Continuous variables were compared between groups using Student t test, Mann-Whitney U test, or 1-way ANOVA as appropriate for the normality of the data distribution and the number of comparator groups. Categorical variables were compared using a chi-square test or Fisher exact test as appropriate for the number of participants in each subgroup. Survival distributions for the primary composite endpoint and each component were compared between groups using Kaplan-Meier methods and the log-rank test. Cases that did not experience the endpoint by the end of the study period or were lost to clinical follow-up were censored for time-to-event analyses. The primary composite endpoint was also modeled using Cox proportional hazards regression to adjust the univariable relationship between surveillance findings and the primary endpoint for clinical covariates. SCI phenotypes (including both i0t1 and i1t1 SC-B-TCMR definitions), Banff chronic injury scores (ci, ct, cg, and cv), and clinical covariates that were associated with the primary endpoint by univariable analysis at P < 0.10 were entered into a multivariable Cox model. We did not include Banff acute injury scores (t, v, i, g, ptc) in the Cox model because of concerns for multicollinearity with SCI and its phenotypes that are defined by these scores. We included the total inflammation score as a covariate in the models to capture inflammation in areas with scarring.34 We also performed a sensitivity analysis where cases of SC-BKVAN were excluded from the SCI group. Visual inspection of log-log plots was used to confirm the proportionality of hazards assumption. All statistical tests were 2-tailed with statistical significance defined as P < 0.05. All analyses were performed using SPSS Statistics version 25 (IBM, Armonk, NY).

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