What Can We Learn About Drug Safety and Other Effects in the Era of Electronic Health Records and Big Data That We Would Not Be Able to Learn From Classic Epidemiology?

As more and more health systems have converted to the use of electronic health records, the amount of searchable and analyzable data is exploding. This includes not just provider or laboratory created data but also data collected by instruments, personal devices, and patients themselves, among others. This has led to more attention being paid to the analysis of these data to answer previously unaddressed questions. This is especially important given the number of therapies previously found to be beneficial in clinical trials that are currently being re-scrutinized. Because there are orders of magnitude more information contained in these data sets, a fundamentally different approach needs to be taken to their processing and analysis and the generation of knowledge. Health care and medicine are drivers of this phenomenon and will ultimately be the main beneficiaries. Concurrently, many different types of questions can now be asked using these data sets. Research groups have become increasingly active in mining large data sets, including nationwide health care databases, to learn about associations of medication use and various unrelated diseases such as cancer. Given the recent increase in research activity in this area, its promise to radically change clinical research, and the relative lack of widespread knowledge about its potential and advances, we surveyed the available literature to understand the strengths and limitations of these new tools. We also outline new databases and techniques that are available to researchers worldwide, with special focus on work pertaining to the broad and rapid monitoring of drug safety and secondary effects.

Genetic variants in one-carbon metabolism genes and breast cancer risk in European American and African American women.

Folate-mediated one-carbon metabolism plays critical roles in DNA synthesis, repair and DNA methylation. The impact of single nucleotide polymorphisms (SNPs) in folate-metabolizing enzymes has been investigated in risk of breast cancer among European or Asian populations, but not among women of African ancestry. We conducted a comprehensive analysis of SNPs in eleven genes involved in one-carbon metabolism and risk of breast cancer in 1,275 European-American (EA) and 1,299 African-American (AA) women who participated in the Women's Circle of Health Study. Allele frequencies varied significantly between EA and AA populations. A number of these SNPs, specifically in genes including MTR, MTRR, SHMT1, TYMS and SLC19A1, were associated with overall breast cancer risk, as well as risk by estrogen receptor (ER) status, in either EA or AA women. Associations appeared to be modified by dietary folate intake. Although single-SNP associations were not statistically significant after correcting for multiple comparisons, polygenetic score analyses revealed significant associations with breast cancer risk. Per unit increase of the risk score was associated with a modest 19 to 50% increase in risk of breast cancer overall, ER positive or ER negative cancer (all p < 0.0005) in EAs or AAs. In summary, our data suggest that one-carbon metabolizing gene polymorphisms could play a role in breast cancer and that may differ between EA and AA women.

Is high serum uric acid a risk marker or a target for treatment? Examination of its independent effect in a large cohort with low cardiovascular risk.

BACKGROUND: Cohort studies evaluating increased uric acid level as a cardiovascular disease (CVD) risk factor have shown variable results; studies are particularly lacking in lower risk populations. STUDY DESIGN: Prospective cohort study. SETTING & PARTICIPANTS: 484,568 adults participating in a medical screening program in Taiwan since 1994 were followed up for a median of 8.5 years. Two subgroups were constructed: the first (n = 246,697; 51%) excluded participants with either overt CVD or overt CVD risk factors (including hypertension, diabetes, obesity, and hypertriglyceridemia) and the second (n = 157,238; 32%) further excluded individuals with early-stage CVD risk factors (including prehypertension, prediabetes, overweight, and borderline hypertriglyceridemia). PREDICTOR: Serum uric acid. OUTCOMES & MEASUREMENTS: All-cause and CVD mortality risk assessed using Cox proportional hazards models for categorical and continuous serum uric acid levels. As applicable, models adjusted for 14 variables. Population-attributable fraction was applied to compare contributions to mortality between high uric acid level and other CVD risk factors. RESULTS: In the total cohort, mean age was 41.4 +/- 14.0 years and 26.2% had serum uric acid levels >or=7 mg/dL. Through 2007, there were 16,246 deaths (3.4% of all participants), with 35.2% of deaths occurring in individuals with hyperuricemia. Adjusted HRs associated with serum uric acid levels >or=7 mg/dL for all-cause and CVD mortality were 1.10 (95% CI, 1.04-1.17) and 1.38 (95% CI, 1.20-1.58), respectively. In individuals with hyperuricemia, 64.3% had overt CVD risk factors and 82.5% had either overt or early-stage CVD risk factors. Individuals with serum uric acid levels >or=8 mg/dL without overt CVD risk factors constituted 13.5% of the total study population with hyperuricemia; in analyses excluding those with overt CVD risk factors, serum uric acid level >or=8 mg/dL was significantly associated with all-cause and CVD mortality, with HRs of 1.37 (95% CI, 1.18-1.60) and 2.30 (95% CI, 1.51-3.49), respectively. In the subgroup of those with serum uric acid levels >or=8 mg/dL but who lacked both overt and early-stage CVD risk factors, the HRs for all-cause and CVD mortality were also significant and were 1.39 (95% CI, 1.08-1.78) and 2.38 (95% CI, 1.24-4.54), respectively. HRs for individuals with the same risk profiles but with serum uric acid of 7.0-7.9 mg/dL were not significant. In all groups, inclusion of proteinuria and glomerular filtration rate in models substantially attenuated the association between uric acid level and outcomes. High uric acid levels contributed a relatively insignificant portion to mortality (1.2%) and CVD deaths (4.5%) in this population. LIMITATIONS: A single measurement of uric acid was used. CONCLUSION: Increased serum uric acid level is a minor, but significant, risk factor for all-cause and CVD mortality. However, except for a small proportion (13.5%), increased serum uric acid level is more a risk marker than a target for treatment and is not an independent risk. Determining appropriate groups to target in clinical trials for uric acid-lowering therapy is critical.

Are Asians at greater mortality risks for being overweight than Caucasians? Redefining obesity for Asians.

OBJECTIVES: To assess whether overweight Asians, assessed on the basis of WHO criteria, are at greater mortality risk than overweight Caucasians, and to determine whether alternative cut-off points (BMI = 23.0-24.9 kg/m2 for overweight and BMI >or= 25.0 kg/m2 for obesity) suggested by the WHO Western Pacific Regional Office are appropriate. DESIGN: The cohort was followed prospectively until the end of 2001. All-cause and CVD mortality risks of the overweight and obese group, relative to the reference group (BMI = 18.5-24.9 or 18.5-22.9 kg/m2), were assessed using Cox regression analysis, adjusting for age, smoking and gender. Excess deaths were estimated with a method proposed by the US Centers for Disease Control and Prevention. SETTING: National Health Interview Survey (NHIS 2001) and a middle-aged perspective cohort in Taiwan. SUBJECTS: Subjects comprised 36 386 civil servants and school teachers, aged 40 years and older, who underwent a medical examination during 1989-1992. RESULTS: In the WHO-defined overweight group, Asians showed a significant increase in all-cause mortality risk compared with Caucasians. Asians showed risks equivalent to Caucasians' at lower BMI (around 5 units). Every unit of BMI increase, at 25.0 kg/m2 or above, was associated with a 9 % increase in relative mortality risk from all causes. Applying a cut-off point of 25.0 kg/m2 for obesity would result a prevalence of 27.1 %, while the traditional WHO cut-off point of 30.0 kg/m2 yielded obesity prevalence of 4.1 %. Excess deaths due to obesity accounted for 8.6 % of all deaths and 21.1 % of CVD deaths, based on the alternative cut-offs. CONCLUSIONS: In this Asian population, significant mortality risks started at BMI >or= 25.0 kg/m2, rather than at BMI >or= 30.0 kg/m2. The study supports the use of BMI >or= 25.0 kg/m2 as a new cut-off point for obesity and BMI = 23.0-24.9 kg/m2 for overweight. The magnitude of obesity-attributable deaths has been hitherto under-appreciated among Asians.