Longitudinal assessment of colonoscopy adverse events in the prospective Cooperative Studies Program no. 380 colorectal cancer screening and surveillance cohort.

BACKGROUND AND AIMS: Data are limited regarding colonoscopy risk during long-term, programmatic colorectal cancer screening and follow-up. We aimed to describe adverse events during follow-up in a colonoscopy screening program after the baseline examination and examine factors associated with increased risk. METHODS: Cooperative Studies Program no. 380 includes 3121 asymptomatic veterans aged 50 to 75 years who underwent screening colonoscopy between 1994 and 1997. Periprocedure adverse events requiring significant intervention were defined as major events (other events were minor) and were tracked during follow-up for at least 10 years. Multivariable odds ratios (ORs) were calculated for factors associated with risk of follow-up adverse events. RESULTS: Of 3727 follow-up examinations in 1983 participants, adverse events occurred in 105 examinations (2.8%) in 93 individuals, including 22 major and 87 minor events (examinations may have had >1 event). Incidence of major events (per 1000 examinations) remained relatively stable over time, with 6.1 events at examination 2, 4.8 at examination 3, and 7.2 at examination 4. Examinations with major events included 1 perforation, 3 GI bleeds requiring intervention, and 17 cardiopulmonary events. History of prior colonoscopic adverse events was associated with increased risk of events (major or minor) during follow-up (OR, 2.7; 95% confidence interval, 1.6-4.6). CONCLUSIONS: Long-term programmatic screening and surveillance was safe, as major events were rare during follow-up. However, serious cardiopulmonary events were the most common major events. These results highlight the need for detailed assessments of comorbid conditions during routine clinical practice, which could help inform individual decisions regarding the utility of ongoing colonoscopy follow-up.

Advanced neoplasia in Veterans at screening colonoscopy using the National Cancer Institute Risk Assessment Tool.

BACKGROUND: Adapting screening strategy to colorectal cancer (CRC) risk may improve efficiency for all stakeholders however limited tools for such risk stratification exist. Colorectal cancers usually evolve from advanced neoplasms that are present for years. We applied the National Cancer Institute (NCI) CRC Risk Assessment Tool, which calculates future risk of CRC, to determine whether it could be used to predict current advanced neoplasia (AN) in a veteran cohort undergoing a baseline screening colonoscopy. METHODS: This was a prospective assessment of the relationship between future CRC risk predicted by the NCI tool, and the presence of AN at screening colonoscopy. Family, medical, dietary and physical activity histories were collected at the time of screening colonoscopy and used to calculate absolute CRC risk at 5, 10 and 20 years. Discriminatory accuracy was assessed. RESULTS: Of 3121 veterans undergoing screening colonoscopy, 94% had complete data available to calculate risk (N = 2934, median age 63 years, 100% men, and 15% minorities). Prevalence of AN at baseline screening colonoscopy was 11 % (N = 313). For tertiles of estimated absolute CRC risk at 5 years, AN prevalences were 6.54% (95% CI, 4.99, 8.09), 11.26% (95% CI, 9.28-13.24), and 14.21% (95% CI, 12.02-16.40). For tertiles of estimated risk at 10 years, the prevalences were 6.34% (95% CI, 4.81-7.87), 11.25% (95% CI, 9.27-13.23), and 14.42% (95% CI, 12.22-16.62). For tertiles of estimated absolute CRC risk at 20 years, current AN prevalences were 7.54% (95% CI, 5.75-9.33), 10.53% (95% CI, 8.45-12.61), and 12.44% (95% CI, 10.2-14.68). The area under the curve for predicting current AN was 0.60 (95% CI; 0.57-0.63, p < 0.0001) at 5 years, 0.60 (95% CI, 0.57-0.63, p < 0.0001) at 10 years and 0.58 (95% CI, 0.54-0.61, p < 0.0001) at 20 years. CONCLUSION: The NCI tool had modest discriminatory function for estimating the presence of current advanced neoplasia in veterans undergoing a first screening colonoscopy. These findings are comparable to other clinically utilized cancer risk prediction models and may be used to inform the benefit-risk assessment of screening, particularly for patients with competing comorbidities and lower risk, for whom a non-invasive screening approach is preferred.

Systolic Blood Pressure and Socioeconomic Status in a large multi-study population.

The present study used harmonized data from eight studies (N = 28,891) to examine the association between socioeconomic status (SES) and resting systolic blood pressure (SBP). The study replicates and extends our prior work on this topic by examining potential moderation of this association by race and gender. We also examined the extent to which body mass index (BMI), waist circumference (WC), and smoking might explain the association between SES and SBP. Data were available from six race/gender groups: 9200 Black women; 2337 Black men; 7248 White women; 6519 White men; 2950 Hispanic women; and 637 Hispanic men. Multivariable regression models showed that greater annual household income was associated with lower SBP in all groups except Hispanic men. The magnitude and form of this negative association differed across groups, with White women showing the strongest linear negative association. Among Black men and Hispanic women, the association was curvilinear: relatively flat among lower income levels, but then negative among higher income ranges. Education also was independently, negatively related to SBP, though evidence was weaker for race and gender differences in the strength of the association. Higher BMI and WC were associated with higher SBP, and current smoking with lower SBP. Inclusion of these risk factors resulted in only a modest change in the magnitude of the SBP and SES relation, accounting on average about 0.4 mmHg of the effect of income and 0.2 mmHg of the effect of education-effects unlikely to be clinically significant. Further understanding of mechanisms underlying the association between SBP and SES may improve risk stratification in clinical settings and potentially inform interventions aimed at reductions in social disparities in health.

The Gulf War Era Cohort and Biorepository: A Longitudinal Research Resource of Veterans of the 1990-1991 Gulf War Era.

The US Department of Veterans Affairs (VA) Gulf War Era Cohort and Biorepository (GWECB) is a nationally representative longitudinal cohort of US veterans who served during the 1990-1991 Gulf War era. The GWECB combines survey data, such as demographic, health behavior, and environmental exposure data; medical records; and a linked biorepository of blood specimens that can support a broad range of future research regarding health concerns unique to veterans of this era. To build this resource, the VA Cooperative Studies Program initiated a pilot study (2014-2016) to establish the GWECB and evaluate the processes required to build and maintain the resource. Participants (n = 1,275) consented to future sharing of their data and biospecimens for research purposes. Here we describe the pilot study, including recruitment and enrollment procedures, data collection and management, quality control, and challenges experienced. The GWECB data available to investigators under approved sharing mechanisms and the procedures for accessing them are extensively detailed. The study's consenting documents and a website link for the research survey are provided. Our hope is that new research drawing on the GWECB data and biospecimens will result in effective treatments and improved approaches to address the health concerns of Gulf War-era veterans.

Fine particulate matter and cardiovascular disease: Comparison of assessment methods for long-term exposure.

BACKGROUND: Adverse cardiovascular events have been linked with PM2.5 exposure obtained primarily from air quality monitors, which rarely co-locate with participant residences. Modeled PM2.5 predictions at finer resolution may more accurately predict residential exposure; however few studies have compared results across different exposure assessment methods. METHODS: We utilized a cohort of 5679 patients who had undergone a cardiac catheterization between 2002-2009 and resided in NC. Exposure to PM2.5 for the year prior to catheterization was estimated using data from air quality monitors (AQS), Community Multiscale Air Quality (CMAQ) fused models at the census tract and 12km spatial resolutions, and satellite-based models at 10km and 1km resolutions. Case status was either a coronary artery disease (CAD) index >23 or a recent myocardial infarction (MI). Logistic regression was used to model odds of having CAD or an MI with each 1-unit (µg/m3) increase in PM2.5, adjusting for sex, race, smoking status, socioeconomic status, and urban/rural status. RESULTS: We found that the elevated odds for CAD>23 and MI were nearly equivalent for all exposure assessment methods. One difference was that data from AQS and the census tract CMAQ showed a rural/urban difference in relative risk, which was not apparent with the satellite or 12km-CMAQ models. CONCLUSIONS: Long-term air pollution exposure was associated with coronary artery disease for both modeled and monitored data.

A novel approach for measuring residential socioeconomic factors associated with cardiovascular and metabolic health.

Individual-level characteristics, including socioeconomic status, have been associated with poor metabolic and cardiovascular health; however, residential area-level characteristics may also independently contribute to health status. In the current study, we used hierarchical clustering to aggregate 444 US Census block groups in Durham, Orange, and Wake Counties, NC, USA into six homogeneous clusters of similar characteristics based on 12 demographic factors. We assigned 2254 cardiac catheterization patients to these clusters based on residence at first catheterization. After controlling for individual age, sex, smoking status, and race, there were elevated odds of patients being obese (odds ratio (OR)=1.92, 95% confidence intervals (CI)=1.39, 2.67), and having diabetes (OR=2.19, 95% CI=1.57, 3.04), congestive heart failure (OR=1.99, 95% CI=1.39, 2.83), and hypertension (OR=2.05, 95% CI=1.38, 3.11) in a cluster that was urban, impoverished, and unemployed, compared with a cluster that was urban with a low percentage of people that were impoverished or unemployed. Our findings demonstrate the feasibility of applying hierarchical clustering to an assessment of area-level characteristics and that living in impoverished, urban residential clusters may have an adverse impact on health.

Clinical utility of a Web-enabled risk-assessment and clinical decision support program.

PURPOSE: Risk-stratified guidelines can improve quality of care and cost-effectiveness, but their uptake in primary care has been limited. MeTree, a Web-based, patient-facing risk-assessment and clinical decision support tool, is designed to facilitate uptake of risk-stratified guidelines. METHODS: A hybrid implementation-effectiveness trial of three clinics (two intervention, one control). PARTICIPANTS: consentable nonadopted adults with upcoming appointments. PRIMARY OUTCOME: agreement between patient risk level and risk management for those meeting evidence-based criteria for increased-risk risk-management strategies (increased risk) and those who do not (average risk) before MeTree and after. MEASURES: chart abstraction was used to identify risk management related to colon, breast, and ovarian cancer, hereditary cancer, and thrombosis. RESULTS: Participants = 488, female = 284 (58.2%), white = 411 (85.7%), mean age = 58.7 (SD = 12.3). Agreement between risk management and risk level for all conditions for each participant, except for colon cancer, which was limited to those <50 years of age, was (i) 1.1% (N = 2/174) for the increased-risk group before MeTree and 16.1% (N = 28/174) after and (ii) 99.2% (N = 2,125/2,142) for the average-risk group before MeTree and 99.5% (N = 2,131/2,142) after. Of those receiving increased-risk risk-management strategies at baseline, 10.5% (N = 2/19) met criteria for increased risk. After MeTree, 80.7% (N = 46/57) met criteria. CONCLUSION: MeTree integration into primary care can improve uptake of risk-stratified guidelines and potentially reduce "overuse" and "underuse" of increased-risk services.Genet Med 18 10, 1020-1028.

A Guide for a Cardiovascular Genomics Biorepository: the CATHGEN Experience.

The CATHeterization GENetics (CATHGEN) biorepository was assembled in four phases. First, project start-up began in 2000. Second, between 2001 and 2010, we collected clinical data and biological samples from 9334 individuals undergoing cardiac catheterization. Samples were matched at the individual level to clinical data collected at the time of catheterization and stored in the Duke Databank for Cardiovascular Diseases (DDCD). Clinical data included the following: subject demographics (birth date, race, gender, etc.); cardiometabolic history including symptoms; coronary anatomy and cardiac function at catheterization; and fasting chemistry data. Third, as part of the DDCD regular follow-up protocol, yearly evaluations included interim information: vital status (verified via National Death Index search and supplemented by Social Security Death Index search), myocardial infarction (MI), stroke, rehospitalization, coronary revascularization procedures, medication use, and lifestyle habits including smoking. Fourth, samples were used to generate molecular data. CATHGEN offers the opportunity to discover biomarkers and explore mechanisms of cardiovascular disease.

Implementing family health history risk stratification in primary care: impact of guideline criteria on populations and resource demand.

UNLABELLED: The Genomic Medicine Model aims to facilitate patient engagement, patient/provider education of genomics/personalized medicine, and uptake of risk-stratified evidence-based prevention guidelines using MeTree, a patient-facing family health history (FHH) collection and clinical decision support (CDS) program. Here we report the number of increased risk (above population-level risk) patients identified for breast/ovarian cancer, colon cancer, hereditary syndrome risk, and thrombosis; the prevalence of FHH elements triggering increased-risk status; and the resources needed to manage their risk. STUDY DESIGN: hybrid implementation-effectiveness study of adults with upcoming well-visits in 2 primary care practices in Greensboro, NC. PARTICIPANTS: 1,184, mean age = 58.8, female = 58% (N = 694), non-white = 20% (N = 215). Increased Risk: 44% (N = 523). RECOMMENDATIONS: genetic counseling = 26% (N = 308), breast MRI = 0.8% (N = 10), breast chemoprophylaxis = 5% (N = 58), early/frequent colonoscopies = 19% (N = 221), ovarian cancer screening referral = 1% (N = 14), thrombosis testing/counseling = 2.4% (N = 71). FHH elements: 8 FHH elements lead to 37.3% of the increased risk categorizations (by frequency): first-degree-relative (FDR) with polyps age ≥60 (7.1%, N = 85), three relatives with Lynch-related cancers (5.4%, N = 65), FDR with polyps age <60 (5.1%, N = 61), three relatives on same side of family with same cancer (4.9%, N = 59), Gail score ≥1.66% (4.9%, N = 58), two relatives with breast cancer (one ≤age 50) (4.1%, N = 49), one relative with breast cancer ≤age 40 (4.1%, N = 48), FDR with colon cancer age ≥60 (1.7%, N = 20). MeTree identifies a high percentage of individuals in the general primary care population needing non-routine risk management/prevention for the selected conditions. Implementing risk-stratification in primary care will likely increase demand for related-resources, particularly colon screening and GC. Understanding the prevalence of FHH elements helps predict resource needs and may aid in guideline development.

Quality of family history collection with use of a patient facing family history assessment tool.

BACKGROUND: Studies have shown that the quality of family health history (FHH) collection in primary care is inadequate to assess disease risk. To use FHH for risk assessment, collected data must have adequate detail. To address this issue, we developed a patient facing FHH assessment tool, MeTree. In this paper we report the content and quality of the FHH collected using MeTree. DESIGN: A hybrid implementation-effectiveness study. Patients were recruited from 2009 to 2012. SETTING: Two community primary care clinics in Greensboro, NC. PARTICIPANTS: All non-adopted adult English speaking patients with upcoming appointments were invited to participate. INTERVENTION: Education about and collection of FHH with entry into MeTree. MEASURES: We report the proportion of pedigrees that were high-quality. High-quality pedigrees are defined as having all the following criteria: (1) three generations of relatives, (2) relatives' lineage, (3) relatives' gender, (4) an up-to-date FHH, (5) pertinent negatives noted, (6) age of disease onset in affected relatives, and for deceased relatives, (7) the age and (8) cause of death (Prim Care31:479-495, 2004.). RESULTS: Enrollment: 1,184. Participant demographics: age range 18-92 (mean 58.8, SD 11.79), 56% male, and 75% white. The median pedigree size was 21 (range 8-71) and the FHH entered into MeTree resulted in a database of 27,406 individuals. FHHs collected by MeTree were found to be high quality in 99.8% (N = 1,182/1,184) as compared to <4% at baseline. An average of 1.9 relatives per pedigree (range 0-50, SD 4.14) had no data reported. For pedigrees where at least one relative has no data (N = 497/1,184), 4.97 relatives per pedigree (range 1-50, SD 5.44) had no data. Talking with family members before using MeTree significantly decreased the proportion of relatives with no data reported (4.98% if you talked to your relative vs. 10.85% if you did not, p-value < 0.001.). CONCLUSION: Using MeTree improves the quantity and quality of the FHH data that is collected and talking with relatives prior to the collection of FHH significantly improves the quantity and quality of the data provided. This allows more patients to be accurately risk stratified and offered appropriate preventive care guided by their risk level. TRIAL NUMBER: NCT01372553.

Assessment of LD matrix measures for the analysis of biological pathway association.

Complex diseases will have multiple functional sites, and it will be invaluable to understand the cross-locus interaction in terms of linkage disequilibrium (LD) between those sites (epistasis) in addition to the haplotype-LD effects. We investigated the statistical properties of a class of matrix-based statistics to assess this epistasis. These statistical methods include two LD contrast tests (Zaykin et al., 2006) and partial least squares regression (Wang et al., 2008). To estimate Type 1 error rates and power, we simulated multiple two-variant disease models using the SIMLA software package. SIMLA allows for the joint action of up to two disease genes in the simulated data with all possible multiplicative interaction effects between them. Our goal was to detect an interaction between multiple disease-causing variants by means of their linkage disequilibrium (LD) patterns with other markers. We measured the effects of marginal disease effect size, haplotype LD, disease prevalence and minor allele frequency have on cross-locus interaction (epistasis). In the setting of strong allele effects and strong interaction, the correlation between the two disease genes was weak (r=0.2). In a complex system with multiple correlations (both marginal and interaction), it was difficult to determine the source of a significant result. Despite these complications, the partial least squares and modified LD contrast methods maintained adequate power to detect the epistatic effects; however, for many of the analyses we often could not separate interaction from a strong marginal effect. While we did not exhaust the entire parameter space of possible models, we do provide guidance on the effects that population parameters have on cross-locus interaction.