Familial Clustering Identified in Periprosthetic Joint Infection Following Primary Total Joint Arthroplasty: A Population-Based Cohort Study

Abstract

Background: It is estimated that the cost to treat periprosthetic joint infection in the United States will approach $1.62 billion by 2020. Thus, the need to better understand the pathogenesis of periprosthetic joint infection is evident. We performed a population-based, retrospective cohort study to determine if familial clustering of periprosthetic joint infection was observed.

Methods: Analyses were conducted using software developed at the Utah Population Database (UPDB) in conjunction with the software package R. The cohort was obtained by querying the UPDB for all patients undergoing total joint arthroplasty and for those patients who had subsequent periprosthetic joint infection. The magnitude of familial risk was estimated by hazard ratios (HRs) from Cox regression models to assess the relative risk of periprosthetic joint infection in relatives and spouses. Using percentiles for age strata, we adjusted for sex, body mass index (BMI) of ≥30 kg/m, and a history of smoking, diabetes, and/or end-stage renal disease. Additionally, we identified families with excess clustering of periprosthetic joint infection above that expected in the population using the familial standardized incidence ratio.

Results: A total of 66,985 patients underwent total joint arthroplasty and 1,530 patients (2.3%) had a periprosthetic joint infection. The risk of periprosthetic joint infection following total joint arthroplasty was elevated in first-degree relatives (HR, 2.16 [95% confidence interval (CI), 1.29 to 3.59]) and combined first and second-degree relatives (HR, 1.79 [95% CI, 1.22 to 2.62]). Further, 116 high-risk pedigrees with a familial standardized incidence ratio of >2 and a p value of <0.05 were identified and 9 were selected for genotyping studies based on the observed periprosthetic joint infection/total joint arthroplasty ratio and visual inspection of the pedigrees for lack of excessive comorbidities.

Conclusions: Although preliminary, these data may help to guide further genetic research associated with periprosthetic joint infections. An understanding of familial risks could lead to new discoveries in creating patient-centered pathways for infection prevention in patients at risk.

Level of evidence: Prognostic Level III. See Instructions for Authors for a complete description of levels of evidence.

Fig. 1

Survival curve showing the probability of periprosthetic joint infection-free survival among the combined first and second-degree relatives of patients with and without periprosthetic joint infection, adjusted for sex, BMI ≥ 30 kg/m², history of smoking, diabetes, or end-stage renal disease. PJI+ = patients with periprosthetic joint infection and PJI- = patients without periprosthetic joint infection.

Fig. 2

Survival curve showing a lower probability of periprosthetic joint infection-free survival in younger patients undergoing total joint arthroplasty. In this model, patients undergoing total joint arthroplasty were stratified into 3 surgery age percentiles: ≤20th percentile (age 18 to 55 years), >20th to ≤80th percentiles (age 56 to 75 years), and >80th percentile (age >75 years), adjusted for sex, BMI ≥ 30 kg/m², history of smoking, history of diabetes, and end-stage renal disease.

Fig. 3

An example of a high-risk pedigree with confounding variables included as well as the number of months to infection and the facility for each patient undergoing total joint arthroplasty. PJI = periprosthetic joint infection, TJA = total joint arthroplasty, Mo = months, and ID = identification.