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. 2022 Jul 26;12(8):1216.
doi: 10.3390/jpm12081216.

A Decision Support Framework for Periprosthetic Joint Infection Treatment: A Cost-Effectiveness Analysis Using Two Modeling Approaches

Vasiliy N Leonenko  1 , Yulia E Kaliberda  1 , Yulia V Muravyova  2 , Vasiliy A Artyukh  2
Affiliations

A Decision Support Framework for Periprosthetic Joint Infection Treatment: A Cost-Effectiveness Analysis Using Two Modeling Approaches

Vasiliy N Leonenko et al. J Pers Med. .

Abstract

Today, periprosthetic joint infection (PJI) is one of the leading indications for revision surgery and the most ominous complication in artificial joint patients. The current state of the art for treating PJI requires the development of methods for planning the costs at different scales to facilitate the selection of the best treatment methods. In this paper, we perform a cost-effectiveness assessment for strategies related to the treatment of PJI using a composite decision support modeling framework. Within the framework, two models are implemented: a detailed discrete-event probabilistic model based on the decision tree approach and a dynamic Markov model with generalized states. The application of the framework is demonstrated on the dataset which was provided by the Russian Scientific Research Institute of Traumatology and Orthopedics named after R.R. Vreden. The analyzed dataset contains 600 patient records divided into two groups (retrospective group, based on old records, and prospective group, based on real-time follow-up). The cost-effectiveness of treatment methods was compared based on associated costs and QALY units gained, with the mentioned two indicators calculated using two models independently from each other. As a result, two comparative rankings of cost-effectiveness of PJI treatment methods were presented based on the model output.

Keywords: Markov model; decision trees; periprosthetic joint infection; revision arthroplasty; total hip replacement.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure A1
Figure A1
Markov model transition probabilities for revision operation with the preservation of endoprosthesis.
Figure A2
Figure A2
Markov model transition probabilities for two-stage total hip replacement with > 2 months between the stages.
Figure A3
Figure A3
Markov model transition probabilities for resection arthroplasty.
Figure A4
Figure A4
Markov model transition probabilities for two-stage total hip replacement with 2–3 weeks between the stages.
Figure A5
Figure A5
Markov model transition probabilities for two-stage total hip replacement with 6–8 weeks between the stages.
Figure A6
Figure A6
Markov model transition probabilities for one-stage total hip replacement.
Figure A7
Figure A7
Markov model transition probabilities for partial one-stage total hip replacement.
Figure A8
Figure A8
Markov model transition probabilities for partial two-stage total hip replacement.
Figure 1
Figure 1
A fragment of the decision tree partial re-THR with confidence intervals for transition probabilities.
Figure 2
Figure 2
Markov model states and transitions.
See this image and copyright information in PMC

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