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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
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    References listed on IDEAS

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    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.
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    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

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