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Time-to-event analysis in economic evaluations: a comparison of modelling methods to assess the cost-effectiveness of transplanting a marginal quality kidney

Sameera Senanayake (), Nicholas Graves, Helen Healy, Keshwar Baboolal, Adrian Barnett and Sanjeewa Kularatna
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Sameera Senanayake: Queensland University of Technology (QUT)
Nicholas Graves: Duke-NUS Medical School
Helen Healy: Royal Brisbane Hospital for Women
Keshwar Baboolal: Royal Brisbane Hospital for Women
Adrian Barnett: Queensland University of Technology (QUT)
Sanjeewa Kularatna: Queensland University of Technology (QUT)

Health Economics Review, 2021, vol. 11, issue 1, 1-12

Abstract: Abstract Background Economic-evaluations using decision analytic models such as Markov-models (MM), and discrete-event-simulations (DES) are high value adds in allocating resources. The choice of modelling method is critical because an inappropriate model yields results that could lead to flawed decision making. The aim of this study was to compare cost-effectiveness when MM and DES were used to model results of transplanting a lower-quality kidney versus remaining waitlisted for a kidney. Methods Cost-effectiveness was assessed using MM and DES. We used parametric survival models to estimate the time-dependent transition probabilities of MM and distribution of time-to-event in DES. MMs were simulated in 12 and 6 monthly cycles, out to five and 20-year time horizon. Results DES model output had a close fit to the actual data. Irrespective of the modelling method, the cycle length of MM or the time horizon, transplanting a low-quality kidney as compared to remaining waitlisted was the dominant strategy. However, there were discrepancies in costs, effectiveness and net monetary benefit (NMB) among different modelling methods. The incremental NMB of the MM in the 6-months cycle lengths was a closer fit to the incremental NMB of the DES. The gap in the fit of the two cycle lengths to DES output reduced as the time horizon increased. Conclusion Different modelling methods were unlikely to influence the decision to accept a lower quality kidney transplant or remain waitlisted on dialysis. Both models produced similar results when time-dependant transition probabilities are used, most notable with shorter cycle lengths and longer time-horizons.

Keywords: Survival analysis; DES model; Markov model; Kidney transplantation (search for similar items in EconPapers)
Date: 2021
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DOI: 10.1186/s13561-021-00312-4

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