Development of a framework and decision tool for the evaluation of health technologies based on surrogate endpoint evidence.

In the drive toward faster patient access to treatments, health technology assessment (HTA) agencies and payers are increasingly faced with reliance on evidence based on surrogate endpoints, increasing decision uncertainty. Despite the development of a small number of evaluation frameworks, there remains no consensus on the detailed methodology for handling surrogate endpoints in HTA practice. This research overviews the methods and findings of four empirical studies undertaken as part of COMED (Pushing the Boundaries of Cost and Outcome Analysis of Medical Technologies) program work package 2 with the aim of analyzing international HTA practice of the handling and considerations around the use of surrogate endpoint evidence. We have synthesized the findings of these empirical studies, in context of wider contemporary body of methodological and policy-related literature on surrogate endpoints, to develop a web-based decision tool to support HTA agencies and payers when faced with surrogate endpoint evidence. Our decision tool is intended for use by HTA agencies and their decision-making committees together with the wider community of HTA stakeholders (including clinicians, patient groups, and healthcare manufacturers). Having developed this tool, we will monitor its use and we welcome feedback on its utility.

Development, validation and effectiveness of diagnostic prediction tools for colorectal cancer in primary care: a systematic review.

BACKGROUND: Tools based on diagnostic prediction models are available to help general practitioners (GP) diagnose colorectal cancer. It is unclear how well they perform and whether they lead to increased or quicker diagnoses and ultimately impact on patient quality of life and/or survival. The aim of this systematic review is to evaluate the development, validation, effectiveness, and cost-effectiveness, of cancer diagnostic tools for colorectal cancer in primary care. METHODS: Electronic databases including Medline and Web of Science were searched in May 2017 (updated October 2019). Two reviewers independently screened titles, abstracts and full-texts. Studies were included if they reported the development, validation or accuracy of a prediction model, or assessed the effectiveness or cost-effectiveness of diagnostic tools based on prediction models to aid GP decision-making for symptomatic patients presenting with features potentially indicative of colorectal cancer. Data extraction and risk of bias were completed by one reviewer and checked by a second. A narrative synthesis was conducted. RESULTS: Eleven thousand one hundred thirteen records were screened and 23 studies met the inclusion criteria. Twenty-studies reported on the development, validation and/or accuracy of 13 prediction models: eight for colorectal cancer, five for cancer areas/types that include colorectal cancer. The Qcancer models were generally the best performing. Three impact studies met the inclusion criteria. Two (an RCT and a pre-post study) assessed tools based on the RAT prediction model. The third study looked at the impact of GP practices having access to RAT or Qcancer. Although the pre-post study reported a positive impact of the tools on outcomes, the results of the RCT and cross-sectional survey found no evidence that use of, or access to, the tools was associated with better outcomes. No study evaluated cost effectiveness. CONCLUSIONS: Many prediction models have been developed but none have been fully validated. Evidence demonstrating improved patient outcome of introducing the tools is the main deficiency and is essential given the imperfect classification achieved by all tools. This need is emphasised by the equivocal results of the small number of impact studies done so far.

EXPLICIT: a feasibility study of remote expert elicitation in health technology assessment.

BACKGROUND: Expert opinion is often sought to complement available information needed to inform model-based economic evaluations in health technology assessments. In this context, we define expert elicitation as the process of encoding expert opinion on a quantity of interest, together with associated uncertainty, as a probability distribution. When availability for face-to-face expert elicitation with a facilitator is limited, elicitation can be conducted remotely, overcoming challenges of finding an appropriate time to meet the expert and allowing access to experts situated too far away for practical face-to-face sessions. However, distance elicitation is associated with reduced response rates and limited assistance for the expert during the elicitation session. The aim of this study was to inform the development of a remote elicitation tool by exploring the influence of mode of elicitation on elicited beliefs. METHODS: An Excel-based tool (EXPLICIT) was developed to assist the elicitation session, including the preparation of the expert and recording of their responses. General practitioners (GPs) were invited to provide expert opinion about population alcohol consumption behaviours. They were randomised to complete the elicitation by either a face-to-face meeting or email. EXPLICIT was used in the elicitation sessions for both arms. RESULTS: Fifteen GPs completed the elicitation session. Those conducted by email were longer than the face-to-face sessions (13 min 30 s vs 10 min 26 s, p = 0.1) and the email-elicited estimates contained less uncertainty. However, the resulting aggregated distributions were comparable. CONCLUSIONS: EXPLICIT was useful in both facilitating the elicitation task and in obtaining expert opinion from experts via email. The findings support the opinion that remote, self-administered elicitation is a viable approach within the constraints of HTA to inform policy making, although poor response rates may be observed and additional time for individual sessions may be required.

A comparison of two methods for expert elicitation in health technology assessments.

BACKGROUND: When data needed to inform parameters in decision models are lacking, formal elicitation of expert judgement can be used to characterise parameter uncertainty. Although numerous methods for eliciting expert opinion as probability distributions exist, there is little research to suggest whether one method is more useful than any other method. This study had three objectives: (i) to obtain subjective probability distributions characterising parameter uncertainty in the context of a health technology assessment; (ii) to compare two elicitation methods by eliciting the same parameters in different ways; (iii) to collect subjective preferences of the experts for the different elicitation methods used. METHODS: Twenty-seven clinical experts were invited to participate in an elicitation exercise to inform a published model-based cost-effectiveness analysis of alternative treatments for prostate cancer. Participants were individually asked to express their judgements as probability distributions using two different methods - the histogram and hybrid elicitation methods - presented in a random order. Individual distributions were mathematically aggregated across experts with and without weighting. The resulting combined distributions were used in the probabilistic analysis of the decision model and mean incremental cost-effectiveness ratios and the expected values of perfect information (EVPI) were calculated for each method, and compared with the original cost-effectiveness analysis. Scores on the ease of use of the two methods and the extent to which the probability distributions obtained from each method accurately reflected the expert's opinion were also recorded. RESULTS: Six experts completed the task. Mean ICERs from the probabilistic analysis ranged between £162,600-£175,500 per quality-adjusted life year (QALY) depending on the elicitation and weighting methods used. Compared to having no information, use of expert opinion decreased decision uncertainty: the EVPI value at the £30,000 per QALY threshold decreased by 74-86 % from the original cost-effectiveness analysis. Experts indicated that the histogram method was easier to use, but attributed a perception of more accuracy to the hybrid method. CONCLUSIONS: Inclusion of expert elicitation can decrease decision uncertainty. Here, choice of method did not affect the overall cost-effectiveness conclusions, but researchers intending to use expert elicitation need to be aware of the impact different methods could have.

Do we know enough about the effect of low-dose computed tomography screening for lung cancer on mortality to act? An updated systematic review, meta-analysis and network meta-analysis of randomised controlled trials 2017 to 2021.

BACKGROUND: For people at high risk of lung cancer, low-dose computed tomography (LDCT) is proposed as a method to reduce mortality. METHODS: Our objective was to estimate the effect of LDCT lung cancer screening on mortality in high-risk populations. A systematic review of randomised controlled trials (RCTs) comparing LDCT screening programmes with usual care (no screening) or other imaging screening programme (such as chest X-ray (CXR)) was conducted. RCTs of CXR screening were additionally included in the network meta-analyses. Bibliographic sources including MEDLINE, Embase, Web of Science and the Cochrane Library were searched to January 2017, and then further extended to November 2021. All key review steps were done by two persons. Quality assessment used the Cochrane Risk of Bias tool. Meta-analyses were performed. RESULTS: Nine RCTs, with up to 12.3 years of follow-up from randomisation, were included in the direct meta-analysis, which showed that LDCT screening was associated with a statistically significant decrease in lung cancer mortality (pooled relative risk (RR) 0.86, 95% confidence interval [CI] 0.77 to 0.96). There was a statistically non-significant decrease in all-cause mortality (pooled RR 0.98, 95% CI 0.95 to 1.01). The statistical heterogeneity for both outcomes was minimal. Network meta-analysis including the nine RCTs in the direct meta-analysis plus two further RCTs comparing CXR with usual care confirmed the size of the effect of LDCT on lung cancer mortality and that this was very similar irrespective of whether the comparator was usual care or CXR screening. CONCLUSIONS: LDCT screening is effective in reducing lung cancer mortality in high-risk populations. The uncertainty of its effect on lung cancer mortality observed in 2018 has been much reduced with new trial results and updates to existing trials, emphasising the importance of updating systematic reviews. Although there are still a number of RCTs unreported or in progress, we predict that further evolution of summary mortality estimates is unlikely. The focus for debate now moves to resolving uncertainty about the cost-effectiveness of LDCT screening taking into account the balance between benefits and harms which occur in all screening programmes.

Coverage with evidence development schemes for medical devices in Europe: characteristics and challenges.

OBJECTIVES: Medical devices are potentially good candidates for coverage with evidence development (CED) schemes, as clinical data at market entry are often sparse and (cost-)effectiveness depends on real-world use. The objective of this research was to explore the diffusion of CED schemes for devices in Europe, and the factors that favour or hamper their utilization. METHODS: We conducted structured interviews with 25 decision-makers from 22 European countries to explore the characteristics of existing CED programmes for devices, and how decision makers perceived 13 pre-identified challenges associated with initiating and operating CED schemes for devices. We also collected data on individual schemes that were either initiated or still ongoing in the last 5 years. RESULTS: We identified seven countries with CED programmes for devices and 78 ongoing schemes. The characteristics of CED programmes varied across countries, including eligibility criteria, roles and responsibilities of stakeholders, funding arrangements, and type of decisions being contemplated at the outset of each scheme. We observed a high variability in how decision makers perceived CED-related challenges possibly reflecting country-specific arrangements and different experiences with CED. One general finding across all countries was that relatively little attention was paid to the evaluation of schemes, both during and at their completion. CONCLUSIONS: CED programmes for devices with different characteristics exist in Europe. Decision-makers' perceptions differ on the challenges associated with these schemes. More exchange of knowledge and experience will help decision makers anticipate the likely challenges in CED schemes for devices, and to learn from good practices existing elsewhere.

Validity of Surrogate Endpoints and Their Impact on Coverage Recommendations: A Retrospective Analysis across International Health Technology Assessment Agencies.

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.

Cancer diagnostic tools to aid decision-making in primary care: mixed-methods systematic reviews and cost-effectiveness analysis.

BACKGROUND: Tools based on diagnostic prediction models are available to help general practitioners diagnose cancer. It is unclear whether or not tools expedite diagnosis or affect patient quality of life and/or survival. OBJECTIVES: The objectives were to evaluate the evidence on the validation, clinical effectiveness, cost-effectiveness, and availability and use of cancer diagnostic tools in primary care. METHODS: Two systematic reviews were conducted to examine the clinical effectiveness (review 1) and the development, validation and accuracy (review 2) of diagnostic prediction models for aiding general practitioners in cancer diagnosis. Bibliographic searches were conducted on MEDLINE, MEDLINE In-Process, EMBASE, Cochrane Library and Web of Science) in May 2017, with updated searches conducted in November 2018. A decision-analytic model explored the tools' clinical effectiveness and cost-effectiveness in colorectal cancer. The model compared patient outcomes and costs between strategies that included the use of the tools and those that did not, using the NHS perspective. We surveyed 4600 general practitioners in randomly selected UK practices to determine the proportions of general practices and general practitioners with access to, and using, cancer decision support tools. Association between access to these tools and practice-level cancer diagnostic indicators was explored. RESULTS: Systematic review 1 - five studies, of different design and quality, reporting on three diagnostic tools, were included. We found no evidence that using the tools was associated with better outcomes. Systematic review 2 - 43 studies were included, reporting on prediction models, in various stages of development, for 14 cancer sites (including multiple cancers). Most studies relate to QCancer® (ClinRisk Ltd, Leeds, UK) and risk assessment tools. DECISION MODEL: In the absence of studies reporting their clinical outcomes, QCancer and risk assessment tools were evaluated against faecal immunochemical testing. A linked data approach was used, which translates diagnostic accuracy into time to diagnosis and treatment, and stage at diagnosis. Given the current lack of evidence, the model showed that the cost-effectiveness of diagnostic tools in colorectal cancer relies on demonstrating patient survival benefits. Sensitivity of faecal immunochemical testing and specificity of QCancer and risk assessment tools in a low-risk population were the key uncertain parameters. SURVEY: Practitioner- and practice-level response rates were 10.3% (476/4600) and 23.3% (227/975), respectively. Cancer decision support tools were available in 83 out of 227 practices (36.6%, 95% confidence interval 30.3% to 43.1%), and were likely to be used in 38 out of 227 practices (16.7%, 95% confidence interval 12.1% to 22.2%). The mean 2-week-wait referral rate did not differ between practices that do and practices that do not have access to QCancer or risk assessment tools (mean difference of 1.8 referrals per 100,000 referrals, 95% confidence interval -6.7 to 10.3 referrals per 100,000 referrals). LIMITATIONS: There is little good-quality evidence on the clinical effectiveness and cost-effectiveness of diagnostic tools. Many diagnostic prediction models are limited by a lack of external validation. There are limited data on current UK practice and clinical outcomes of diagnostic strategies, and there is no evidence on the quality-of-life outcomes of diagnostic results. The survey was limited by low response rates. CONCLUSION: The evidence base on the tools is limited. Research on how general practitioners interact with the tools may help to identify barriers to implementation and uptake, and the potential for clinical effectiveness. FUTURE WORK: Continued model validation is recommended, especially for risk assessment tools. Assessment of the tools' impact on time to diagnosis and treatment, stage at diagnosis, and health outcomes is also recommended, as is further work to understand how tools are used in general practitioner consultations. STUDY REGISTRATION: This study is registered as PROSPERO CRD42017068373 and CRD42017068375. FUNDING: This project was funded by the National Institute for Health Research (NIHR) Health Technology programme and will be published in full in Health Technology Assessment; Vol. 24, No. 66. See the NIHR Journals Library website for further project information.

In the UK, people with cancer tend to die sooner than people with cancer in other European countries. This may be because their cancers are caught at a later stage, perhaps after they have spread. Spotting cancer earlier in people, and testing them sooner, may extend people's lives. Researchers have developed 'diagnostic tools', which give the probability of having cancer, based on a patient's symptoms, blood test results and other information. The tools help family doctors decide who needs further testing for possible cancer, including cancers of the digestive, urinary and reproductive systems, and in the blood. We do not know how many family doctors have these tools, or how well the tools work. We systematically reviewed published studies about how these tools were developed, how good and accurate they are, and what effects their use has on patients. We found that many tools have been developed, but there is little evidence that they improve the quality or length of life. We sent surveys to family doctors all over the UK asking if they had the tools at their practice and if they used them. Based on the replies we received, we estimate that the tools are in about one in three practices. They are likely to be used in about half of the practices where they are available. For practices in England only, we looked for, but did not find, any association between using the tools and the number of urgent appointments made for cancer testing. We used a computer model to show what might happen if family doctors used the tools for patients who have symptoms of bowel cancer. In our model, if general practitioners used the tools, patients would need fewer appointments before they were referred to a specialist. This should reduce the time to diagnosis and treatment, compared with not using the tools. However, there is very little evidence as to whether or not this is indeed the case. Therefore, at the moment, we cannot say whether or not the use of such tools by general practitioners is better for patients and the NHS. More research is needed on what effect these tools have on patients, especially as to whether or not quality and length of life are improved.

Surrogate Endpoints in Health Technology Assessment: An International Review of Methodological Guidelines.

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.

Informing Reimbursement Decisions Using Cost-Effectiveness Modelling: A Guide to the Process of Generating Elicited Priors to Capture Model Uncertainties.

In informing decisions, utilising health technology assessment (HTA), expert elicitation can provide valuable information, particularly where there is a less-developed evidence-base at the point of market access. In these circumstances, formal methods to elicit expert judgements are preferred to improve the accountability and transparency of the decision-making process, help reduce bias and the use of heuristics, and also provide a structure that allows uncertainty to be expressed. Expert elicitation is the process of transforming the subjective and implicit knowledge of experts into their quantifiable expressions. The use of expert elicitation in HTA is gaining momentum, and there is particular interest in its application to diagnostics, medical devices and complex interventions such as in public health or social care. Compared with the gathering of experimental evidence, elicitation constitutes a reasonably low-cost source of evidence. Given its inherent subject nature, the potential biases in elicited evidence cannot be ignored and, due to its infancy in HTA, there is little guidance to the analyst wishing to conduct a formal elicitation exercise. This article attempts to summarise the stages of designing and conducting an expert elicitation, drawing on key literature and examples, most of which are not in HTA. In addition, we critique their applicability to HTA, given its distinguishing features. There are a number of issues that the analyst should be mindful of, in particular the need to appropriately characterise the uncertainty associated with model inputs and the fact that there are often numerous parameters required, not all of which can be defined using the same quantities. This increases the need for the elicitation task to be as straightforward as possible for the expert to complete.

Methods to elicit probability distributions from experts: a systematic review of reported practice in health technology assessment.

BACKGROUND: Elicitation is a technique that can be used to obtain probability distribution from experts about unknown quantities. We conducted a methodology review of reports where probability distributions had been elicited from experts to be used in model-based health technology assessments. METHODS: Databases including MEDLINE, EMBASE and the CRD database were searched from inception to April 2013. Reference lists were checked and citation mapping was also used. Studies describing their approach to the elicitation of probability distributions were included. Data was abstracted on pre-defined aspects of the elicitation technique. Reports were critically appraised on their consideration of the validity, reliability and feasibility of the elicitation exercise. RESULTS: Fourteen articles were included. Across these studies, the most marked features were heterogeneity in elicitation approach and failure to report key aspects of the elicitation method. The most frequently used approaches to elicitation were the histogram technique and the bisection method. Only three papers explicitly considered the validity, reliability and feasibility of the elicitation exercises. CONCLUSION: Judged by the studies identified in the review, reports of expert elicitation are insufficient in detail and this impacts on the perceived usability of expert-elicited probability distributions. In this context, the wider credibility of elicitation will only be improved by better reporting and greater standardisation of approach. Until then, the advantage of eliciting probability distributions from experts may be lost.