Different regulatory framework for medical devices and drugs in the European Union: Impact on clinical research and health technology assessments.

OBJECTIVES: Understanding whether the regulatory framework in the European Union creates different standards for medical devices and drugs, assessing whether there is evidence on the impact of those standards on clinical and HTA research, and reflecting on findings in order to propose legislative changes for promoting a more efficient allocation of resources in the healthcare systems. METHODS: Reviewing and comparing the legal framework for the approval of medical devices and drugs in the EU, with a particular focus on the changes brought by Regulation (EU) 2017/745. Investigating the available information on manufacturer sponsored clinical studies and HTA-supported recommendations for medical devices and drugs. RESULTS: The review of the legislation identified different standards for approval of devices and drugs on their quality, safety, and performance/efficacy dimensions and fewer manufacturer sponsored clinical studies and HTA-supported recommendations for medical devices versus drugs. CONCLUSIONS: Policy changes could be implemented in order to promote an integrated evidence-based assessment system for a better allocation of resources in healthcare, namely: a consensual classification of medical devices from an HTA perspective, which could be used as a guide for generating outcomes in clinical investigation, and the adoption of conditional coverage practices including mandatory post-approval evidence development for performing periodic technology assessments.

Matching-Adjusted Indirect Comparisons of Lorlatinib Versus Chemotherapy for Patients With Second-Line or Later Anaplastic Lymphoma Kinase-Positive Non-Small Cell Lung Cancer.

OBJECTIVES: This study aimed to compare the relative efficacy of lorlatinib, an anaplastic lymphoma kinase-tyrosine kinase inhibitor, with chemotherapy, for patients with second-line or later advanced anaplastic lymphoma kinase-positive non-small cell lung cancer. The endpoints of interest were overall survival (OS) and progression-free survival (PFS). METHODS: Evidence for lorlatinib was informed by the single-arm phase I/II trial B7461001. A systematic literature review (SLR) was performed to identify OS and PFS data for chemotherapy. Unanchored matching-adjusted indirect comparisons (MAICs) between lorlatinib and chemotherapy (pemetrexed/docetaxel, platinum-based, or systemic therapy) were performed. RESULTS: The SLR identified 3 relevant studies reporting PFS. Lorlatinib was associated with a significant decrease in the hazard of progression versus the 2 types of chemotherapy assessed. For PFS, the MAIC of lorlatinib versus the combined treatment arm of docetaxel or pemetrexed resulted in an adjusted hazard ratio (HR) of 0.22 (95% confidence interval [CI] 0.15-0.31). When lorlatinib was compared with platinum-based chemotherapy through an MAIC, the adjusted HR for PFS was 0.40 (95% CI 0.29-0.55). An exploratory comparison was performed for OS with evidence for systemic therapy (assumed equivalent to chemotherapy) not identified in the SLR. Lorlatinib provided a significant decrease in hazard of death (OS) versus systemic therapy, with HRs ranging from 0.12 (95% CI 0.05-0.27) to 0.43 (95% CI 0.27-0.60). CONCLUSIONS: Lorlatinib demonstrated a significant improvement in PFS compared with chemotherapy, although limitations in the analyses were identified. The evidence informing OS comparisons was highly limited but suggested benefit of lorlatinib compared with systemic therapy.

Home Telemonitoring and a Diagnostic Algorithm in the Management of Heart Failure in the Netherlands: Cost-effectiveness Analysis.

BACKGROUND: Heart failure is a major health concern associated with significant morbidity, mortality, and reduced quality of life in patients. Home telemonitoring (HTM) facilitates frequent or continuous assessment of disease signs and symptoms, and it has shown to improve compliance by involving patients in their own care and prevent emergency admissions by facilitating early detection of clinically significant changes. Diagnostic algorithms (DAs) are predictive mathematical relationships that make use of a wide range of collected data for calculating the likelihood of a particular event and use this output for prioritizing patients with regard to their treatment. OBJECTIVE: This study aims to assess the cost-effectiveness of HTM and a DA in the management of heart failure in the Netherlands. Three interventions were analyzed: usual care, HTM, and HTM plus a DA. METHODS: A previously published discrete event simulation model was used. The base-case analysis was performed according to the Dutch guidelines for economic evaluation. Sensitivity, scenario, and value of information analyses were performed. Particular attention was given to the cost-effectiveness of the DA at various levels of diagnostic accuracy of event prediction and to different patient subgroups. RESULTS: HTM plus the DA extendedly dominates HTM alone, and it has a deterministic incremental cost-effectiveness ratio compared with usual care of €27,712 (currency conversion rate in purchasing power parity at the time of study: €1=US $1.29; further conversions are not applicable in cost-effectiveness terms) per quality-adjusted life year. The model showed robustness in the sensitivity and scenario analyses. HTM plus the DA had a 96.0% probability of being cost-effective at the appropriate €80,000 per quality-adjusted life year threshold. An optimal point for the threshold value for the alarm of the DA in terms of its cost-effectiveness was estimated. New York Heart Association class IV patients were the subgroup with the worst cost-effectiveness results versus usual care, while HTM plus the DA was found to be the most cost-effective for patients aged <65 years and for patients in New York Heart Association class I. CONCLUSIONS: Although the increased costs of adopting HTM plus the DA in the management of heart failure may seemingly be an additional strain on scarce health care resources, the results of this study demonstrate that, by increasing patient life expectancy by 1.28 years and reducing their hospitalization rate by 23% when compared with usual care, the use of this technology may be seen as an investment, as HTM plus the DA in its current form extendedly dominates HTM alone and is cost-effective compared with usual care at normally accepted thresholds in the Netherlands.

Modeling Early Warning Systems: Construction and Validation of a Discrete Event Simulation Model for Heart Failure.

OBJECTIVES: Developing and validating a discrete event simulation model that is able to model patients with heart failure managed with usual care or an early warning system (with or without a diagnostic algorithm) and to account for the impact of individual patient characteristics in their health outcomes. METHODS: The model was developed using patient-level data from the Trans-European Network - Home-Care Management System study. It was coded using RStudio Version 1.3.1093 (version 3.6.2.) and validated along the lines of the Assessment of the Validation Status of Health-Economic decision models tool. The model includes 20 patient and disease characteristics and generates 8 different outcomes. Model outcomes were generated for the base-case analysis and used in the model validation. RESULTS: Patients managed with the early warning system, compared with usual care, experienced an average increase of 2.99 outpatient visits and a decrease of 0.02 hospitalizations per year, with a gain of 0.81 life years (0.45 quality-adjusted life years) and increased average total costs of €11 249. Adding a diagnostic algorithm to the early warning system resulted in a 0.92 life year gain (0.57 quality-adjusted life years) and increased average costs of €9680. These patients experienced a decrease of 0.02 outpatient visits and 0.65 hospitalizations per year, while they avoided being hospitalized 0.93 times. The model showed robustness and validity of generated outcomes when comparing them with other models addressing the same problem and with external data. CONCLUSIONS: This study developed and validated a unique patient-level simulation model that can be used for simulating a wide range of outcomes for different patient subgroups and treatment scenarios. It provides useful information for guiding research and for developing new treatment options by showing the hypothetical impact of these interventions on a large number of important heart failure outcomes.

Impact of hospitalisation on health-related quality of life in patients with chronic heart failure.

BACKGROUND: Empirical identification of the direct impact of hospitalisation in the change in utility could provide an interpretation for some of the unexplained variance in quality of life responses in clinical practice and clinical trials and provide assistance to researchers in assessing the impact of a hospitalisation in the context of economic evaluations. This study had the goal of determining the impact of nonfatal hospitalisations on the quality of life of a cohort of patients previously diagnosed with heart failure by using their quality of life measurements before and after hospitalisation. METHODS: The impact of hospitalisation on health-related quality of life was estimated by calculating the difference in utility measured using the EQ-5D-3L in patients that were hospitalised and had records of utility before and after hospitalisation. The variation in differences between the utilities pre and post hospitalisation was explained through two multiple linear regression models using (1) the individual patient characteristics and (2) the hospitalisation characteristics as explanatory variables. RESULTS: The mean difference between health-related quality of life measurement pre and post hospitalisation was found to be 0.020 [95% CI: - 0.020, 0.059] when measured with the EQ-5D index, while there was a mean decrease of - 0.012 [95% CI: - 0.043, 0.020] in the utility measured with the visual analogue scale. Differences in utility variation according to the primary cause for hospitalisation were found. Regression models showed a statistically significant impact of body mass index and serum creatinine in the index utility differences and of serum creatinine for utilities measured with the visual analogue scale. CONCLUSIONS: Knowing the impact of hospitalisation on health-related quality of life is particularly relevant for informing cost-effectiveness studies designed to assess health technologies aimed at reducing hospital admissions. Through using patient-level data it was possible to estimate the variation in utilities before and after the average hospitalisation and for hospitalisations due to the most common causes for hospital admission. These estimates for (dis) utility could be used in the calculations of effectiveness on economic evaluations, especially when discrete event simulations are the employed modelling technique.

Early warning systems for the management of chronic heart failure: a systematic literature review of cost-effectiveness models.

INTRODUCTION: Describing the general and methodological characteristics of decision-analytical models used in the economic evaluation of early warning systems for the management of chronic heart failure patients and performing a quality assessment of their methodological characteristics is expected to provide concise and useful insight to inform the future development of decision-analytical models in the field of heart failure management. AREAS COVERED: The literature on decision-analytical models for the economic evaluation of early warning systems for the management of chronic heart failure patients was systematically reviewed. Nine electronic databases were searched through the combination of synonyms for heart failure and sensitive filters for cost-effectiveness and early warning systems. EXPERT COMMENTARY: The retrieved models show some variability with regards to their general study characteristics. Overall, they display satisfactory methodological quality, even though some points could be improved, namely on the consideration and discussion of any competing theories regarding model structure and disease progression, identification of key parameters and the use of expert opinion, and uncertainty analyses. A comprehensive definition of early warning systems and further research under this label should be pursued. To improve the transparency of economic evaluation publications, authors should make available detailed technical information regarding the published models.

Pomalidomide with Dexamethasone for Treating Relapsed and Refractory Multiple Myeloma Previously Treated with Lenalidomide and Bortezomib: An Evidence Review Group Perspective of an NICE Single Technology Appraisal.

The National Institute for Health and Care Excellence (NICE), as part of the institute's single technology appraisal (STA) process, invited the manufacturer of pomalidomide (POM; Imnovid®, Celgene) to submit evidence regarding the clinical and cost effectiveness of the drug in combination with dexamethasone (POM + LoDEX) for the treatment of relapsed and refractory multiple myeloma (RRMM) after at least two regimens including lenalidomide (LEN) and bortezomib (BOR). Kleijnen Systematic Reviews Ltd (KSR) and Erasmus University Rotterdam were commissioned as the Evidence Review Group (ERG) for this submission. The ERG reviewed the evidence submitted by the manufacturer, validated the manufacturer's decision analytic model, and conducted exploratory analyses in order to assess the robustness and validity of the presented clinical and cost-effectiveness results. This paper describes the company submission, the ERG assessment, and NICE's subsequent decisions. The company conducted a systematic review to identify studies comparing POM with comparators outlined in the NICE scope: panobinostat with bortezomib and dexamethasone (PANO + BOR + DEX), bendamustine with thalidomide and dexamethasone (BTD) and conventional chemotherapy (CC). The main clinical effectiveness evidence was obtained from MM-003, a randomized controlled trial (RCT) comparing POM + LoDEX with high-dose dexamethasone (HiDEX; used as a proxy for CC). Additional data from other studies were also used as nonrandomized observational data sources for the indirect treatment comparison of POM + LoDEX with BTD and PANO + BOR + DEX. Covariate or treatment switching adjustment methods were used for each comparison. The model developed in Microsoft® Excel 2010 using a semi-Markov partitioned survival structure, submitted in the original submission to NICE for TA338, was adapted for the present assessment of the cost effectiveness of POM + LoDEX. Updated evidence from the clinical-effectiveness part was used for the survival modelling of progression-free survival and overall survival. For POM + LoDEX, the patient access scheme (PAS) discount was applied to the POM price. Three separate comparisons were conducted for each comparator, each comparison using a different dataset and adjustment methods. The ERG identified and corrected some errors, and the corrected incremental cost-effectiveness ratios (ICERs) for POM + LoDEX versus each comparator were presented: approximately £45,000 per quality-adjusted life-year (QALY) gained versus BTD, savings of approximately £143,000 per QALY lost versus PANO + BOR + DEX, and approximately £49,000 per QALY gained versus CC. The ERG also conducted full incremental analyses, which revealed that CC, POM + LoDEX and PANO + BOR + DEX were on the cost-effectiveness frontier. The committee's decision on the technology under analysis deemed that POM + LoDEX should be recommended as an option for treating multiple myeloma in adults at third or subsequent relapse of treatments including both LEN and BOR, contingent on the company providing POM with the discount agreed in the PAS.

Biologicals and biosimilars: safety issues in Europe.

INTRODUCTION: Medicinal products of a biological origin are approved by the EMA at a centralized level. However, there is no harmonization about their use in Europe. The current regulation referring to the safety of biological medicinal products and biosimilars in Europe has been identified. The safety associated with medicinal products of a biological origin is assured by the pharmacovigilance system, which has evolved, but doesn't yet incorporate all of the specific information from this market segment, namely that related to the identification of drugs, and its use - including the prescription and dispensing, given the possibility of interchangeability and substitution. The terminology, information systems and traceability systems aren't entirely appropriate to ensure the safety requirements for therapy with medicinal products of a biological origin. Areas covered: This article aims to identify the prescription and dispensing profiles of reference biological medicines and biosimilars in the EU, and the determinants that support their safe use. Expert opinion: The European pharmacovigilance system must evolve to ensure the safety along all of the biologicals' therapeutic cycle. It must consider the safety for each of the medicines in addition to their safety pattern related to the eventual switching procedure.