EVIDENCE REQUIRED BY HEALTH TECHNOLGY ASSESSMENT AND REIMBURSEMENT BODIES EVALUATING DIAGNOSTIC OR PROGNOSTIC ALGORITHMS THAT INCLUDE OMICS DATA.

OBJECTIVES: Multi-analyte assays with algorithmic analyses (MAAAs) use combinations of circulating and clinical markers including omics-based sources for diagnostic and/or prognostic purposes. Assessing MAAAs is challenging under existing health technology assessment (HTA) methods or practices. We undertook a scoping review to explore the HTA methods used for MAAAs to identify the criteria used for clinical research and reimbursement purposes. METHODS: This review included only non-companion (stand-alone) tests that are actionable and that have been evaluated by leading HTA or insurer/reimbursement bodies up to September 2017. RESULTS: Twenty-five reports and articles evaluating seventeen MAAAs were examined, most of which have been developed in oncology. The two main models used were the EUnetHTA Core model and the Evaluation of Genomic Applications in Practice and Prevention ACCE framework. Clinical validity and utility criteria were used, as were economic, ethical, legal, and social aspects. Economic evidence on MAAAs was scarce, and there is no consensus on whether the perspectives used are sufficiently broad to include all relevant stakeholders. CONCLUSIONS: Clinical utility and efficiency were the most used criteria, with stronger evidence needed linking the use of the algorithm with the clinical outcomes in real-life practice. HTA bodies must as well consider questions related to the analytical validity of MAAAs or with organizational aspects. The two main models, the EUnetHTA Core model and the ACCE framework, could be adapted to the assessment of MAAAs.

Meta-analytic estimation of measurement variability and assessment of its impact on decision-making: the case of perioperative haemoglobin concentration monitoring.

BACKGROUND: As a part of a larger Health Technology Assessment (HTA), the measurement error of a device used to monitor the hemoglobin concentration of a patient undergoing surgery, as well as its decision consequences, were to be estimated from published data. METHODS: A Bayesian hierarchical model of measurement error, allowing the meta-analytic estimation of both central and dispersion parameters (under the assumption of normality of measurement errors) is proposed and applied to published data; the resulting potential decision errors are deduced from this estimation. The same method is used to assess the impact of an initial calibration. RESULTS: The posterior distributions are summarized as mean ± sd (credible interval). The fitted model exhibits a modest mean expected error (0.24 ± 0.73 (-1.23 1.59) g/dL) and a large variability (mean absolute expected error 1.18 ± 0.92 (0.05 3.36) g/dL). The initial calibration modifies the bias (-0.20 ± 0.87 (-1.99 1.49) g/dL), but the variability remains almost as large (mean absolute expected error 1.05 ± 0.87 (0.04 3.21) g/dL). This entails a potential decision error ("false positive" or "false negative") for about one patient out of seven. CONCLUSIONS: The proposed hierarchical model allows the estimation of the variability from published aggregates, and allows the modeling of the consequences of this variability in terms of decision errors. For the device under assessment, these potential decision errors are clinically problematic.

Assessment and non-clinical impact of medical devices.

Medical devices (MDs) cover a wide variety of products. They accompany changes in medical practice in step with technology innovations. Innovations in the field of MDs can improve the conditions of use of health technology and/or modify the organisation of care beyond the strict diagnostic or therapeutic benefit for the patients. However, these non purely clinical criteria seem to be only rarely documented or taken into account in the assessment of MDs during reimbursement decisions at national level or for formulary listing by hospitals even though multidimensional models for the assessment of health technologies have been developed that take into account the views of all stakeholders in the healthcare system In this article, after summarising the background concerning the assessment of health technologies in France, a definition of non-clinical criteria for the assessment of MDs is proposed and a decision tree for the assessment of MDs is described. Future lines of approach are proposed as a conclusion.

Fully bioresorbable drug-eluting coronary scaffolds: A review.

Following the development of stents, then drug-eluting stents (DES), bioresorbable scaffolds are proposed as a third evolution in coronary angioplasty, aiming to reduce the incidence of restenosis and stent thrombosis and to restore vascular physiology. At least 16 such devices are currently under development, but published clinical data were available for only three of them in September 2014. The first device is Abbott's BVS(®), a poly-L-lactic acid (PLLA)-based everolimus-eluting device, which has been tested in a registry and two non-randomized trials. Clinical results seem close to what is expected from a modern DES, but possibly with more post-procedural side-effects. Two randomized trials versus DES are underway. This device is already marketed in many European countries. The second device is Elixir's DESolve(®), a PLLA-based novolimus-eluting device, which has been evaluated in two single-arm trials. Results are not widely different from those expected from a DES. The third device is Biotronik's DREAMS(®), a metallic magnesium-based paclitaxel-eluting device, which has been assessed in an encouraging single-arm trial; its second version is currently undergoing evaluation in a single-arm trial. The available results suggest that the technological and clinical development of bioresorbable scaffolds is not yet complete: their possible clinical benefits are still unclear compared with third-generation DES; the impact of arterial physiology restoration has to be assessed over the long term; and their cost-effectiveness has to be established. From the perspective of a health technology assessment, there is no compelling reason to hasten the clinical use of these devices before the results of ongoing randomized controlled trials become available.