The NICE Diagnostics Assessment Programme

Crabb, Nick; Marlow, Mirella; Bell, Hanan; Newland, Adrian C.

doi:10.1016/j.hlpt.2012.01.005

Cited by 8 publications

(7 citation statements)

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“…It is well recognized, however, that there is a need for well-structured economic assessment to provide robust data on the potential added value of the technology providing the personalized approach to medicine. This need for methodological scrutiny in the economic assessment of personalized medicine is consistent with any evaluation of a health care technology, and there are up to now very few specific guidelines available for the economic assessment of personalized medicine (for an example of a work in progress, see National Institute for Health and Care Excellence's [NICE's] Diagnostics Assessment Programme) [1]. This lack of specific guidance may be viewed to be appropriate given the same evaluative framework is likely to be generally applicable to identify and quantify the incremental costs and benefits of a technology that personalizes medicine.…”

Section: Introductionmentioning

confidence: 91%

“…medicine may introduce additional levels of complexity. In the United Kingdom, NICE has acknowledged the potential complexity that the evaluation of a diagnostics poses by the introduction of a discrete appraisal process, the Diagnostics Assessment Programme, for complex diagnostics [1]. Currently, companion diagnostic medicines will continue to be appraised using the NICE Technology Appraisal process with a focus on the added value of the targeted medicine component.…”

Section: Test Characteristics Should Be Translated Into Clinical Utilitymentioning

confidence: 99%

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Current Methodological Issues in the Economic Assessment of Personalized Medicine

2013

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There is a need for methodological scrutiny in the economic assessment of personalized medicine. In this article, we present a list of 10 specific issues that we argue pose specific methodological challenges that require careful consideration when designing and conducting robust model-based economic evaluations in the context of personalized medicine. Key issues are related to the correct framing of the research question, interpretation of test results, data collection of medical management options after obtaining test results, and expressing the value of tests. The need to formulate the research question clearly and be explicit and specific about the technology being evaluated is essential because various test kits can have the same purpose and yet differ in predictive value, costs, and relevance to practice and patient populations. The correct reporting of sensitivity/specificity, and especially the false negatives and false positives (which are population dependent), of the investigated tests is also considered as a key element. This requires additional structural complexity to establish the relationship between the test result and the consecutive treatment changes and outcomes. This process involves translating the test characteristics into clinical utility, and therefore outlining the clinical and economic consequences of true and false positives and true and false negatives. Information on treatment patterns and on their costs and outcomes, however, is often lacking, especially for false-positive and false-negative test results. The analysis can even become very complex if different tests are combined or sequentially used. This potential complexity can be handled by explicitly showing how these tests are going to be used in practice and then working with the combined sensitivities and specificities of the tests. Each of these issues leads to a higher degree of uncertainty in economic models designed to assess the added value of personalized medicine compared with their simple pharmaceutical counterparts. To some extent, these problems can be overcome by performing early population-level simulations, which can lead to the identification and collection of data on critical input parameters. Finally, it is important to understand that a test strategy does not necessarily lead to more quality-adjusted life-years (QALYs). It is possible that the test will lead to not only fewer QALYs but also fewer costs, which can be defined as "decremental" cost per QALYs. Different decision criteria are needed to interpret such results.

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Section: Introductionmentioning

confidence: 91%

Section: Test Characteristics Should Be Translated Into Clinical Utilitymentioning

confidence: 99%

Current Methodological Issues in the Economic Assessment of Personalized Medicine

2013

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“…Within the jurisdictions of the FDA and other national regulatory authorities (Crabb, Marlow, Bell, & Newland, 2012), a companion diagnostic device with a particular therapeutic product is "stipulated in the instructions for use in the labeling of both the diagnostic device and the corresponding therapeutic product, as well as in the labeling of any generic equivalents and biosimilar equivalents of the therapeutic product" (FDA, 2015a). This means that the Companion Diagnostic test must be performed before a new partner therapeutic can be prescribed.…”

Section: Companion Diagnosticsmentioning

confidence: 99%

“…Around 30% of breast cancer patients express EGF receptor 2 and thus may benefit from this biological drug. The HER2 test was approved in 1999 by the FDA (Roche & Ingle, 1999), and then by NICE (Crabb et al, 2012) and other regulatory agencies, as a companion diagnostic for use with trastuzumab as the companion therapeutic agent: the first example of formal regulatory licensing of a companion diagnostic. The Cochrane Collaboration publishes secondary research on treatment outcomes.…”

Section: Egf Receptor 2 Antagonism With Trastuzmabmentioning

confidence: 99%

Clinical Perspectives on Targeting Therapies for Personalized Medicine

Singer

Zaïr

2016

Advances in Protein Chemistry and Structural Biology

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Expected benefits from new technology include more efficient patient selection for clinical trials, more cost-effective treatment pathways for patients and health services and a more profitable accelerated approach for drug developers. Regulatory authorities expect the pharmaceutical and biotechnology industries to accelerate their development of companion diagnostics and companion therapeutics toward the goal of safer and more effective personalized medicine, and expect health services to fund and prescribers to adopt these new therapeutic technologies. This review discusses the importance of a range of new approaches to developing new and reprofiled medicines to treat common and serious diseases, and rare diseases: new network pharmacology approaches, adaptive trial designs with enriched populations more likely to respond safely to treatment, as assessed by companion diagnostics for response and toxicity risk and use of "real world" data. Case studies are described of single and multiple protein drug targets in several important therapeutic areas. These case studies also illustrate the value and complexity of use of selective biomarkers of clinical response and risk of adverse drug effects, either singly or in combination.

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“…The first issue illustrates our ambition, in including a paper by Crabb [3] on the pioneering new Centre for Health Technology Assessment of Devices and Diagnostics within the UK's National Institute for Health and Clinical Excellence (NICE) [4]. There is a pressing need to improve the evidence base and evidence synthesis for medical diagnostics and devices, many of which lack rigorous data on their clinical and cost-effectiveness.…”

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confidence: 99%

Health Policy and Technology and the Fellowship of Postgraduate Medicine

Singer¹

2012

Health Policy and Technology

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The NICE Diagnostics Assessment Programme

Cited by 8 publications

References 0 publications

Current Methodological Issues in the Economic Assessment of Personalized Medicine

Current Methodological Issues in the Economic Assessment of Personalized Medicine

Clinical Perspectives on Targeting Therapies for Personalized Medicine

Health Policy and Technology and the Fellowship of Postgraduate Medicine

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