Economic utility of a blood-based genomic test for the assessment of patients with symptoms suggestive of obstructive coronary artery disease

Use of a Blood Biomarker Test Improves Economic Utility in the Evaluation of Older Patients Presenting with Cognitive Impairment

More than 16 million Americans living with cognitive impairment warrant a diagnostic evaluation to determine the cause of this disorder. The recent availability of disease-modifying therapies for Alzheimer's disease (AD) is expected to significantly drive demand for such diagnostic testing. Accurate, accessible, and affordable methods are needed. Blood biomarkers (BBMs) offer advantages over usual care amyloid positron emission tomography (PET) and cerebrospinal fluid (CSF) biomarkers in these regards. This study used a budget impact model to assess the economic utility of the PrecivityAD® blood test, a clinically validated BBM test for the evaluation of brain amyloid, a pathological hallmark of AD. The model compared 2 scenarios: (1) baseline testing involving usual care practice, and (2) early use of a BBM test before usual care CSF and PET biomarker use. At a modest 40% adoption rate, the BBM test scenario had comparable sensitivity and specificity to the usual care scenario and showed net savings in the diagnostic work-up of $3.57 million or $0.30 per member per month in a 1 million member population, translating to over $1B when extrapolated to the US population as a whole and representing a 11.4% cost reduction. Savings were driven by reductions in the frequency and need for CSF and PET testing. Additionally, BBM testing was associated with a cost savings of $643 per AD case identified. Use of the PrecivityAD blood test in the clinical care pathway may prevent unnecessary testing, provide cost savings, and reduce the burden on both patients and health plans.

System dynamics simulation for evaluating implementation strategies of genomic sequencing: tutorial and conceptual model

INTRODUCTION

Precision Medicine (PM), especially in oncology, involve diagnostic and complex treatment pathways that are based on genomic features. To conduct evaluation and decision analysis for PM, advanced modeling techniques are needed due to its complexity. Although System Dynamics (SD) has strong modeling power, it has not been widely used in PM and individualized treatment.

AREAS COVERED

We explained SD tools using examples in cancer context and the rationale behind using SD for genomic testing and personalized oncology. We compared SD with other Dynamic Simulation Modelling (DSM) methods and listed SD's advantages. We developed a conceptual model using Causal Loop Diagram (CLD) for strategic decision-making in Whole Genome Sequencing (WGS) implementation.

EXPERT OPINION

The paper demonstrates that SD is well-suited for health policy evaluation challenges and has useful tools for modeling precision oncology and genomic testing. SD's system-oriented modeling captures dynamic and complex interactions within systems using feedback loops. SD models are simple to implement, utilize less data and computational resources, and conduct both exploratory and explanatory analyses over time. If the targeted system has complex interactions and many components, deals with lack of data, and requires interpretability and clinicians' input, SD offers attractive advantages for modeling and evaluating scenarios.

Incremental predictive value of the combined use of the neutrophil-to-lymphocyte ratio and systolic blood pressure difference after successful drug-eluting stent implantation

BACKGROUND

Previous work has highlighted the importance of the neutrophil-to-lymphocyte ratio (NLR) and the difference in the ward-to-catheterization laboratory systolic blood pressure (ΔSBP) in prognostic stratification after acute coronary syndrome. However, there is paucity of data regarding the added value of combining these two variables to predict 5-year major clinical outcomes after percutaneous coronary intervention.

METHODS

A total of 1188 patients were classified into four groups according to the NLR andΔSBP (high vs. low) using cutoffs derived from an analysis of receiver operating characteristic curves. A NLR > 3.0 and aΔSBP > 25 mmHg were considered high values. The primary endpoint was the composite of all-cause death, cardiac death, and non-fatal myocardial infarction. The secondary endpoint was the composite of target lesion revascularization, target vessel revascularization, and incidence of cerebrovascular accidents.

RESULTS

The incidence of the primary endpoint was significantly higher in the high NLR and ΔSBP group than in the other three groups (2.2% vs. 4.7% vs. 4.3% vs. 13.2%, p < 0.001). The incidence of the secondary endpoint was similar among the four groups. Incorporation of high NLR and high ΔSBP into a model with conventional and meaningful clinical and procedural risk factors increased the C-statistics in predicting the primary endpoint (0.575 to 0.635, p = 0.002).

CONCLUSIONS

The power to predict the primary endpoint after drug-eluting stent implantation at the 5-year follow-up was improved by combining NLR and ΔSBP.

The Clinical Utility of a Precision Medicine Blood Test Incorporating Age, Sex, and Gene Expression for Evaluating Women with Stable Symptoms Suggestive of Obstructive Coronary Artery Disease: Analysis from the PRESET Registry

Background: Evaluating women with symptoms suggestive of coronary artery disease (CAD) remains challenging. A blood-based precision medicine test yielding an age/sex/gene expression score (ASGES) has shown clinical validity in the diagnosis of obstructive CAD. We assessed the effect of the ASGES on the management of women with suspected obstructive CAD in a community-based registry.

Materials and Methods: The prospective PRESET (A Registry to Evaluate Patterns of Care Associated with the Use of Corus^® CAD in Real World Clinical Care Settings) Registry (NCT01677156) enrolled 566 patients presenting with symptoms suggestive of stable obstructive CAD from 21 United States primary care practices from 2012 to 2014. Demographics, clinical characteristics, and referrals to cardiology or further functional and/or anatomical cardiac studies after ASGES testing were collected for this subgroup analysis of women from the PRESET Registry. Patients were followed for 1-year post-ASGES testing.

Results: This study cohort included 288 women with a median age 57 years. The median body mass index was 29.2, with hyperlipidemia and hypertension present in 48% and 43% of patients, respectively. Median ASGES was 8.5 (range 1–40), with 218 (76%) patients having low (≤15) ASGES. Clinicians referred 9% (20/218) low ASGES versus 44% (31/70) elevated ASGES women for further cardiac evaluation (odds ratio 0.14, p < 0.0001, adjusted for patient demographics and clinical covariates). Across the score range, higher ASGES were associated with a higher likelihood of posttest cardiac referral. At 1-year follow-up, low ASGES women experienced fewer major adverse cardiac events than elevated ASGES women (1.3% vs. 4.2% respectively, p = 0.16).

Conclusions: Incorporation of ASGES into the diagnostic workup demonstrated clinical utility by helping clinicians identify women less likely to benefit from further cardiac evaluation.

Clinical Utility of a Precision Medicine Test Evaluating Outpatients with Suspected Obstructive Coronary Artery Disease

BACKGROUND

Identifying patients with obstructive coronary artery disease can be challenging for primary care physicians. Advances in precision medicine may help augment clinical tools and redefine the paradigm for evaluating coronary artery disease in the outpatient setting. A blood-based age/sex/gene expression score (ASGES) incorporating key features of precision medicine has shown clinical validity with a 96% negative predictive value and 89% sensitivity in estimating a symptomatic patient's current likelihood of obstructive coronary artery disease. To better characterize the clinical utility of the ASGES and measure its impact on clinician decision-making, a community-based registry was established.

METHODS

The prospective PRESET Registry (NCT01677156) enrolled stable, nonacute adult patients presenting with typical or atypical symptoms suggestive of obstructive coronary artery disease from 21 US primary care practices from August 2012 to August 2014. Demographics, clinical characteristics, and ASGES results (predefined as low [ASGES ≤15] or elevated [ASGES >15]) were collected, as were referrals to Cardiology or further functional/anatomic cardiac testing after ASGES testing. Patients were followed for 1 year post ASGES testing.

RESULTS

Among the 566-patient cohort (median age 56 years), clinicians referred 26/252 (10%) of patients with low scores vs 137/314 (44%) of patients with elevated scores to Cardiology or advanced cardiac testing for further evaluation (unadjusted odds ratio 0.15, P <.0001; adjusted odds ratio after accounting for clinical covariates = 0.18, P <.0001). Data on 84 patients referred for advanced cardiac testing showed abnormal findings in 0 of 13 (0%) low ASGES and 10 of 71 (14%) elevated ASGES patients. Major adverse cardiovascular events and revascularization were noted in 3/252 (1.2%) patients with low ASGES and 14/314 (4.5%) patients with elevated ASGES score (P <.03).

CONCLUSIONS

In this community-based cardiovascular registry, the ASGES demonstrated clinical utility in the evaluation of patients with suspected obstructive coronary artery disease. Low-score patients were less likely to undergo cardiac referral, were unlikely to have positive findings on further cardiac work-up, and had a low rate of adverse cardiovascular events in 1-year follow-up. Our work provides evidence supporting the value of using precision medicine in the delivery of cardiovascular care.

A systematic review and checklist presenting the main challenges for health economic modeling in personalized medicine: towards implementing patient-level models

INTRODUCTION

The ongoing development of genomic medicine and the use of molecular and imaging markers in personalized medicine (PM) has arguably challenged the field of health economic modeling (HEM). This study aims to provide detailed insights into the current status of HEM in PM, in order to identify if and how modeling methods are used to address the challenges described in literature. Areas covered: A review was performed on studies that simulate health economic outcomes for personalized clinical pathways. Decision tree modeling and Markov modeling were the most observed methods. Not all identified challenges were frequently found, challenges regarding companion diagnostics, diagnostic performance, and evidence gaps were most often found. However, the extent to which challenges were addressed varied considerably between studies. Expert commentary: Challenges for HEM in PM are not yet routinely addressed which may indicate that either (1) their impact is less severe than expected, (2) they are hard to address and therefore not managed appropriately, or (3) HEM in PM is still in an early stage. As evidence on the impact of these challenges is still lacking, we believe that more concrete examples are needed to illustrate the identified challenges and to demonstrate methods to handle them.

The diagnosis of CAD in women: addressing the unmet need - a report from the national expert roundtable meeting

A multistakeholder panel comprising experts in the fields of clinical cardiology, medical technology innovation, women's health research and policy analysis, personalized medicine, payers (including self-insured employers), patient advocacy, and health economics was convened at the Heart House in Washington, DC. The following points emerged as key concepts: (1) Diagnostic challenges in the evaluation of women with symptoms suggestive of obstructive coronary artery disease (CAD) result from: (a) presentation with atypical symptoms and lower pretest probability of disease compared to men, (b) fatty tissue and breast tissue attenuation on cardiac imaging leading to false positive findings, and (c) the presence of microvascular CAD. (2) Diagnostic challenges lead to both over-testing of low-risk women and under-testing of high-risk women. (3) Efforts should be directed toward increasing clinician, clinical professional society, and consumer awareness and understanding of sex-specific differences between men and women in the pathophysiology of CAD. (4) Multiple health care stakeholders should be made aware of new advances in genomic approaches to address the challenges of diagnosing obstructive CAD; specifically, the Corus CAD gene expression test, which was shown to have high sensitivity and negative predictive value in a recent clinical trial. As such, it has promise as a tool to help clinicians to rule out obstructive CAD as a cause of a patient's symptoms. (Population Health Management 2015;18:86-92).