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

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. Oijen, Jan Ijzermans, Cornelis J. A. Punt, Geraldine R. Vink and Veerle M. H. Coupé
Additional contact information
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)
Veerle M. H. Coupé: Amsterdam UMC, VU University

The European Journal of Health Economics, 2020, vol. 21, issue 7, No 9, 1059-1073

Abstract: 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.

Keywords: Colon cancer; Adjuvant chemotherapy; Markov cohort model; Survival analysis (search for similar items in EconPapers)
JEL-codes: D61 I19 (search for similar items in EconPapers)
Date: 2020
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DOI: 10.1007/s10198-020-01199-4

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