Systematic assessment of decision-analytic models evaluating diagnostic tests for acute myocardial infarction based on cardiac troponin assays

Cardiac amyloidosis and aortic stenosis: a state-of-the-art review

Cardiac amyloidosis is caused by the extracellular deposition of amyloid fibrils in the heart, involving not only the myocardium but also any cardiovascular structure. Indeed, this progressive infiltrative disease also involves the cardiac valves and, specifically, shows a high prevalence with aortic stenosis. Misfolded protein infiltration in the aortic valve leads to tissue damage resulting in the onset or worsening of valve stenosis. Transthyretin cardiac amyloidosis and aortic stenosis coexist in patients > 65 years in about 4-16% of cases, especially in those undergoing transcatheter aortic valve replacement. Diagnostic workup for cardiac amyloidosis in patients with aortic stenosis is based on a multi-parametric approach considering clinical assessment, electrocardiogram, haematologic tests, basic and advanced echocardiography, cardiac magnetic resonance, and technetium labelled cardiac scintigraphy like technetium-99 m (99mTc)-pyrophosphate, 99mTc-3,3-diphosphono-1,2-propanodicarboxylic acid, and 99mTc-hydroxymethylene diphosphonate. However, a biopsy is the traditional gold standard for diagnosis. The prognosis of patients with coexisting cardiac amyloidosis and aortic stenosis is still under evaluation. The combination of these two pathologies worsens the prognosis. Regarding treatment, mortality is reduced in patients with cardiac amyloidosis and severe aortic stenosis after undergoing transcatheter aortic valve replacement. Further studies are needed to confirm these findings and to understand whether the diagnosis of cardiac amyloidosis could affect therapeutic strategies. The aim of this review is to critically expose the current state-of-art regarding the association of cardiac amyloidosis with aortic stenosis, from pathophysiology to treatment.

Health economic evaluations of medical tests: Translating laboratory information into value - A case study example

Health-care providers and funders are focused on identifying value in all their services and that includes laboratories. This means that in order to gain a share of scarce resources, laboratory professionals must also understand and assess the value of tests and that includes their economic impact. This can be assessed using health economic modelling tools which, when used in conjunction with a detailed value proposition for the test, can translate laboratory information into value. While a variety of health economic assessment tools are available, this review will focus on the use of decision analytic models which essentially compare the outcomes from pathways with and without the new test, the value of which is being assessed. A step-by-step framework is provided to guide laboratory professionals through the essential steps of conducting the evaluation. Initial steps include mapping the clinical pathway, understanding the goal of the evaluation, identifying the key stakeholders and their needs and determining a suitable analytical model. Following collection of the actual data, the validity of the model must be checked, and the robustness of the outcomes tested through sensitivity analysis. The last step is to translate the findings into measures of value which can then inform appropriate decisions by the stakeholders. This review of basic health economic modelling should enable laboratory professionals to have an understanding of how modelling can be applied to tests in their own environment and help deliver their potential value.

Who Conducts Health Economic Evaluations of Laboratory Tests? A Scoping Review

BACKGROUND

Health economic evaluations (HEEs) are effectively used to inform decision making in healthcare. We sought to assess the level of involvement of laboratory professionals (LPs) in HEEs of laboratory tests.

METHODS

A systematic literature search was conducted in Medline (2013 to November 28, 2018) for original articles reporting HEEs of medical laboratory tests. Eligible studies were characterized by indication, utilization, region, setting, study design, primary outcome measures, and sponsorship. Authors were classified based on stated affiliation as clinician, scientist, public health expert, or LP.

RESULTS

In total, 140 HEEs were included in the study, of which 24 (17.1%) had contributions from LPs. Studies were primarily focused on infectious disease (n = 68), oncology (n = 23), and cardiovascular disease (n = 16). Cost-utility or cost-effectiveness analyses (n = 117) were the most frequent study types, with effectiveness measured mainly in terms of quality-adjusted life-years (n = 57) and detected cases (n = 41). Overall, 76% of HEEs followed a social or health system perspective, whereas 15% took a hospital viewpoint. Partial or full funding was received from public health organizations or industry in 39% and 16% of studies, respectively. The involvement of LPs was associated with test utilization, secondary care, analytic perspective, and an immediate time horizon (all P < 0.05). Quality of studies was found to be lower in HEEs coauthored by LPs.

CONCLUSION

Multidisciplinary collaboration is essential to understanding the complexity of clinical pathways. HEEs are used effectively to inform healthcare decision making. The involvement of LPs in HEEs is low. This implies that laboratory expertise is frequently not considered in decision processes.