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Title: | A Computationally Efficient Method for Probabilistic Parameter Threshold Analysis for Health Economic Evaluations | Authors: | PIETERS, Zoe Strong, Mark Pitzer, Virginia E. Beutels, Philippe Bilcke, Joke |
Issue Date: | 2020 | Publisher: | SAGE PUBLICATIONS INC | Source: | MEDICAL DECISION MAKING, 40 (5) , p. 669 -679 (Art N° 0272989X20937253) | Abstract: | Background. Threshold analysis is used to determine the threshold value of an input parameter at which a health care strategy becomes cost-effective. Typically, it is performed in a deterministic manner, in which inputs are varied one at a time while the remaining inputs are each fixed at their mean value. This approach will result in incorrect threshold values if the cost-effectiveness model is nonlinear or if inputs are correlated.Objective. To propose a probabilistic method for performing threshold analysis, which accounts for the joint uncertainty in all input parameters and makes no assumption about the linearity of the cost-effectiveness model.Methods. Three methods are compared: 1) deterministic threshold analysis (DTA); 2) a 2-level Monte Carlo approach, which is considered the gold standard; and 3) a regression-based method using a generalized additive model (GAM), which identifies threshold values directly from a probabilistic sensitivity analysis sample.Results. We applied the 3 methods to estimate the minimum probability of hospitalization for typhoid fever at which 3 different vaccination strategies become cost-effective in Uganda. The threshold probability of hospitalization at which routine vaccination at 9 months with catchup campaign to 5 years becomes cost-effective is estimated to be 0.060 and 0.061 (95% confidence interval [CI], 0.058-0.064), respectively, for 2-level and GAM. According to DTA, routine vaccination at 9 months with catchup campaign to 5 years would never become cost-effective. The threshold probability at which routine vaccination at 9 months with catchup campaign to 15 years becomes cost-effective is estimated to be 0.092 (DTA), 0.074 (2-level), and 0.072 (95% CI, 0.069-0.075) (GAM). GAM is 430 times faster than the 2-level approach.Conclusions. When the cost-effectiveness model is nonlinear, GAM provides similar threshold values to the 2-level Monte Carlo approach and is computationally more efficient. DTA provides incorrect results and should not be used. | Notes: | Pieters, Z (corresponding author), Univ Antwerp, Hasselt Univ, Data Sci Inst, I BioStat, DS-243,Univ Pl 1, B-2610 Antwerp, Belgium. zoe.pieters@uantwerpen.be |
Other: | Pieters, Z (corresponding author), Univ Antwerp, Hasselt Univ, Data Sci Inst, I BioStat, DS-243,Univ Pl 1, B-2610 Antwerp, Belgium. zoe.pieters@uantwerpen.be | Keywords: | deterministic sensitivity analysis;Monte Carlo approach;probabilistic sensitivity analysis;probabilistic threshold analysis | Document URI: | http://hdl.handle.net/1942/31972 | ISSN: | 0272-989X | e-ISSN: | 1552-681X | DOI: | 10.1177/0272989X20937253 | ISI #: | WOS:000546012800001 | Rights: | The Author(s) 2020. Article reuse guidelines: sagepub.com/journals-permissions DOI: 10.1177/0272989X20937253 journals.sagepub.com/home/mdm | Category: | A1 | Type: | Journal Contribution | Validations: | ecoom 2021 |
Appears in Collections: | Research publications |
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