Beggs M.,Aviir Inc.
Pharmacogenomics | Year: 2013
Aviir, Inc. is a venture-funded biotechnology company developing and commercializing laboratory tests to provide personalized information to physicians and patients, with the goal of preventing cardiovascular disease and metabolic syndromes. Leveraging advanced research, Aviir developed and launched MIRISK VP™, a risk assessment test to better identify individuals at risk of a heart attack. Aviir also offers an extensive menu of other cardiovascular and metabolic tests through its Clinical Laboratory Improvement Amendments (CLIA)-certified laboratory. Efforts are likewise focused on expanding genomics testing capability to address sudden cardiac death attributed to inherited cardiovascular diseases. This completes their integrated precision diagnostics approach that combines biomarker immunoassays with genomic and transcription analysis, along with core clinical chemistry to deliver a comprehensive personal health solution. Source
Nolan N.,Aviir Inc. |
Tee L.,Aviir Inc. |
Vijayakumar S.,Aviir Inc. |
Burazor I.,University of Nis |
And 6 more authors.
Expert Opinion on Medical Diagnostics | Year: 2013
Background: Coronary heart disease (CHD) remains prevalent despite efforts to improve CHD risk assessment. The authors developed a multi-analyte immunoassay-based CHD risk assessment (CHDRA) algorithm, clinically validated in a multicenter study, to improve CHDRA in intermediate risk individuals. Objective: Clinical laboratory validation of the CHDRA biomarker assays' analytical performance. Methods: Multiplexed immunoassay panels developed for the seven CHDRA assays were evaluated with donor sera in a clinical laboratory. Specificity, sensitivity, interfering substances and reproducibility of the CHDRA assays, along with the effects of pre-analytical specimen processing, were evaluated. Results: Analytical measurements of the CHDRA panel proteins (CTACK, Eotaxin, Fas Ligand, HGF, IL-16, MCP-3 and sFas) exhibited acceptable accuracy (80-120%), cross-reactivity (< 1%), interference (< 30% at high concentrations of bilirubin, lipids, hemoglobin and HAMA), sensitivity and reproducibility (< 20% CV across multiple runs, operators and instruments). Recoveries from donor sera subjected to typical clinical laboratory pre-analytical conditions were within 80-120%. The pre-analytical variables did not substantively impact the CHDRA scores. Conclusions: The CHDRA panel analytical validation in a clinical laboratory meets or exceeds the specifications established during the clinical utility studies. Risk score reproducibility across multiple test scenarios suggests the assays are not susceptible to clinical laboratory pre-analytical and analytical variation. © 2013 Informa UK, Ltd. Source
Miller A.W.,Biomedical Informatics Research Center |
McCarty C.A.,Second Street |
Broeckel U.,Medical College of Wisconsin |
Hytopoulos V.,Aviir Inc. |
Cross D.S.,University of North Texas Health Science Center
Journal of Biomedical Informatics | Year: 2014
Objective: We aim to quantify HMG-CoA reductase inhibitor (statin) prescriber-intended exposure-time using a generalizable algorithm that interrogates data stored in the electronic health record (EHR). Materials and methods: This study was conducted using the Marshfield Clinic (MC) Personalized Medicine Research Project (PMRP) a central Wisconsin-based population and biobank with, on average, 30. years of electronic health data available in the independently-developed MC Cattails MD EHR. Individuals with evidence of statin exposure were identified from the electronic records, and manual chart abstraction of all mentions of prescribed statins was completed. We then performed electronic chart abstraction of prescriber-intended exposure time for statins, using previously identified logic to capture pill-splitting events, normalizing dosages to atorvastatin-equivalent dose. Four models using iterative training sets were tested to capture statin end-dates. Calculated cumulative provider-intended exposures were compared to manually abstracted gold-standard measures of ordered statin prescriptions, and aggregate model results (totals) for training and validation populations were compared. The most successful model was the one with the smallest discordance between modeled and manually abstracted Atorvastatin 10. mg/year Equivalents (AEs). Results: Of the approximately 20,000 patients enrolled in the PMRP, 6243 were identified with statin exposure during the study period (1997-2011), 59.8% of whom had been prescribed multiple statins over an average of approximately 11. years. When the best-fit algorithm was implemented and validated by manual chart review for the statin-ordered population, it was found to capture 95.9% of the correlation between calculated and expected statin provider-intended exposure time for a random validation set, and the best-fit model was able to predict intended statin exposure to within a standard deviation of 2.6 AEs, with a standard error of +0.23 AEs. Conclusion: We demonstrate that normalized provider-intended statin exposure time can be estimated using a combination of structured clinical data sources, including a medications ordering system and a clinical appointment coordination system, supplemented with text data from clinical notes. © 2014 Elsevier Inc. Source
Cross D.S.,Marshfield Clinic |
McCarty C.A.,Marshfield Clinic |
Hytopoulos E.,Aviir Inc. |
Beggs M.,Aviir Inc. |
And 9 more authors.
Current Medical Research and Opinion | Year: 2012
Background:Many coronary heart disease (CHD) events occur in individuals classified as intermediate risk by commonly used assessment tools. Over half the individuals presenting with a severe cardiac event, such as myocardial infarction (MI), have at most one risk factor as included in the widely used Framingham risk assessment. Individuals classified as intermediate risk, who are actually at high risk, may not receive guideline recommended treatments. A clinically useful method for accurately predicting 5-year CHD risk among intermediate risk patients remains an unmet medical need. Objective:This study sought to develop a CHD Risk Assessment (CHDRA) model that improves 5-year risk stratification among intermediate risk individuals. Methods:Assay panels for biomarkers associated with atherosclerosis biology (inflammation, angiogenesis, apoptosis, chemotaxis, etc.) were optimized for measuring baseline serum samples from 1084 initially CHD-free Marshfield Clinic Personalized Medicine Research Project (PMRP) individuals. A multivariable Cox regression model was fit using the most powerful risk predictors within the clinical and protein variables identified by repeated cross-validation. The resulting CHDRA algorithm was validated in a Multiple-Ethnic Study of Atherosclerosis (MESA) case-cohort sample. Results:A CHDRA algorithm of age, sex, diabetes, and family history of MI, combined with serum levels of seven biomarkers (CTACK, Eotaxin, Fas Ligand, HGF, IL-16, MCP-3, and sFas) yielded a clinical net reclassification index of 42.7% (p<0.001) for MESA patients with a recalibrated Framingham 5-year intermediate risk level. Across all patients, the model predicted acute coronary events (hazard ratio=2.17, p<0.001), and remained an independent predictor after Framingham risk factor adjustments. Limitations:These include the slightly different event definition with the MESA samples and inability to include PMRP fatal CHD events. Conclusions:A novel risk score of serum protein levels plus clinical risk factors, developed and validated in independent cohorts, demonstrated clinical utility for assessing the true risk of CHD events in intermediate risk patients. Improved accuracy in cardiovascular risk classification could lead to improved preventive care and fewer deaths. © 2012 Informa UK Ltd All rights reserved. Source
Hytopoulos E.,Aviir Inc. |
Lee M.L.,Quorum Inc. |
Beggs M.,Aviir Inc. |
French C.,Aviir Inc. |
Tong K.B.,Quorum Inc.
Journal of Medical Economics | Year: 2014
Objectives: The goal of this study is to determine the cost-effectiveness of MIRISK VP, a next generation coronary heart disease risk assessment score, in correctly reclassifying and appropriately treating asymptomatic, intermediate risk patients. Study design: A Markov model was employed with simulated subjects based on the Multi-Ethnic Study of Atherosclerosis (MESA). This study evaluated three treatment strategies: (i) practice at MESA enrollment, (ii) current guidelines, and (iii) MIRISK VP in MESA. Methods: The model assessed patient healthcare costs and outcomes, expressed in terms of life years and quality-adjusted life years (QALYs), over the lifetime of the cohort from the provider and payer perspective. A total of 50,000 hypothetical individuals were used in the model. A sensitivity analysis was conducted (based on the various input parameters) for the entire cohort and also for individuals aged 65 and older. Results: Guiding treatment with MIRISK VP leads to the highest net monetary benefits when compared to the 'Practice at MESA Enrollment' or to the 'Current Guidelines' strategies. MIRISK VP resulted in a lower mortality rate from any CHD event and a modest increase in QALY of 0.12-0.17 years compared to the other two approaches. Limitations: This study has limitations of not comparing performance against strategies other than the FRS, the results are simulated as with all models, the model does not incorporate indirect healthcare costs, and the impact of patient or physician behaviors on outcomes were not taken into account. Conclusions: MIRISK VP has the potential to improve patient outcomes compared to the alternative strategies. It is marginally more costly than both the 'Practice at MESA Enrollment' and the 'Current Guidelines' strategies, but it provides increased effectiveness, which leads to positive net monetary benefits over either strategy. © 2014 Informa UK Ltd. Source