IDEAS home Printed from https://ideas.repec.org/a/spr/aphecp/v23y2025i3d10.1007_s40258-024-00926-9.html
   My bibliography  Save this article

Using Genomic Heterogeneity to Inform Therapeutic Decisions for Metastatic Colorectal Cancer: An Application of the Value of Heterogeneity Framework

Author

Listed:
  • Reka E. Pataky

    (Canadian Centre for Applied Research in Cancer Control, BC Cancer
    BC Cancer Research Centre)

  • Stuart Peacock

    (Canadian Centre for Applied Research in Cancer Control, BC Cancer
    Simon Fraser University)

  • Stirling Bryan

    (Vancouver Coastal Health Research Institute
    The University of British Columbia)

  • Mohsen Sadatsafavi

    (The University of British Columbia)

  • Dean A. Regier

    (Canadian Centre for Applied Research in Cancer Control, BC Cancer
    The University of British Columbia)

Abstract

Background and Objective Mutations in KRAS and NRAS are predictive of poor response to cetuximab and panitumumab, two anti-epidermal growth factor receptor (EGFR) monoclonal antibodies used in metastatic colorectal cancer (mCRC). Our objective was to explore the value of using KRAS and NRAS mutation status to inform third-line anti-EGFR therapy for mCRC using the value of heterogeneity (VOH) framework. Methods We used administrative data to identify mCRC patients who were potentially eligible for third-line therapy in 2006–2019 in British Columbia (BC), Canada. We compared three alternative stratification policies in place during the study period: the unstratified policy where anti-EGFR therapy was not offered (2006–2009), stratification by KRAS mutation (2009–2016), and stratification by KRAS+NRAS mutation (2016–2019). We used inverse-probability-of-treatment weighting to balance covariates across the three groups. Cost and survival time were calculated using a 3-year time horizon and adjusted for censoring, with bootstrapping to characterize uncertainty. Mean net monetary benefit (NMB) was calculated at a range of threshold values. The VOH of using KRAS and NRAS mutation status to inform treatment selection was calculated as the change in NMB with increasing stratification, under current (static VOH) or perfect (dynamic VOH) information. Results We included 2664 patients in the analysis. At a willingness-to-pay of CA$100,000/ life-year gained (LYG), stratification on KRAS mutation status provided a static VOH of CA$1565 per patient; further stratification on KRAS+NRAS provided additional static VOH of CA$594. The static VOH exceeded the marginal cost of genomic testing under both policies. Conclusions Stratification of anti-EGFR therapy by KRAS and NRAS mutation status can provide additional value at a threshold of CA$100,000/LYG. There is diminishing marginal value and increasing marginal costs as the policy becomes more stratified. The VOH framework can illustrate the value of subgroup-specific decisions in a comprehensive way, to better inform targeted treatment policies.

Suggested Citation

  • Reka E. Pataky & Stuart Peacock & Stirling Bryan & Mohsen Sadatsafavi & Dean A. Regier, 2025. "Using Genomic Heterogeneity to Inform Therapeutic Decisions for Metastatic Colorectal Cancer: An Application of the Value of Heterogeneity Framework," Applied Health Economics and Health Policy, Springer, vol. 23(3), pages 441-452, May.
  • Handle: RePEc:spr:aphecp:v:23:y:2025:i:3:d:10.1007_s40258-024-00926-9
    DOI: 10.1007/s40258-024-00926-9
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s40258-024-00926-9
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s40258-024-00926-9?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. David D. Kim & Anirban Basu, 2017. "New Metrics for Economic Evaluation in the Presence of Heterogeneity: Focusing on Evaluating Policy Alternatives Rather than Treatment Alternatives," Medical Decision Making, , vol. 37(8), pages 930-941, November.
    2. Jeffrey S. Hoch & Andrew H. Briggs & Andrew R. Willan, 2002. "Something old, something new, something borrowed, something blue: a framework for the marriage of health econometrics and cost‐effectiveness analysis," Health Economics, John Wiley & Sons, Ltd., vol. 11(5), pages 415-430, July.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Qi Cao & Erik Buskens & Hans L. Hillege & Tiny Jaarsma & Maarten Postma & Douwe Postmus, 2019. "Stratified treatment recommendation or one-size-fits-all? A health economic insight based on graphical exploration," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 20(3), pages 475-482, April.
    2. Abualbishr Alshreef & Allan J. Wailoo & Steven R. Brown & James P. Tiernan & Angus J. M. Watson & Katie Biggs & Mike Bradburn & Daniel Hind, 2017. "Cost-Effectiveness of Haemorrhoidal Artery Ligation versus Rubber Band Ligation for the Treatment of Grade II–III Haemorrhoids: Analysis Using Evidence from the HubBLe Trial," PharmacoEconomics - Open, Springer, vol. 1(3), pages 175-184, September.
    3. Jasjeet Singh Sekhon & Richard D. Grieve, 2012. "A matching method for improving covariate balance in cost‐effectiveness analyses," Health Economics, John Wiley & Sons, Ltd., vol. 21(6), pages 695-714, June.
    4. Andrea Manca & Neil Hawkins & Mark J. Sculpher, 2005. "Estimating mean QALYs in trial‐based cost‐effectiveness analysis: the importance of controlling for baseline utility," Health Economics, John Wiley & Sons, Ltd., vol. 14(5), pages 487-496, May.
    5. A. Gafni & S. D. Walter & S. Birch & P. Sendi, 2008. "An opportunity cost approach to sample size calculation in cost‐effectiveness analysis," Health Economics, John Wiley & Sons, Ltd., vol. 17(1), pages 99-107, January.
    6. John Hutton, 2012. "‘Health Economics’ and the evolution of economic evaluation of health technologies," Health Economics, John Wiley & Sons, Ltd., vol. 21(1), pages 13-18, January.
    7. Christian Brettschneider & Sebastian Kohlmann & Benjamin Gierk & Bernd Löwe & Hans-Helmut König, 2017. "Depression screening with patient-targeted feedback in cardiology: The cost-effectiveness of DEPSCREEN-INFO," PLOS ONE, Public Library of Science, vol. 12(8), pages 1-15, August.
    8. Rissanen, Elisa & Karjalainen, Piia & Kiviruusu, Olli & Kankaanpää, Eila & Aronen, Eeva T. & Haula, Taru & Sääksvuori, Lauri & Vornanen, Riitta & Linnosmaa, Ismo, 2024. "Cost-effectiveness of a parenting program to reduce children’s behavioral problems among families receiving child protection services and other family support services – A randomized controlled trial," Children and Youth Services Review, Elsevier, vol. 158(C).
    9. Claudia Schulz & Gisela Büchele & Raphael S. Peter & Dietrich Rothenbacher & Christian Brettschneider & Ulrich C. Liener & Clemens Becker & Kilian Rapp & Hans-Helmut König, 2021. "Health-economic evaluation of collaborative orthogeriatric care for patients with a hip fracture in Germany: a retrospective cohort study using health and long-term care insurance claims data," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 22(6), pages 873-885, August.
    10. Wanrudee Isaranuwatchai & Maureen Markle-Reid & Jeffrey Hoch, 2015. "Adjusting for Baseline Covariates in Net Benefit Regression: How You Adjust Matters," PharmacoEconomics, Springer, vol. 33(10), pages 1083-1090, October.
    11. Ya-Chen Shih & Nebiyou Bekele & Ying Xu, 2007. "Use of Bayesian Net Benefit Regression Model to Examine the Impact of Generic Drug Entry on the Cost Effectiveness of Selective Serotonin Reuptake Inhibitors in Elderly Depressed Patients," PharmacoEconomics, Springer, vol. 25(10), pages 843-862, October.
    12. Richard M. Nixon & David Wonderling & Richard D. Grieve, 2010. "Non‐parametric methods for cost‐effectiveness analysis: the central limit theorem and the bootstrap compared," Health Economics, John Wiley & Sons, Ltd., vol. 19(3), pages 316-333, March.
    13. Lukasz Tanajewski & Matthew Franklin & Georgios Gkountouras & Vladislav Berdunov & Judi Edmans & Simon Conroy & Lucy E Bradshaw & John R F Gladman & Rachel A Elliott, 2015. "Cost-Effectiveness of a Specialist Geriatric Medical Intervention for Frail Older People Discharged from Acute Medical Units: Economic Evaluation in a Two-Centre Randomised Controlled Trial (AMIGOS)," PLOS ONE, Public Library of Science, vol. 10(5), pages 1-18, May.
    14. Richard Grieve & John Cairns & Simon G. Thompson, 2010. "Improving costing methods in multicentre economic evaluation: the use of multiple imputation for unit costs," Health Economics, John Wiley & Sons, Ltd., vol. 19(8), pages 939-954, August.
    15. Andrew H. Briggs, 2022. "Healing the past, reimagining the present, investing in the future: What should be the role of race as a proxy covariate in health economics informed health care policy?," Health Economics, John Wiley & Sons, Ltd., vol. 31(10), pages 2115-2119, October.
    16. Carmen Selva-Sevilla & Elena Conde-Montero & Manuel Gerónimo-Pardo, 2020. "Bayesian Regression Model for a Cost-Utility and Cost-Effectiveness Analysis Comparing Punch Grafting Versus Usual Care for the Treatment of Chronic Wounds," IJERPH, MDPI, vol. 17(11), pages 1-21, May.
    17. DE RIDDER, Annemieke & DE GRAEVE, Diana, 2007. "Comparing the cost-effectiveness of Haloperidol, Risperidone and Olanzapine in the treatment of schizophrenia using the net-benefit regression approach," Working Papers 2007012, University of Antwerp, Faculty of Business and Economics.
    18. William Hollingworth & Christopher G. Fawsitt & Padraig Dixon & Larisa Duffy & Ricardo Araya & Tim J. Peters & Howard Thom & Nicky J. Welton & Nicola Wiles & Glyn Lewis, 2020. "Cost-Effectiveness of Sertraline in Primary Care According to Initial Severity and Duration of Depressive Symptoms: Findings from the PANDA RCT," PharmacoEconomics - Open, Springer, vol. 4(3), pages 427-438, September.
    19. Todd H. Wagner & Jean Yoon & Josephine C. Jacobs & Angela So & Amy M. Kilbourne & Wei Yu & David E. Goodrich, 2020. "Estimating Costs of an Implementation Intervention," Medical Decision Making, , vol. 40(8), pages 959-967, November.
    20. Nicholas Graves & Mary Courtney & Helen Edwards & Anne Chang & Anthony Parker & Kathleen Finlayson, 2009. "Cost-Effectiveness of an Intervention to Reduce Emergency Re-Admissions to Hospital among Older Patients," PLOS ONE, Public Library of Science, vol. 4(10), pages 1-9, October.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:aphecp:v:23:y:2025:i:3:d:10.1007_s40258-024-00926-9. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.