Imperial College London

Dr Kelly Seo

Faculty of MedicineDepartment of Surgery & Cancer

Honorary Research Associate
 
 
 
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Contact

 

mk.seo

 
 
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Location

 

Sir Alexander Fleming BuildingSouth Kensington Campus

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Summary

 

Publications

Publication Type
Year
to

13 results found

Angelis A, Harker M, Cairns J, Seo MK, Legood R, Miners A, Wiseman V, Chalkidou K, Grieve R, Briggs Aet al., 2023, The Evolving Nature of Health Technology Assessment: A Critical Appraisal of NICE's New Methods Manual, VALUE IN HEALTH, Vol: 26, Pages: 1503-1509, ISSN: 1098-3015

Journal article

Luis ABD, Seo MK, 2022, Reply to comment on "Demonstrating the value of cancer biomarkers at the population" REPLY, EUROPEAN JOURNAL OF HEALTH ECONOMICS, Vol: 23, Pages: 757-758, ISSN: 1618-7598

Journal article

Seo MK, Strong M, 2021, A Practical Guide to Modeling and Conducting a Cost-Effectiveness Analysis of Companion Biomarker Tests for Targeted Therapies Using R: Tutorial Paper., Pharmacoeconomics, Vol: 39, Pages: 1373-1381

Despite the increasing number of potential biomarkers identified in laboratories and reported in much literature, the adoption of biomarkers routinely available in clinical practice to inform treatment decisions is very limited. Reimbursement decisions for new health technologies are often informed by economic evaluations; however, economic evaluations of diagnostics/testing technologies, such as companion biomarker tests, are far less frequently reported than drugs. Furthermore, few countries provide the health economic evaluation methods guide specific to co-dependent technologies such as companion diagnostics or precision medicines. Therefore, this paper aims to guide the process of the development of cost-effectiveness models of cancer biomarkers for targeted therapies, focusing on companion diagnostics. This tutorial paper provides practical guidance on how to conduct economic evaluations of cancer biomarkers and how to model the characteristics of the biomarker tests as part of the value for money of corresponding targeted therapies. This paper presents a brief introduction to the methods and data requirements, a step-by-step guide to constructing a health economic model of companion cancer biomarkers, and a discussion of issues that arise in their application to healthcare decision making. This practical guidance is provided in R, and worked examples are provided in this paper with R codes in the accompanying electronic supplementary material.

Journal article

Seo MK, Cairns J, 2021, How are we evaluating the cost-effectiveness of companion biomarkers for targeted cancer therapies? A systematic review., BMC cancer, Vol: 21, ISSN: 1471-2407

<h4>Background</h4>Despite the increasing economic assessment of biomarker-guided therapies, no clear agreement exists whether existing methods are sufficient or whether different methods might produce different cost-effectiveness results. This study aims to examine current practices of modeling companion biomarkers when assessing the cost-effectiveness of targeted cancer therapies. It investigates the current methods in modeling the characteristics of companion diagnostics based on existing economic evaluations of biomarker-guided therapies in cancer.<h4>Methods</h4>A literature search was performed using Medline, Embase, EconLit, Cochrane library for economic evaluations of biomarker-guided therapies with companion diagnostics in cancer. Preferred Reporting Items of Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed. Studies were selected using pre-specified eligibility criteria based on the PICO framework. To make the included studies more comparable, we qualitatively synthesized the data under nine domains of methods where consensus was deemed lacking.<h4>Results</h4>Only four of the twenty-two studies included in this review were found to be of good quality with respect to incorporating the characteristics of companion biomarkers in economic evaluations. However, many evaluations focused on a pre-selected patient group rather than including all patients regardless of their biomarker status. Companion biomarker characteristics captured in evaluations were often limited to the cost or the accuracy of the test. Often, only the costs of biomarker testing were modelled. Clinical outcomes and health state utilities were often not included due to the limited data generated by clinical trials. Methods of economic evaluation were not applied consistently in assessments of companion cancer biomarkers for targeted therapies. It was also shown that conflicting cost-effectiveness results were likely depending on what c

Journal article

Luis ABD, Seo MK, 2021, Has the development of cancer biomarkers to guide treatment improved health outcomes?, EUROPEAN JOURNAL OF HEALTH ECONOMICS, Vol: 22, Pages: 789-810, ISSN: 1618-7598

Journal article

Micocci M, Gordon AL, Seo MK, Allen AJ, Davies K, Lasserson D, Thompson C, Spilsbury K, Akrill C, Heath R, Astle A, Sharpe C, Perera R, Hayward G, Buckle Pet al., 2021, Is point-of-care testing feasible and safe in care homes in England? An exploratory usability and accuracy evaluation of a point-of-care polymerase chain reaction test for SARS-CoV-2, Age and Ageing, Vol: 50, Pages: 1464-1472, ISSN: 0002-0729

IntroductionReliable rapid testing for COVID-19 is needed in care homes to reduce the risk of outbreaks and enable timely care. This study aimed to examine the usability and test performance of a point of care polymerase chain reaction (PCR) test for detection of SARS-CoV-2 (POCKITTM Central) in care homes.MethodsPOCKITTM Central was evaluated in a purposeful sample of four UK care homes. Test agreement with laboratory real-time PCR and usability and used errors were assessed.ResultsNo significant usability-related hazards emerged, and the sources of error identified were found to be amendable with minor changes in training or test workflow. POCKITTM Central has acceptable sensitivity and specificity based on RT-PCR as the reference standard, especially for symptomatic cases.Asymptomatic specimens showed 83.3% (95% confidence interval (CI): 35.9–99.6%) positive agreement and 98.7% negative agreement (95% CI: 96.2–99.7%), with overall prevalence and bias-adjusted kappa (PABAK) of 0.965 (95% CI: 0.932– 0.999). Symptomatic specimens showed 100% (95% CI: 2.5–100%) positive agreement and 100% negative agreement (95% CI: 85.8–100%), with overall PABAK of 1.Recommendations are provided to mitigate the frequency of occurrence of the residual use errors observed. Integration pathways were discussed to identify opportunities and limitations of adopting POCKIT™ Central for screening and diagnostic testing purposes.ConclusionsPoint-of-care PCR testing in care homes can be considered with appropriate preparatory steps and safeguards. Further diagnostic accuracy evaluations and in-service evaluation studies should be conducted, if the test is to be implemented more widely, to build greater certainty on this initial exploratory analysis.

Journal article

Seo MK, Straume O, Akslen LA, Cairns Jet al., 2020, HSP27 Expression as a Novel Predictive Biomarker for Bevacizumab: is it Cost Effective?, PHARMACOECONOMICS-OPEN, Vol: 4, Pages: 529-539, ISSN: 2509-4262

Journal article

Seo MK, 2019, How are we assessing the value for money of cancer biomarkers in economic evaluations?, Value in Health, ISPOR Europe 2019

Conference paper

Seo MK, Cairns J, 2018, Do cancer biomarkers make targeted therapies cost-effective? A systematic review in metastatic colorectal cancer., PLoS One, Vol: 13, Pages: 1-23, ISSN: 1932-6203

BACKGROUND: Recent advances in targeted therapies have raised expectations that the clinical application of biomarkers would improve patient's health outcomes and potentially save costs. However, the cost-effectiveness of biomarkers remains unclear irrespective of the cost-effectiveness of corresponding therapies. It is thus important to determine whether biomarkers for targeted therapies provide good value for money. This study systematically reviews economic evaluations of biomarkers for targeted therapies in metastatic colorectal cancer (mCRC) and assesses the cost-effectiveness of predictive biomarkers in mCRC. METHODS: A literature search was performed using Medline, Embase, EconLit, NHSEED. Papers published from 2000 until June 2018 were searched. All economic evaluations assessing biomarker-guided therapies with companion diagnostics in mCRC were searched. To make studies more comparable, cost-effectiveness results were synthesized as per biomarker tests and corresponding therapies. Methodological quality was assessed using the Quality of Health Economic Studies (QHES) instrument. RESULTS: Forty-six studies were included in this review. Of these, 17 studies evaluated the intrinsic value of cancer biomarkers, whereas the remaining studies focused on assessing the cost-effectiveness of corresponding drugs. Most studies indicated favourable cost-effectiveness of biomarkers for targeted therapies in mCRC. Some studies reported that biomarkers were cost-effective, while their corresponding therapies were not cost-effective. A considerable number of economic evaluations were conducted in pre-defined genetic populations and thus, often failed to fully capture the biomarker's clinical and economic values. The average QHES score was 73.6. CONCLUSION: Cancer biomarkers for targeted therapies in mCRC were mostly found to be cost-effective; otherwise, they at least improved the cost-effectiveness of targeted therapies by saving some costs. However, this did not necessari

Journal article

Blanchard A, Wik E, Seo MK, Cairns J, Tranvåg E, Norheim OF, Fleck LM, Blasimme A, Engen C, Strand Ret al., 2017, Cancer Biomarkers Ethics, Economics and Society, Publisher: Megaloceros Forlag, ISBN: 9788291851044

This book reflects upon the promise of cancer biomarkers and asks questions such as: How may the complexity of cancer biology impede the robustness of biomarkers in the clinic?

Book

Seo MK, 2017, Economic evaluations of cancer biomarkers for targeted therapies: practices, challenges, and policy implications, Cancer biomarkers: ethics, economics and society, Editors: Blanchard, Strand, Publisher: Megaloceros Press, 2017. p.25-38.

With the increased knowledge in genetics and molecular biology, healthcare providers can be guided by biomarker tests when making clinical decisions regarding treatment. These advances have raised expectations over personalised medicine or precision medicine, which aims to provide the right treatment to the right patient. It is thus argued that cancer biomarkers for targeted therapies will eventually improve patient outcomes and help to achieve resource allocation efficiency in healthcare. However, there is widespread scepticism about the research and development (R&D) of biomarkers and personalised medicine because the number of biomarkers successfully entering into the clinical routine is very low compared to the number of biomarkers published. It implies a significant time-lag between the pace of rapidly evolving medical technologies and the actual use in clinical practice. Such lagged integration may potentially delay the improvement of patient outcomes or may harm patients unresponsive to the corresponding therapies. Therefore, it is of public interest to ensure the timely integration of new technologies into clinical use through adequate levels of reimbursement and coverage. However, it requires that test developers demonstrate robust evidence of the health economic impact of biomarkers for targeted therapies. This chapter discusses current methodological approaches and challenges in conducting economic evaluations of cancer biomarkers and the complexity of evidence generation faced by test developers without clear guidance on evidentiary standards and data requirements. It then discusses some implications for regulatory and reimbursement bodies. Although some of the issues could be better addressed by other fields (for example, the clinical utility of biomarker testing), a consensus on methodological approaches and data requirements for economic evaluations of cancer biomarkers needs to be reached in the field of health economics. Currently, no agreement

Book chapter

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