Assessing the value of cardiac biomarkers: going beyond diagnostic accuracy?

Cost-effectiveness of applying high-sensitivity troponin I to a score for cardiovascular risk prediction in asymptomatic population

INTRODUCTION

Risk stratification scores such as the European Systematic COronary Risk Evaluation (SCORE) are used to guide individuals on cardiovascular disease (CVD) prevention. Adding high-sensitivity troponin I (hsTnI) to such risk scores has the potential to improve accuracy of CVD prediction. We investigated how applying hsTnI in addition to SCORE may impact management, outcome, and cost-effectiveness.

METHODS

Characteristics of 72,190 apparently healthy individuals from the Biomarker for Cardiovascular Risk Assessment in Europe (BiomarCaRE) project were included into a discrete-event simulation comparing two strategies for assessing CVD risk. The standard strategy reflecting current practice employed SCORE (SCORE); the alternative strategy involved adding hsTnI information for further stratifying SCORE risk categories (S-SCORE). Individuals were followed over ten years from baseline examination to CVD event, death or end of follow-up. The model tracked the occurrence of events and calculated direct costs of screening, prevention, and treatment from a European health system perspective. Cost-effectiveness was expressed as incremental cost-effectiveness ratio (ICER) in € per quality-adjusted life year (QALYs) gained during 10 years of follow-up. Outputs were validated against observed rates, and results were tested in deterministic and probabilistic sensitivity analyses.

RESULTS

S-SCORE yielded a change in management for 10.0% of individuals, and a reduction in CVD events (4.85% vs. 5.38%, p<0.001) and mortality (6.80% vs. 7.04%, p<0.001). S-SCORE led to 23 (95%CI: 20-26) additional event-free years and 7 (95%CI: 5-9) additional QALYs per 1,000 subjects screened, and resulted in a relative risk reduction for CVD of 9.9% (95%CI: 7.3-13.5%) with a number needed to screen to prevent one event of 183 (95%CI: 172 to 203). S-SCORE increased costs per subject by 187€ (95%CI: 177 € to 196 €), leading to an ICER of 27,440€/QALY gained. Sensitivity analysis was performed with eligibility for treatment being the most sensitive.

CONCLUSION

Adding a person's hsTnI value to SCORE can impact clinical decision making and eventually improves QALYs and is cost-effective compared to CVD prevention strategies using SCORE alone. Stratifying SCORE risk classes for hsTnI would likely offer cost-effective alternatives, particularly when targeting higher risk groups.

The early economic evaluation of novel biomarkers to accelerate their translation into clinical applications

BACKGROUND

Translating prognostic and diagnostic biomarker candidates into clinical applications takes time, is very costly, and many candidates fail. It is therefore crucial to be able to select those biomarker candidates that have the highest chance of successfully being adopted in the clinic. This requires an early estimate of the potential clinical impact and commercial value. In this paper, we aim to demonstratively evaluate a set of novel biomarkers in terms of clinical impact and commercial value, using occurrence of cardiovascular disease (CVD) in type-2 diabetes (DM2) patients as a case study.

METHODS

We defined a clinical application for the novel biomarkers, and subsequently used data from a large cohort study in The Netherlands in a modeling exercise to assess the potential clinical impact and headroom for the biomarkers.

RESULTS

The most likely application of the biomarkers would be to identify DM2 patients with a low CVD risk and subsequently withhold statin treatment. As a result, one additional CVD event in every 75 patients may be expected. The expected downstream savings resulted in a headroom for a point-of-care device ranging from €119.09 at a willingness to accept of €0 for one additional CVD event, to €0 at a willingness to accept of €15,614 or more.

CONCLUSION

It is feasible to evaluate novel biomarkers on outcomes directly relevant to technological development and clinical adoption. Importantly, this may be attained at the same point in time and using the same data as used for the evaluation of association with disease and predictive power.

The Cost-effective Laboratory: Implementation of Economic Evaluation of Laboratory Testing

Laboratory testing as a part of laboratory in vitro diagnostic (IVD) has become required tool in clinical practice for diagnosing, monitoring and prognosis of diseases, as well as for prediction of treatment response. The number of IVD tests available in laboratory practice has increased over the past decades and is likely to further increase in the future. Consequently, there is growing concern about the overutilization of laboratory tests and rising costs for laboratory testing. It is estimated that IVD accounts for between 1.4 and 2.3% of total healthcare expenditure and less than 5% of total hospital cost (Lewin Group report). These costs are rather low when compared to pharmaceuticals and medical aids which account for 15 and 5%, respectively. On the other hand, IVD tests play an important role in clinical practice, as they influence from 60% to 70% of clinical decision-making. Unfortunately, constant increases in healthcare spending are not directly related to healthcare benefit. Since healthcare resources are limited, health payers are interested whether the benefits of IVD tests are actually worth their cost. Many articles have introduced frameworks to assess the economic value of IVD tests. The most appropriate tool for quantitative assessment of their economic value is cost-effectiveness (CEA) and cost-utility (CUA) analysis. The both analysis determine cost in terms of effectiveness or utilities (combine quantity and quality of life) of new laboratory test against its alternative. On the other hand, some investigators recommended calculation of laboratory test value as product of two ratios: Laboratory test value = (Technical accuracy/Turnaround time) × (Utility/Costs). Recently, some researches used multicriteria decision analysis which allows comparison of diagnostic strategies in terms of benefits, opportunities, costs and risks. All analyses are constructed to identify laboratory test that produce the greatest healthcare benefit with the resources available. Without solid evidence that certain laboratory tests are cost-effective, laboratory services cannot be improved. Consequently, simple policy measures such as cost cutting may be imposed upon many laboratories while patients will have limited access to laboratory service.

The Value of In Vitro Diagnostic Testing in Medical Practice: A Status Report

BACKGROUND

In vitro diagnostic (IVD) investigations are indispensable for routine patient management. Appropriate testing allows early-stage interventions, reducing late-stage healthcare expenditure (HCE).

AIM

To investigate HCE on IVDs in two developed markets and to assess the perceived value of IVDs on clinical decision-making. Physician-perceived HCE on IVD was evaluated, as well as desired features of new diagnostic markers.

METHODS

Past and current HCE on IVD was calculated for the US and Germany. A total of 79 US/German oncologists and cardiologists were interviewed to assess the number of cases where: physicians ask for IVDs; IVDs are used for initial diagnosis, treatment monitoring, or post-treatment; and decision-making is based on an IVD test result. A sample of 201 US and German oncologists and cardiologists was questioned regarding the proportion of HCE they believed to be attributable to IVD testing. After disclosing the actual IVD HCE, the physician's perception of the appropriateness of the amount was captured. Finally, the association between physician-rated impact of IVD on decision-making and perceived contribution of IVD expenditure on overall HCE was assessed.

RESULTS

IVD costs account for 2.3% and 1.4% of total HCE in the US and Germany. Most physicians (81%) believed that the actual HCE on IVDs was >5%; 19% rated the spending correctly (0-4%, p<0.001). When informed of the actual amount, 64% of physicians rated this as appropriate (p<0.0001); 66% of decision-making was based on IVD. Significantly, more physicians asked for either additional clinical or combined clinical/health economic data than for the product (test/platform) alone (p<0.0001).

CONCLUSIONS

Our results indicate a poor awareness of actual HCE on IVD, but a high attributable value of diagnostic procedures for patient management. New markers should deliver actionable and medically relevant information, to guide decision-making and foster improved patient outcomes.