Next-Generation Sequencing vs Culture-Based Methods for Diagnosing Periprosthetic Joint Infection After Total Knee Arthroplasty: A Cost-Effectiveness Analysis

Background: Periprosthetic joint infection (PJI) after total knee arthroplasty is challenging to diagnose. Compared with culture-based techniques, next-generation sequencing (NGS) is more sensitive for identifying organisms but is also less specific and more expensive. To date, there has been no study comparing the cost-effectiveness of these two methods to diagnose PJI after total knee arthroplasty. Methods: A Markov, state-transition model projecting lifetime costs and quality-adjusted life years (QALYs) was constructed to determine the cost-effectiveness from a societal perspective. The primary outcome was incremental cost-effectiveness ratio, with a willingness-to-pay threshold of $100,000/QALY. Sensitivity analyses were performed to evaluate parameter assumptions. Results: At our base case values, culture was not determined to be cost-effective compared to NGS, with an incremental cost-effectiveness ratio of $422,784 per QALY. One-way sensitivity analyses found NGS to be the cost-effective choice above a pretest probability of 45.5% for PJI. In addition, NGS was cost-effective if its sensitivity was greater than 70.0% and its specificity greater than 94.1%. Two-way sensitivity analyses revealed that the pretest probability and test performance parameters (sensitivity and specificity) were the largest factors for identifying whether a particular strategy was cost-effective. Conclusion: The results of our model suggest that the cost-effectiveness of NGS to diagnose PJI depends primarily on the pretest probability of PJI and the performance characteristics of the NGS technology. Our results are consistent with the idea that NGS should be reserved for clinical contexts with a high pretest probability of PJI. Further study is required to determine the indications and subgroups for which NGS offers clinical benefit. (c) 2019 Elsevier Inc. All rights reserved.