IDEAS home Printed from https://ideas.repec.org/a/spr/eujhec/v21y2020i7d10.1007_s10198-020-01199-4.html
   My bibliography  Save this article

Modeling Personalized Adjuvant TreaTment in EaRly stage coloN cancer (PATTERN)

Author

Listed:
  • Gabrielle Jongeneel

    (Amsterdam UMC, VU University)

  • Marjolein J. E. Greuter

    (Amsterdam UMC, VU University)

  • Felice N. Erning

    (Netherlands Comprehensive Cancer Organization (IKNL))

  • Miriam Koopman

    (University Medical Center Utrecht, Utrecht University)

  • Jan P. Medema

    (Amsterdam UMC, University of Amsterdam)

  • Raju Kandimalla

    (Baylor Scott & White Research Institute and Charles A. Sammons Cancer Center, Baylor University Medical Center)

  • Ajay Goel

    (Baylor Scott & White Research Institute and Charles A. Sammons Cancer Center, Baylor University Medical Center)

  • Luis Bujanda

    (Universidad del País Vasco (UPV/EHU))

  • Gerrit A. Meijer

    (The Netherlands Cancer Institute)

  • Remond J. A. Fijneman

    (The Netherlands Cancer Institute)

  • Martijn G. H. Oijen

    (Amsterdam UMC, University of Amsterdam)

  • Jan Ijzermans

    (Erasmus MC University Medical Center)

  • Cornelis J. A. Punt

    (Amsterdam UMC, University of Amsterdam)

  • Geraldine R. Vink

    (Netherlands Comprehensive Cancer Organization (IKNL)
    University Medical Center Utrecht, Utrecht University)

  • Veerle M. H. Coupé

    (Amsterdam UMC, VU University)

Abstract

Aim To develop a decision model for the population-level evaluation of strategies to improve the selection of stage II colon cancer (CC) patients who benefit from adjuvant chemotherapy. Methods A Markov cohort model with a one-month cycle length and a lifelong time horizon was developed. Five health states were included; diagnosis, 90-day mortality, death other causes, recurrence and CC death. Data from the Netherlands Cancer Registry were used to parameterize the model. Transition probabilities were estimated using parametric survival models including relevant clinical and pathological covariates. Subsequently, biomarker status was implemented using external data. Treatment effect was incorporated using pooled trial data. Model development, data sources used, parameter estimation, and internal and external validation are described in detail. To illustrate the use of the model, three example strategies were evaluated in which allocation of treatment was based on (A) 100% adherence to the Dutch guidelines, (B) observed adherence to guideline recommendations and (C) a biomarker-driven strategy. Results Overall, the model showed good internal and external validity. Age, tumor growth, tumor sidedness, evaluated lymph nodes, and biomarker status were included as covariates. For the example strategies, the model predicted 83, 87 and 77 CC deaths after 5 years in a cohort of 1000 patients for strategies A, B and C, respectively. Conclusion This model can be used to evaluate strategies for the allocation of adjuvant chemotherapy in stage II CC patients. In future studies, the model will be used to estimate population-level long-term health gain and cost-effectiveness of biomarker-based selection strategies.

Suggested Citation

  • Gabrielle Jongeneel & Marjolein J. E. Greuter & Felice N. Erning & Miriam Koopman & Jan P. Medema & Raju Kandimalla & Ajay Goel & Luis Bujanda & Gerrit A. Meijer & Remond J. A. Fijneman & Martijn G. H, 2020. "Modeling Personalized Adjuvant TreaTment in EaRly stage coloN cancer (PATTERN)," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 21(7), pages 1059-1073, September.
    • Handle: RePEc:spr:eujhec:v:21:y:2020:i:7:d:10.1007_s10198-020-01199-4
    DOI: 10.1007/s10198-020-01199-4
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10198-020-01199-4
    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/s10198-020-01199-4?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. Mehmet U. S. Ayvaci & Jinghua Shi & Oguzhan Alagoz & Sam J. Lubner, 2013. "Cost-Effectiveness of Adjuvant FOLFOX and 5FU/LV Chemotherapy for Patients with Stage II Colon Cancer," Medical Decision Making, , vol. 33(4), pages 521-532, May.
    2. Robert R J Coebergh van den Braak & Anieta M Sieuwerts & Raju Kandimalla & Zarina S Lalmahomed & Sandra I Bril & Anne van Galen & Marcel Smid & Katharina Biermann & J Han J M van Krieken & Wigard P Kl, 2017. "High mRNA expression of splice variant SYK short correlates with hepatic disease progression in chemonaive lymph node negative colon cancer patients," PLOS ONE, Public Library of Science, vol. 12(9), pages 1-18, September.
    3. K. Ishak & Noemi Kreif & Agnes Benedict & Noemi Muszbek, 2013. "Overview of Parametric Survival Analysis for Health-Economic Applications," PharmacoEconomics, Springer, vol. 31(8), pages 663-675, August.
    4. Jackson, Christopher, 2016. "flexsurv: A Platform for Parametric Survival Modeling in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 70(i08).
    5. Mathilda L. Bongers & Dirk de Ruysscher & Cary Oberije & Philippe Lambin & Carin A. Uyl–de Groot & V. M. H. Coupé, 2016. "Multistate Statistical Modeling," Medical Decision Making, , vol. 36(1), pages 86-100, January.
    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. Elizabeth G Bond & Lusine Abrahamyan & Mohammad K A Khan & Andrea Gershon & Murray Krahn & Ping Li & Rajibul Mian & Nicholas Mitsakakis & Mohsen Sadatsafavi & Teresa To & Petros Pechlivanoglou & for t, 2020. "Understanding resource utilization and mortality in COPD to support policy making: A microsimulation study," PLOS ONE, Public Library of Science, vol. 15(8), pages 1-16, August.
    2. K. Ishak & Irina Proskorovsky & Agnes Benedict, 2015. "Simulation and Matching-Based Approaches for Indirect Comparison of Treatments," PharmacoEconomics, Springer, vol. 33(6), pages 537-549, June.
    3. Sharples, Linda D., 2018. "The role of statistics in the era of big data: Electronic health records for healthcare research," Statistics & Probability Letters, Elsevier, vol. 136(C), pages 105-110.
    4. Suvra Pal & Hongbo Yu & Zachary D. Loucks & Ian M. Harris, 2020. "Illustration of the Flexibility of Generalized Gamma Distribution in Modeling Right Censored Survival Data: Analysis of Two Cancer Datasets," Annals of Data Science, Springer, vol. 7(1), pages 77-90, March.
    5. Michael Crowther & Paul Lambert, 2016. "Multistate survival analysis in Stata," United Kingdom Stata Users' Group Meetings 2016 02, Stata Users Group.
    6. I. Oostrum & T. A. Russell-Smith & M. Jakobsson & J. Torup Østby & B. Heeg, 2022. "Cost-Effectiveness of Inotuzumab Ozogamicin Compared to Standard of Care Chemotherapy for Treating Relapsed or Refractory Acute Lymphoblastic Leukaemia Patients in Norway and Sweden," PharmacoEconomics - Open, Springer, vol. 6(1), pages 47-62, January.
    7. Caitlin Eichten & Qiufei Ma & Thomas E. Delea & May Hagiwara & Roberto Ramos & Şerban R. Iorga & Jie Zhang & Richard T. Maziarz, 2021. "Lifetime Costs for Treated Follicular Lymphoma Patients in the US," PharmacoEconomics, Springer, vol. 39(10), pages 1163-1183, October.
    8. Linh Hoang Khanh Dang & Carlo Giovanni Camarda & France Meslé & Nadine Ouellette & Jean-Marie Robine & Jacques Vallin, 2023. "The question of the human mortality plateau: Contrasting insights by longevity pioneers," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 48(11), pages 321-338.
    9. María del Mar Rueda & Sergio Martínez-Puertas & Luis Castro-Martín, 2022. "Methods to Counter Self-Selection Bias in Estimations of the Distribution Function and Quantiles," Mathematics, MDPI, vol. 10(24), pages 1-19, December.
    10. Camarda, Carlo Giovanni, 2022. "The curse of the plateau. Measuring confidence in human mortality estimates at extreme ages," Theoretical Population Biology, Elsevier, vol. 144(C), pages 24-36.
    11. Eberechukwu Onukwugha & Jason Bergtold & Rahul Jain, 2015. "A Primer on Marginal Effects—Part I: Theory and Formulae," PharmacoEconomics, Springer, vol. 33(1), pages 25-30, January.
    12. John W. Stevens, 2018. "Using Evidence from Randomised Controlled Trials in Economic Models: What Information is Relevant and is There a Minimum Amount of Sample Data Required to Make Decisions?," PharmacoEconomics, Springer, vol. 36(10), pages 1135-1141, October.
    13. Jodi Gray & Thomas Sullivan & Nicholas R. Latimer & Amy Salter & Michael J. Sorich & Robyn L. Ward & Jonathan Karnon, 2021. "Extrapolation of Survival Curves Using Standard Parametric Models and Flexible Parametric Spline Models: Comparisons in Large Registry Cohorts with Advanced Cancer," Medical Decision Making, , vol. 41(2), pages 179-193, February.
    14. Kevin Marsh & Peng Xu & Panagiotis Orfanos & Agnes Benedict & Kamal Desai & Ingolf Griebsch, 2014. "Model-Based Cost-Effectiveness Analyses for the Treatment of Chronic Myeloid Leukaemia: A Review and Summary of Challenges," PharmacoEconomics, Springer, vol. 32(9), pages 853-864, September.
    15. Carmen María Yago & Francisco Javier Díez, 2023. "DESnets: A Graphical Representation for Discrete Event Simulation and Cost-Effectiveness Analysis," Mathematics, MDPI, vol. 11(7), pages 1-24, March.
    16. Philip Cooney & Arthur White, 2023. "Direct Incorporation of Expert Opinion into Parametric Survival Models to Inform Survival Extrapolation," Medical Decision Making, , vol. 43(3), pages 325-336, April.
    17. Sandjar Djalalov & Jaclyn Beca & Emmanuel M. Ewara & Jeffrey S. Hoch, 2019. "A Comparison of Different Analysis Methods for Reconstructed Survival Data to Inform Cost‑Effectiveness Analysis," PharmacoEconomics, Springer, vol. 37(12), pages 1525-1536, December.
    18. Stavroula A Chrysanthopoulou, 2017. "MILC: A Microsimulation Model of the Natural History of Lung Cancer," International Journal of Microsimulation, International Microsimulation Association, vol. 10(3), pages 5-26.
    19. Xiaomin Wan & Liubao Peng & Yuanjian Li, 2015. "A Review and Comparison of Methods for Recreating Individual Patient Data from Published Kaplan-Meier Survival Curves for Economic Evaluations: A Simulation Study," PLOS ONE, Public Library of Science, vol. 10(3), pages 1-21, March.
    20. Burger, Rulof & Ito, Seiro, 2016. "Labour market turnovers among South African youths," IDE Discussion Papers 603, Institute of Developing Economies, Japan External Trade Organization(JETRO).

    More about this item

    Keywords

    Colon cancer; Adjuvant chemotherapy; Markov cohort model; Survival analysis;
    All these keywords.

    JEL classification:

    • D61 - Microeconomics - - Welfare Economics - - - Allocative Efficiency; Cost-Benefit Analysis
    • I19 - Health, Education, and Welfare - - Health - - - Other

    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:eujhec:v:21:y:2020:i:7:d:10.1007_s10198-020-01199-4. 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.