In the drive towards faster patient access to treatments, health technology assessment (HTA) agencies are increasingly faced with reliance on evidence from surrogate endpoints, leading to increased decision uncertainty. This study undertook an updated survey of methodological guidance for using surrogate endpoints across international HTA agencies. We reviewed HTA and economic evaluation methods guidance from European, Australian and Canadian HTA agencies. We considered how guidelines addressed the methods for handling surrogate endpoints, including (1) level of evidence, (2) methods of validation, and (3) thresholds of acceptability. Across the 73 HTA agencies surveyed, 29 (40%) had methodological guidelines that made specific reference to consideration of surrogate outcomes. Of the 45 methods documents analysed, the majority [27 (60%)] were non-technology specific, 15 (33%) focused on pharmaceuticals and three (7%) on medical devices. The principles of the European network for Health Technology Assessment (EUnetHTA) guidelines published in 2015 on the handling of surrogate endpoints appear to have been adopted by many European HTA agencies, i.e. preference for final patient-relevant outcomes and reliance on surrogate endpoints with biological plausibility and epidemiological evidence of the association between the surrogate and final endpoint. Only a small number of HTA agencies (UK National Institute for Care and Excellence; the German Institute for Medical Documentation and Information and Institute for Quality and Efficiency in Health Care; the Australian Pharmaceutical Benefits Advisory Committee; and the Canadian Agency for Drugs and Technologies in Health) have developed more detailed prescriptive criteria for the acceptance of surrogate endpoints, e.g. meta-analyses of randomised controlled trials showing strong association between the treatment effect on the surrogate and final outcomes. As the decision uncertainty associated with reliance on surrogate endpoints carries a risk to patients and society, there is a need for HTA agencies to develop more detailed methodological guidance for consistent selection and evaluation of health technologies that lack definitive final patient-relevant outcome evidence at the time of the assessment.
Aim Technological and computational advancements offer new tools for the collection and analysis of real-world data (RWD). Considering the substantial effort and resources devoted to collecting RWD, a greater return would be achieved if real-world evidence (RWE) was effectively used to support Health Technology Assessment (HTA) and decision making on medical technologies. A useful question is: To what extent are RWD suitable for generating RWE? Methods We mapped existing RWD sources in Europe for three case studies: hip and knee arthroplasty, transcatheter aortic valve implantation (TAVI) and mitral valve repair (TMVR), and robotic surgery procedures. We provided a comprehensive assessment of their content and appropriateness for conducting the HTA of medical devices. The identification of RWD sources was performed combining a systematic search on PubMed with gray literature scoping, covering fifteen European countries. Results We identified seventy-one RWD sources on arthroplasties; ninety-five on TAVI and TMVR; and seventy-seven on robotic procedures. The number, content, and integrity of the sources varied dramatically across countries. Most sources included at least one health outcome (97.5%), with mortality and rehospitalization/reoperation the most common; 80% of sources included resource outcomes, with length of stay the most common, and comparators were available in almost 70% of sources. Conclusions RWD sources bear the potential for the HTA of medical devices. The main challenges are data accessibility, a lack of standardization of health and economic outcomes, and inadequate comparators. These findings are crucial to enabling the incorporation of RWD into decision making and represent a readily available tool for getting acquainted with existing information sources.
Background Surrogate endpoints (i.e., intermediate endpoints intended to predict for patient-centered outcomes) are increasingly common. However, little is known about how surrogate evidence is handled in the context of health technology assessment (HTA). Objectives 1) To map methodologies for the validation of surrogate endpoints and 2) to determine their impact on acceptability of surrogates and coverage decisions made by HTA agencies. Methods We sought HTA reports where evaluation relied on a surrogate from 8 HTA agencies. We extracted data on the methods applied for surrogate validation. We assessed the level of agreement between agencies and fitted mixed-effects logistic regression models to test the impact of validation approaches on the agency’s acceptability of the surrogate endpoint and their coverage recommendation. Results Of the 124 included reports, 61 (49%) discussed the level of evidence to support the relationship between the surrogate and the patient-centered endpoint, 27 (22%) reported a correlation coefficient/association measure, and 40 (32%) quantified the expected effect on the patient-centered outcome. Overall, the surrogate endpoint was deemed acceptable in 49 (40%) reports ( k-coefficient 0.10, P = 0.004). Any consideration of the level of evidence was associated with accepting the surrogate endpoint as valid (odds ratio [OR], 4.60; 95% confidence interval [CI], 1.60–13.18, P = 0.005). However, we did not find strong evidence of an association between accepting the surrogate endpoint and agency coverage recommendation (OR, 0.71; 95% CI, 0.23–2.20; P = 0.55). Conclusions Handling of surrogate endpoint evidence in reports varied greatly across HTA agencies, with inconsistent consideration of the level of evidence and statistical validation. Our findings call for careful reconsideration of the issue of surrogacy and the need for harmonization of practices across international HTA agencies.
Variation in healthcare utilization has been discussed extensively, with many studies showing that variation exists, but fewer studies investigating the underlying factors. In our study, we used a logistic multilevel‐model at the patient, hospital, and regional levels to investigate (i) the levels to which variation could be attributed and (ii) the hospital and regional factors associated with treatment decisions. To do so, we used hospital discharge records for the years 2012–2016 in Germany and Italy and for 2014–2016 in the Netherlands combined with hospital and regional characteristics in nine case studies. We used a theoretical framework to categorize these case studies into effective, preference‐sensitive, and supply‐sensitive care. Our results suggest that most variation in the treatment decision can be attributed to the hospital level (e.g., case volume), whereas only a minor part is explained by regional characteristics. Italy had the highest share attributable to the regional level, whereas the Netherlands had the lowest. We observed less variation for procedures in the effective‐care category compared to the preference‐ and supply‐sensitive categories. Although our results were heterogeneous, we identified patterns in line with the theoretical framework for treatment categories, underlining the need to address variation differently depending on the category in question.
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