct nuclear families. Thus, the standard approach of factor analysis cannot be applied to these diet data to ascertain dietary patterns. In this project we propose to investigate whether the determinants of the correlation matrix of each family unit will allow us to adjust the original correlation matrix of the dietary intake data prior to ascertaining dietary intake patterns. If these methods are appropriate, then in the future the dietary patterns among related individuals could be assessed by standard orthogonal principal component factor analysis.^

The combined effect of pravastatin and aspirin on clinical cardiovascular events

The 3-hydroxy-3methylglutaryl coenzyme A (HMG-CoA) reductase inhibitors, or statins, can achieve significant reductions in plasma low-density lipoprotein (LDL)-cholesterol levels. Experimental and clinical evidence now shows that some statins interfere with formation of atherosclerotic lesions independent of their hypolipidemic properties. Vulnerable plaque rupture can result in thrombus formation and artery occlusion; this plaque deterioration is responsible for most acute coronary syndromes, including myocardial infarction (MI), unstable angina, and coronary death, as well as coronary heart diseaseequivalent non-hemorrhagic stroke. Inhibition of HMG-CoA reductase has potential pleiotropic effects other than lipid-lowering, as statins block mevalonic acid production, a precursor to cholesterol and numerous other metabolites. Statins' beneficial effects on clinical events may also thus involve nonlipid-related mechanisms that modify endothelial function, inflammatory responses, plaque stability, and thrombus formation. Aspirin, routinely prescribed to post-MI patients as adjunct therapy, may potentiate statins beneficial effects, as aspirin does not compete metabolically with statins but acts similarly on atherosclerotic lesions. Common functions of both medications include inhibition of platelet activity and aggregation, reduction in atherosclerotic plaque macrophage cell count, and prevention of atherosclerotic vessel endothelial dysfunction. The Cholesterol and Recurrent Events (CARE) trial provides an ideal population in which to examine the combined effects of pravastatin and aspirin. Lipid levels, intermediate outcomes, are examined by pravastatin and aspirin status, and differences between the two pravastatin groups are found. A modified Cox proportional-hazards model with aspirin as a time-dependent covariate was used to determine the effect of aspirin and pravastatin on the clinical cardiovascular composite endpoint of coronary heart disease death, recurrent MI or stroke. Among those assigned to pravastatin, use of aspirin reduced the composite primary endpoint by 35%; this result was similar by gender, race, and diabetic status. Older patients demonstrated a nonsignificant 21% reduction in the primary outcome, whereas the younger had a significant reduction of 43% in the composite primary outcome. Secondary outcomes examined include coronary artery bypass graft (38% reduction), nonsurgical bypass, peripheral vascular disease, and unstable angina. Pravastatin and aspirin in a post-MI population was found to be a beneficial combination that seems to work through lipid and nonlipid, anti-inflammatory mechanisms. ^