Matching the model with the evidence: comparing discrete event simulation and state-transition modeling for time-to-event predictions in a cost-effectiveness analysis of treatment in metastatic colorectal cancer patients
| Autor: | Mira D. Franken, Cornelis J. A. Punt, Maarten Joost IJzerman, Anne M. May, Miriam Koopman, Hendrik Koffijberg, Koen Degeling, Martijn G.H. van Oijen |
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| Přispěvatelé: | Oncology, APH - Methodology, APH - Quality of Care, CCA - Cancer Treatment and Quality of Life, Health Technology & Services Research |
| Jazyk: | angličtina |
| Rok vydání: | 2018 |
| Předmět: |
Matching (statistics)
Markov modeling Cancer Research Cost effectiveness Epidemiology Cost-Benefit Analysis UT-Hybrid-D Discrete event simulation Markov model 03 medical and health sciences 0302 clinical medicine Statistics State-transition modeling Medicine Humans Time-to-event 030212 general & internal medicine Event (probability theory) Parametric statistics business.industry 030503 health policy & services Cost-effectiveness analysis Transition modeling Markov Chains Oncology Individual patient data Cost-effectiveness Quality-Adjusted Life Years 0305 other medical science business Colorectal Neoplasms |
| Zdroj: | Cancer epidemiology, 57, 60-67. Elsevier BV Cancer Epidemiology, 57, 60. Elsevier BV Cancer epidemiology, 57, 60-67. Elsevier |
| ISSN: | 1877-7821 |
| Popis: | Background Individual patient data, e.g. from clinical trials, often need to be extrapolated or combined with additional evidence when assessing long-term impact in cost-effectiveness modeling studies. Different modeling methods can be used to represent the complex dynamics of clinical practice; the choice of which may impact cost-effectiveness outcomes. We compare the use of a previously designed cohort discrete-time state-transition model (DT-STM) with a discrete event simulation (DES) model. Methods The original DT-STM was replicated and a DES model developed using AnyLogic software. Models were populated using individual patient data of a phase III study in metastatic colorectal cancer patients, and compared based on their evidence structure, internal validity, and cost-effectiveness outcomes. The DT-STM used time-dependent transition probabilities, whereas the DES model was populated using parametric distributions. Results The estimated time-dependent transition probabilities for the DT-STM were irregular and more sensitive to single events due to the required small cycle length and limited number of event observations, whereas parametric distributions resulted in smooth time-to-event curves for the DES model. Although the DT-STM and DES model both yielded similar time-to-event curves, the DES model represented the trial data more accurately in terms of mean health-state durations. The incremental cost-effectiveness ratio (ICER) was €172,443 and €168,383 per Quality Adjusted Life Year gained for the DT-STM and DES model, respectively. Conclusion DES represents time-to-event data from clinical trials more naturally and accurately than DT-STM when few events are observed per time cycle. As a consequence, DES is expected to yield a more accurate ICER. |
| Databáze: | OpenAIRE |
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