Transplant-associated thrombotic microangiopathy (TA-TMA) causes microthrombi formation and multiorgan dysfunction, leading to a sevenfold increase in need for renal replacement therapy and a threefold increase in transplant-related mortality in affected patients.1-3 Patients with sickle cell disease (SCD), who have baseline endothelial injury, face a sixfold higher risk of developing TA-TMA than other transplant recipients. In this manuscript, sickle cell disease refers to sickle cell anemia.4 Diagnosis of TA-TMA in paediatric patients is based on biopsy or clinical criteria such as the modified Jodele criteria.1 Guidelines to screen for TA-TMA recommend screening with daily full blood count, chemistry and blood pressures, twice weekly lactate dehydrogenase (LDH) and weekly urine protein to creatinine ratio and peripheral smear for schistocytes.5 However, predictive biomarkers before the onset of end-organ damage have not been established. Early identification of TA-TMA would enable timely intervention with therapies such as complement blockade2 to significantly reduce morbidity and mortality. Markers of complement activation, endothelial damage and thrombosis have been explored, but none predict TA-TMA.1 Single-centre cohorts have shown that sC5b-9 levels on Day 28 and the complement protein Ba on Day 7 post-transplant were associated with TA-TMA.6, 7 Unlike these costly, specialized markers that require time to obtain, the endothelial activation and stress index (EASIX) score is based on routine laboratory values—platelet count, creatinine and LDH—and has been applied in the adult and paediatric transplant settings to predict mortality as well as endotheliopathies such as sinusoidal obstruction syndrome or graft-versus-host disease (GVHD).8-11 We retrospectively compared peri-transplant EASIX scores between patients with SCD who did and did not develop TA-TMA after haematopoietic stem cell transplant (HSCT) and defined a cut-point to prompt a more definitive TA-TMA workup. All patients with SCD who underwent HSCT at Children's National Hospital between June 2016 and June 2024 were studied. Patients who received non-myeloablative conditioning with alemtuzumab and 300 cGy total body irradiation (TBI) were excluded given that TA-TMA has not been reported after this HSCT approach.12 TA-TMA was identified by the clinical team in real time, and all patients in the TA-TMA group for this study were classified as ‘definite TA-TMA’ based on Jodele criteria. In patients who underwent second transplants, each transplant was evaluated as an individual observation. This study was approved by the Children's National Hospital Institutional Review Board. Baseline demographics, SCD disease complications, therapies and transplant characteristics were collected. To account for platelet transfusions, if patients had multiple platelet counts in 1 day, the lower of the two counts was used. EASIX scores (LDH (U/L) × creatinine (mg/dL)/platelet count (109/L)) were calculated for each of the following time points: Baseline (day of pretransplant admission), Days −5, 0 (transplant), +7, +10, +14, +17, +21, +28, +60, +90, +120. Demographics and baseline characteristics of patients with and without TA-TMA (TMA group and non-TMA group) were summarized using descriptive statistics. Group comparisons of baseline characteristics were done using chi-squared or Mann–Whitney U-tests. All p-values are presented for post hoc comparisons or signal finding and were unadjusted. Median EASIX scores, interquartile ranges and difference in median EASIX scores between groups along with bootstrapped 95% confidence interval CI were calculated for each time point and displayed using boxplots. An exploratory analysis was performed using a composite EASIX score, defined as the overall median value calculated from all patient EASIX scores across Days 14, 17 and 21. The composite score was used to determine the optimal cut-point for identifying TA-TMA, maximizing sensitivity while maintaining a minimum specificity of 60%, based on 10 000 bootstrap iterations using the cutpointr package. Analyses were conducted using R (v2024.09.1 + 394) with tidyverse, cutpointr and ggplot.13 Our study included 67 transplants, which were performed in 62 paediatric patients with SCD. Nine patients (13.4%) developed TA-TMA and diagnosed at a median of 52 days post-transplant (range: 27–116 days). All patients with TA-TMA were subsequently treated with eculizumab. Baseline patient and transplant characteristics are summarized in Table 1. Conditioning regimens for patients who received second transplant are summarized in Table S1. Most baseline characteristics including age, history of SCD complications, pre-HSCT SCD medications, graft source and donor type were similar between TA-TMA and non-TMA groups. Patients diagnosed with TA-TMA had slightly higher baseline haemoglobin F% and a higher proportion received myeloablative conditioning (7/9, 77.8%) when compared to the non-TMA group (19/58, 32.8%), p = 0.01. EASIX scores across multiple time points pre- and post-transplant are shown in Figure 1A. Median EASIX scores were nominally higher in patients who developed TA-TMA at all days measured, with the largest difference observed on Days +17 and +21. Median EASIX scores for TA-TMA versus non-TMA were baseline 0.63 versus 0.36 (difference 0.27, 95% CI: −0.03, 0.71), Day −5 0.81 versus 0.49 (difference 0.32, 95% CI: −0.06, 0.52), Day 0 0.77 versus 0.68 (difference 0.09, 95% CI: −0.17, 1.07), Day +7 3.87 versus 2.17 (difference = 1.7, 95% CI:0.44, 4.06), Day +10 2.81 versus 1.68 (difference = 1.13, 95% CI: −0.51, 7.00), Day +14 3.92 versus 2.11 (difference = 1.81, 95% CI: −0.66, 5.54), Day +17 4.77 versus 2.05 (difference = 2.72, 95% CI: 1.15, 6.81), Day +21 4.97 versus 1.75 (difference = 3.22, 95% CI: 2.27, 4.71), Day +28 2.43 versus 0.1.5 (difference = 0.93, 95% CI: −0.17, 2.19), Day +60 1.44 versus 0.71 (difference = 0.73, 95% CI: 0.28, 5.47), Day +90 1.00 versus 0.69 (difference = 0.31, 95% CI: −0.09, 1.99) and Day +120 1.13 versus 0.66 (difference = 0.47, 95% CI: 0.09, 0.95). The median composite score for Days 14–21 for patients who went on to develop TA-TMA was 4.55 whereas the score for the non-TMA group was 1.97 (p < 0.001, Figure 1B). Figure 1C shows the performance of the optimal cut-point of 2.83 for an EASIX score on any day from Days +14 to 21. The sensitivity at this cut-point was 84.6%, specificity of 66.7%, accuracy of 69.2% and area under curve (AUC) of 0.8. To assess the contribution of individual components of the EASIX score, platelet count, LDH levels and creatinine levels were compared across time points. Overall, the TA-TMA group was observed to have lower median platelet counts, higher median LDH levels and lower median creatinine levels compared to the non-TMA group (Figure 1D,E). Median platelet counts between the two cohorts were observed to be different at all time points post-transplant except at baseline and Day+28. Median LDH levels only differed on Days +28 and +60, and median creatinine levels alone did not differ at any time point. In addition to TA-TMA, we tabulated incidence of graft-versus-host disease (GVHD) and surprisingly observed no acute GVHD and only one case (11.1%) of chronic GVHD in the TA-TMA group. Among those without TA-TMA, 13 (22.4%) developed acute GVHD and 10 (17.2%) developed chronic GVHD. While these differences were not statistically significant, they are in contrast to our expectation based on prior literature which links risk of TA-TMA and GVHD14 and raises the question of whether this relationship differs in the sickle cell population compared with other post-transplant patients. In summary, this study evaluates the use of the EASIX score specifically among transplant patients with SCD, a population particularly vulnerable to post-transplant endotheliopathies due to baseline endothelial dysfunction. Our findings suggest that elevated EASIX scores within the first 28 days post-transplant period may serve as a screening tool for TA-TMA in paediatric and adolescent SCD patients. In this cohort, EASIX scores were observed not to differ between the TMA and non-TMA groups at baseline, but increased on Days +14–21, consistent with findings by Muratore et al.10 and likely reflecting a divergent response to pretransplant conditioning. Based on our prespecified desired performance characteristics maximizing the sensitivity with a minimum specificity of 60%, the EASIX score of 2.83 between Days +14 and +21 identified the occurrence of TA-TMA with 84.6% sensitivity and 66.7% specificity. Since this difference in EASIX score arose several weeks earlier than the clinical diagnosis of TA-TMA in most patients, prospectively calculated EASIX scores may serve as a screening tool in the early post-transplant period. Recognition of the risk associated with elevated EASIX scores may help clinicians identify patients who could benefit from closer monitoring and preventative interventions such as modulation of medications that increase the risk of endothelial injury or more aggressive treatment of GVHD. Limitations of this study include its small sample size and retrospective design. As expected with a rare condition, the population is skewed with more patients in the non-TMA compared with the TMA group. Baseline factors such as conditioning regimen and prior transplants are likely important contributors to TA-TMA risk and should be considered in future multivariate analyses in larger cohorts. Further work is also needed to explore the observation of lower incidence of GVHD among sickle cell patients diagnosed with TA-TMA. In addition, variable platelet transfusion practices at early post-HSCT time points may influence EASIX scores. To improve the specificity of this score for prediction of TA-TMA, it can be combined with other associated clinical variables, such as hypertension or proteinuria. Future work should focus on validation of findings in larger, multicentre settings, development of combination scores that include EASIX as well as other variables, and examination of the relationship between EASIX scores and other post-transplant complications. Reethu Krishnan, Anant Vatsayan, Hari Sankaran and Alexandra Dreyzin conceptualized the study. Reethu Krishnan, Anant Vatsayan, Hari Sankaran and Alexandra Dreyzin analysed the data. Reethu Krishnan and Hari Sankaran completed the statistical analysis. Reethu Krishnan drafted the initial manuscript. All authors critically reviewed the data and revised the manuscript. The authors have nothing to report. This research was supported in part by the Intramural Research Program of the National Institutes of Health (NIH)-National Cancer Institute- NIH K12 Scholars, Grant/Award Number: K12CA226330. The contributions of the NIH author(s) were made as part of their official duties as NIH federal employees, are in compliance with agency policy requirements and are considered Works of the United States Government. However, the findings and conclusions presented in this paper are those of the author(s) and do not necessarily reflect the views of the NIH or the U.S. Department of Health and Human Services. The authors declare no competing interests. The study was approved by the institutional IRB. The data that support the findings of this study are available from the corresponding author upon reasonable request. Table S1. Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. 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Krishnan et al. (Thu,) studied this question.
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