Using Stepwise Pharmacogenomics and Proteomics to Predict Hepatitis C Treatment Response in Difficult to Treat Patient Populations.

PURPOSE: In the interferon era of hepatitis C virus (HCV) therapies, genotype/subtype, cirrhosis, prior treatment failure, sex, and race predicted relapse. Our objective is to validate a targeted proteomics platform of 17 peptides to predict sustained virologic response (SVR). EXPERIMENTAL DESIGN: Stored plasma from three, open-label, trials of HIV/HCV-coinfected subjects receiving interferon-containing regimens is identified. LC-MS/MS is used to quantitate the peptides directly from plasma, and IL28B genotyping is completed using stored peripheral blood mononuclear cells (PBMC). A logistic regression model is built to analyze the probability of SVR using responders and nonresponders to interferon-based regimens. RESULTS: The cohort (N = 35) is predominantly black (51.4%), male (86%), and with median age 48 years. Most patients achieve SVR (54%). Using multivariable models, it is verified that three human corticosteroid binding globulin (CBG) peptides are predictive of SVR in patients with the unfavorable IL28B genotypes (CT/TT). The model performs better than IL28B alone, with an area under the curve of 0.870. CONCLUSIONS AND CLINICAL RELEVANCE: In HIV/HCV-coinfected patients, three human CBG peptides that accurately predict treatment response with interferon-based therapy are identified. This study suggests that a stepwise approach combining a genetic predictor followed by targeted proteomics can improve the accuracy of clinical decision-making.

Potential Cost-effectiveness of Early Identification of Hospital-acquired Infection in Critically Ill Patients.

RATIONALE: Limitations in methods for the rapid diagnosis of hospital-acquired infections often delay initiation of effective antimicrobial therapy. New diagnostic approaches offer potential clinical and cost-related improvements in the management of these infections. OBJECTIVES: We developed a decision modeling framework to assess the potential cost-effectiveness of a rapid biomarker assay to identify hospital-acquired infection in high-risk patients earlier than standard diagnostic testing. METHODS: The framework includes parameters representing rates of infection, rates of delayed appropriate therapy, and impact of delayed therapy on mortality, along with assumptions about diagnostic test characteristics and their impact on delayed therapy and length of stay. Parameter estimates were based on contemporary, published studies and supplemented with data from a four-site, observational, clinical study. Extensive sensitivity analyses were performed. The base-case analysis assumed 17.6% of ventilated patients and 11.2% of nonventilated patients develop hospital-acquired infection and that 28.7% of patients with hospital-acquired infection experience delays in appropriate antibiotic therapy with standard care. We assumed this percentage decreased by 50% (to 14.4%) among patients with true-positive results and increased by 50% (to 43.1%) among patients with false-negative results using a hypothetical biomarker assay. Cost of testing was set at $110/d. MEASUREMENTS AND MAIN RESULTS: In the base-case analysis, among ventilated patients, daily diagnostic testing starting on admission reduced inpatient mortality from 12.3 to 11.9% and increased mean costs by $1,640 per patient, resulting in an incremental cost-effectiveness ratio of $21,389 per life-year saved. Among nonventilated patients, inpatient mortality decreased from 7.3 to 7.1% and costs increased by $1,381 with diagnostic testing. The resulting incremental cost-effectiveness ratio was $42,325 per life-year saved. Threshold analyses revealed the probabilities of developing hospital-acquired infection in ventilated and nonventilated patients could be as low as 8.4 and 9.8%, respectively, to maintain incremental cost-effectiveness ratios less than $50,000 per life-year saved. CONCLUSIONS: Development and use of serial diagnostic testing that reduces the proportion of patients with delays in appropriate antibiotic therapy for hospital-acquired infections could reduce inpatient mortality. The model presented here offers a cost-effectiveness framework for future test development.

Use of a patient-entered family health history tool with decision support in primary care: impact of identification of increased risk patients on genetic counseling attendance.

Several barriers inhibit collection and use of detailed family health history (FHH) in primary care. MeTree, a computer-based FHH intake and risk assessment tool with clinical decision support, was developed to overcome these barriers. Here, we describe the impact of MeTree on genetic counseling (GC) referrals and attendance. Non-adopted, English speaking adults scheduled for a well-visit in two community-based primary-care clinics were invited to participate in an Implementation-Effectiveness study of MeTree. Participants' demographic characteristics and beliefs were assessed at baseline. Immediately after an appointment with a patient for whom GC was recommended, clinicians indicated whether they referred the patient and, if not, why. The study genetic counselor kept a database of patients with a GC recommendation and contacted those with a referral. Of 542 patients completing MeTree, 156 (29 %) received a GC recommendation. Of these, 46 % (n = 72) were referred and 21 % (n = 33) underwent counseling. Patient preferences, additional clinical information unavailable to MeTree, and an incomplete clinician evaluation of the FHH accounted for the 85 patients clinicians chose not to refer. Although MeTree identified a significant proportion of patients for whom GC was recommended, persistent barriers indicate the need for improved referral processes and patient and physician education about the benefits of GC.

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.

Providing patient education: impact on quantity and quality of family health history collection.

BACKGROUND: Family health history (FHH) is an underutilized tool in primary care to identify and risk-stratify individuals with increased cancer risk. OBJECTIVE: Evaluate the influence of patient education on quantity and quality of FHH entered into a primary care-based software program, and impact on the program's cancer risk management recommendations. DESIGN: Two primary care practices within a larger type II hybrid implementation-effectiveness controlled clinical trial. PARTICIPANTS: English speaking non-adopted patients with a well visit appointment December 2012-March 2013. INTERVENTIONS: One to two weeks prior to their well visit appointment, participants entered their FHH into the program. PARTICIPANTS were then provided educational materials describing key FHH components. They were instructed to use the interval to collect additional FHH information. Patients then returned for their scheduled appointment, and updated their FHH with any new information. MAIN MEASURES: Percentage per pedigree of relatives meeting individual quality criteria. Changes made after patient education and changes to recommendations for surveillance, chemoprevention or genetic counseling referral. KEY RESULTS: Post patient education, pedigrees exhibited a greater percentage (per pedigree) of: deceased relatives with age at death (84 vs. 81 % p = 0.02), deceased relatives with cause of death (91 vs. 87 % p = 0.02), relatives with a named health condition (45 vs. 42 % p = 0.002), and a greater percentage of relatives with high quality records (91 vs. 89 % p = 0.02). Of 43 participants with pedigree changes that could trigger changes in risk stratified prevention recommendations, 12 participants (28 %) received such changes. CONCLUSIONS: Patient education improves FHH collection and subsequent risk stratification utilized in providing actionable evidence-based care recommendations for cancer risk management.

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.

Patient and primary care provider experience using a family health history collection, risk stratification, and clinical decision support tool: a type 2 hybrid controlled implementation-effectiveness trial.

BACKGROUND: Family health history (FHH) is the single strongest predictor of disease risk and yet is significantly underutilized in primary care. We developed a patient facing FHH collection tool, MeTree, that uses risk stratification to generate clinical decision support for breast cancer, colorectal cancer, ovarian cancer, hereditary cancer syndromes, and thrombosis. Here we present data on the experience of patients and providers after integration of MeTree into 2 primary care practices. METHODS: This was a Type 2 hybrid controlled implementation-effectiveness study in 3 community-based primary care clinics in Greensboro, NC. All non-adopted adult English speaking patients with upcoming routine appointments were invited. Patients were recruited from December 2009 to the present and followed for one year. Ease of integration of MeTree into clinical practice at the two intervention clinics was evaluated through patient surveys after their appointment and at 3 months post-visit, and physician surveys 3 months after tool integration. RESULTS: Total enrollment =1,184. Average time to complete MeTree = 27 minutes. Patients found MeTree: easy to use (93%), easy to understand (97%), useful (98%), raised awareness of disease risk (85%), and changed how they think about their health (86%). Of the 26% (N = 311) asking for assistance to complete the tool, age (65 sd 9.4 vs. 57 sd 11.8, p-value < 0.00) and large pedigree size (24.4 sd 9.81 vs. 22.2 sd 8.30, p-value < 0.00) were the only significant factors; 77% of those requiring assistance were over the age of 60. Providers (N = 14) found MeTree: improved their practice (86%), improved their understanding of FHH (64%), made practice easier (79%), and worthy of recommending to their peers (93%). CONCLUSIONS: Our study shows that MeTree has broad acceptance and support from both patients and providers and can be implemented without disruption to workflow.

Personal DNA testing in college classrooms: perspectives of students and professors.

Discourse on the integration of personal genetics and genomics into classrooms is increasing; however, limited data have been collected on the perspectives of students and professors. We conducted a cross-sectional survey of undergraduate and graduate students as well as professors at two major universities to assess attitudes regarding the use of personal DNA testing and other personalized activities in college classrooms. Students indicated that they were more likely to enroll (60.2%) in a genetics course if it offered personal DNA testing; undergraduate students were more likely than graduate students to enroll if personal DNA testing was offered (p=0.029). Students who majored in the physical sciences were less likely to enroll than students in the biological or social sciences (p=0.019). Students also indicated that when course material is personalized, the course is more interesting (94.6%) and the material is easier to learn (87.3%). Professors agreed that adding a personalized element increases student interest, participation, and learning (86.0%, 82.6%, and 72.6%, respectively). The results of this study indicate that, overall, students and professors had a favorable view of the integration of personalized information, including personal DNA testing, into classroom activities, and students welcomed more opportunities to participate in personalized activities.

Recombination modulates how selection affects linked sites in Drosophila.

One of the most influential observations in molecular evolution has been a strong association between local recombination rate and nucleotide polymorphisms across the genome. This is interpreted as evidence for ubiquitous natural selection. The alternative explanation, that recombination is mutagenic, has been rejected by the absence of a similar association between local recombination rate and nucleotide divergence between species. However, many recent studies show that recombination rates are often very different even in closely related species, questioning whether an association between recombination rate and divergence between species has been tested satisfactorily. To circumvent this problem, we directly surveyed recombination across approximately 43% of the D. pseudoobscura physical genome in two separate recombination maps and 31% of the D. miranda physical genome, and we identified both global and local differences in recombination rate between these two closely related species. Using only regions with conserved recombination rates between and within species and accounting for multiple covariates, our data support the conclusion that recombination is positively related to diversity because recombination modulates Hill-Robertson effects in the genome and not because recombination is predominately mutagenic. Finally, we find evidence for dips in diversity around nonsynonymous substitutions. We infer that at least some of this reduction in diversity resulted from selective sweeps and examine these dips in the context of recombination rate.

The physiology of the normal human breast: an exploratory study

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The physiology of the nonlactating human breast likely plays a key role in factors that contribute to the etiology of breast cancer and other breast conditions. Although there has been extensive research into the physiology of lactation, few reports explore the physiology of the resting mammary gland, including mechanisms by which compounds such as hormones, drugs, and potential carcinogens enter the breast ducts. The purpose of this study was to explore transport of exogenous drugs into ductal fluid in nonlactating women and determine if their concentrations in the fluid are similar to those observed in the breast milk of lactating women. We selected two compounds that have been well characterized during lactation, caffeine and cimetidine. Caffeine passively diffuses into breast milk, but cimetidine is actively transported and concentrated in breast milk. After ingestion of caffeine and cimetidine, 14 nonlactating subjects had blood drawn and underwent ductal lavage at five time points over 12 h to measure drug levels in the fluid and blood. The concentrations of both caffeine and cimetidine in lavage fluid were substantially less than those observed in breast milk. Our results support recent evidence that the cimetidine transporter is not expressed in the nonlactating mammary gland, and highlight intriguing differences in the physiology and molecular transport of the lactating and nonlactating breast. The findings of this exploratory study warrant further exploration into the physiology of the nonlactating mammary gland to elucidate factors involved in disease initiation and progression (AU)

The physiology of the normal human breast: an exploratory study.

The physiology of the nonlactating human breast likely plays a key role in factors that contribute to the etiology of breast cancer and other breast conditions. Although there has been extensive research into the physiology of lactation, few reports explore the physiology of the resting mammary gland, including mechanisms by which compounds such as hormones, drugs, and potential carcinogens enter the breast ducts. The purpose of this study was to explore transport of exogenous drugs into ductal fluid in nonlactating women and determine if their concentrations in the fluid are similar to those observed in the breast milk of lactating women. We selected two compounds that have been well characterized during lactation, caffeine and cimetidine. Caffeine passively diffuses into breast milk, but cimetidine is actively transported and concentrated in breast milk. After ingestion of caffeine and cimetidine, 14 nonlactating subjects had blood drawn and underwent ductal lavage at five time points over 12 h to measure drug levels in the fluid and blood. The concentrations of both caffeine and cimetidine in lavage fluid were substantially less than those observed in breast milk. Our results support recent evidence that the cimetidine transporter is not expressed in the nonlactating mammary gland, and highlight intriguing differences in the physiology and molecular transport of the lactating and nonlactating breast. The findings of this exploratory study warrant further exploration into the physiology of the nonlactating mammary gland to elucidate factors involved in disease initiation and progression.