Pre-transplant Factors Research Articles

9175 Pretransplant Clinical Characteristics Related To Change In Bone Mineral Density In Adults 1 Year After Allogeneic Hematopoietic Stem Cell Transplantation At Bucaramanga, Colombia Reference Center

Abstract Disclosure: G.A. Parra-Serrano: None. C.L. Sossa: None. K.J. Moreno Medina: None. M. Ochoa: None. A. Reyes Gonzalez: None. A. Plata: None. P. Mantilla Mantilla: None. Introduction: Hematopoietic stem cell transplantation (HSCT) , refractory to pharmacological management, increases 10-year survival by 80%, Chronic complications include alterations in bone metabolism, that increase appearance of osteoporosis (13.8 - 17%), non traumatic fractures, and loss of Bone mineral density (BMD) at the hip -4.2%, L1L4 -2% and femoral neck-9%. Methods Calculate Change at (BMD) in adults undergoing allogenic (HSCT) after 1y and determine pretransplant factors related to this change. Composite endpoint osteoporosis/lowbonemass (osteoporosis Tscore<-2.5 and/or low bone mass Zscore-2.0) 1 year after transplant, Adult patients Retrospective cohort study, ethical comittee approval, anonymized database, undergoing allogeneic (HSCT) between 2009 and 2022, (BMD) measured at lumbar spine (L1L4) and femoral neck before and one year after transplant; Also paraclinical variables: TSH, vitaminD, kidney function, glucocorticoid, Graft vs host disease, disease relapse, diabetes. Descriptive analisis performed, simple linear regresion analisis for delta L1L4 and femoral neck BMD before and 1 year after transplant, and multivariate regresion analisis for variables p<0.2 on simple lineal regression analysis . Results 123 patients, (48 included, 73 excluded (22 died, 50 densitometry data not suitable)). BMD change At lumbar spine, -4.7% (NS) , and at femoral neck -9.8% (p<0.05), Simple regression analysis no correlation for preclinical variables at lumbar spine. negative correlation between prednisolone dose at femoral neck BMD (p 0.007, coefficient B -0.0086 [IC95% -0.014, 0.0025]). Mutivariate regression analysis performed for BMD diference at femoral neck, after adjusting for variables p<0.2 on simple regression analysis, model that include (prednisone dose, diabetes and relapse before transplant showed Rsquare 0.19 coefficient 0.0092 p 0.003. For every gram of glucocorticoid (prednisolone) bone loss decrease -0.9% of BMD at femoral neck at 1 year follow up. Proportion of patients with composite osteoporosis/lowbonemass at femoral neck pre-transplant (n2) 4.17%, postransplant (n14) 29.17%. * p 0.0005. no difference observed at lumbar spine. Fracture incidence n2 (4%) at lumbar spine and n1 (2%) at femoral neck. Conclusions At femoral neck, People with HSCT present significant decrease in (BMD) and higuer incidence of Osteoporosis or low bone mass, not observed at lumbar spine, after adjusting for multiple variables. for every 1gr of prednisolone equivalent dose, (BMD) decrease -0.9%, at femoral neck p0.003. The model only explain 19% of change of BMD at femoral neck, that suggest immune response caused by allogenic transplantation might be responsible, in part, of BMD change. Presentation: 6/3/2024

Artificial intelligence–based model for the recurrence of hepatocellular carcinoma after liver transplantation

BackgroundArtificial intelligence–based models might improve patient selection for liver transplantation in hepatocellular carcinoma. The objective of the current study was to develop artificial intelligence–based deep learning models and determine the risk of recurrence after living donor liver transplantation for hepatocellular carcinoma. MethodsThe study was a single-center retrospective cohort study. Patients who underwent living donor liver transplantation for hepatocellular carcinoma were divided into training and validation cohorts (n = 192). The deep learning models were used to stratify patients in the training cohort into low- and high-risk groups, and 5-year recurrence-free survival was assessed in the validation cohort. ResultsThe median follow-up period was 59.1 (33.9–72.4) months. The artificial intelligence model (pretransplant factors) had an area under the curve of 0.86 in the training cohort and 0.71 in the validation cohort. The largest tumor diameter and alpha-fetoprotein level had the greatest Shapley Additive exPlanations values for recurrence (>0.4). The 5-year recurrence-free survival rates in the low- and high-risk groups were 92.6% and 45% (P < .001). In the second artificial intelligence model (pretransplant factors + grade), the area under the curve for the validation cohort was 0.77, with 5-year recurrence-free survival rates of 96% and 30% in the low- and high-risk groups (P < .001). None of the low-risk patients outside the Milan and University of California San Francisco Criteria had recurrence during follow-up. ConclusionsThe artificial intelligence–based hepatocellular carcinoma transplant recurrence models might improve patient selection for liver transplantation.

Hospital-Acquired and Ventilator-Associated Pneumonia Early After Lung Transplantation: A Prospective Study on Incidence, Pathogen Origin, and Outcome.

Hospital-acquired (HAP) and ventilator-associated pneumonia (VAP) are important complications early (<30 days) after lung transplantation (LT). However, current incidence, associated factors, and outcomes are not well reported. LT recipients transplanted at our institution (July 2019-January 2020 and October 2021-November 2022) were prospectively included. We assessed incidence and presentation of pneumonia and evaluated the impact of associated factors using regression models. We also evaluated molecular relatedness of respiratory pathogens collected peri-transplant and at pneumonia occurrence using pulsed-field gel electrophoresis (PFGE). In the first 30 days post-LT, 25/270 (9.3%) recipients were diagnosed with pneumonia (68% [17/25] VAP; 32% [8/25] HAP). Median time to pneumonia was 11 days (IQR, 7-13); 49% (132/270) of donor and 16% (44/270) of recipient respiratory peri-transplant cultures were positive. However, pathogens associated with pneumonia were not genetically related to either donor or recipient cultures at transplant, as determined by PFGE. Diagnosed pulmonary hypertension (HR, 4.42; 95% CI, 1.62-12.08) and immunosuppression use (HR, 2.87; 95% CI, 1.30-6.56) were pre-transplant factors associated with pneumonia. Pneumonia occurrence was associated with longer hospital stay (HR, 5.44; 95% CI, 2.22-13.37) and VAP with longer ICU stay (HR, 4.31; 95% CI, 1.73-10.75) within the first 30 days post-transplantation; 30- and 90-day mortality were similar. Prospectively assessed early pneumonia incidence occurred in ∼10% of LT. Populations at increased risk for pneumonia occurrence include LT with pre-transplant pulmonary hypertension and pre-transplant immunosuppression. Pneumonia was associated with increased healthcare use, highlighting the need for further improvements by preferentially targeting higher-risk patients.

Adenovirus infections after allogeneic hematopoietic cell transplantation in children and adults: a study from the Infectious Diseases Working Party of the European Society for Blood and Marrow Transplantation.

The objective of the study was the analysis of clinical types, outcomes, and risk factors associated with the outcome of adenovirus (ADV) infection, in children and adults after allo-HCT. A total number of 2529 patients (43.9% children; 56.1% adults) transplanted between 2000 and 2022 reported to the EBMT database with diagnosis of ADV infection were analyzed. ADV infection manifested mainly as viremia (62.6%) or gastrointestinal infection (17.9%). The risk of 1-year mortality was higher in adults (p = 0.0001), and in patients with ADV infection developing before day +100 (p < 0.0001). The 100-day overall survival after diagnosis of ADV infections was 79.2% in children and 71.9% in adults (p < 0.0001). Factors contributing to increased risk of death by day +100 in multivariate analysis, in children: CMV seropositivity of donor and/or recipient (p = 0.02), and Lansky/Karnofsky score <90 (p < 0.0001), while in adults: type of ADV infection (viremia or pneumonia vs gastrointestinal infection) (p = 0.0004), second or higher HCT (p = 0.0003), and shorter time from allo-HCT to ADV infection (p = 0.003). In conclusion, we have shown that in patients infected with ADV, short-term survival is better in children than adults. Factors directly related to ADV infection (time, clinical type) contribute to mortality in adults, while pre-transplant factors (CMV serostatus, Lansky/Karnofsky score) contribute to mortality in children.

The predictive value of HCT-CI and CCI comorbidity indices in predicting survival and mortality before allogeneic stem cell transplantation in acute leukemia patients: A single-centre experience

Objective: Acute leukemia often involves comorbidities, impacting treatment decisions and patient outcomes. Clinicians commonly use the Charlson Comorbidity Index (CCI) and the Hematopoietic Stem Cell Transplantation Comorbidity Index (HCT-CI) to assess their influence. However, their effectiveness in predicting survival and non-relapse mortality (NRM) in acute leukemia patients under 65 undergoing allogeneic stem cell transplantation remains unclear. Patients and Methods: We conducted a retrospective single-center analysis on adults diagnosed with acute myeloid leukemia (AML) or acute lymphoblastic leukemia (ALL). The study included 35 patients, comprising 16 AML and 19 ALL cases. Patients were categorized based on age-adjusted HCT-CI and CCI scores. Results: The 2-year NRM rate was determined to be 51.4%. Statistical analysis found no significant associations between age-adjusted CCI (p=0.217) and age-adjusted HCT-CI (p=0.102) with NRM. However, median overall survival significantly varied based on risk levels (p=0.003), HCT-CI groups (p=0.009), and CCI groups (p=0.011). Conclusion: Using age-adjusted HCT-CI and CCI for comorbidity scoring in initial assessment of acute leukemia patients and those under 65 shows promise. However, these indices were ineffective in predicting NRM, emphasizing the importance of considering other significant pre-transplant factors like genetic risk, conditioning regimens, and donor type.

#2504 Histopathological findings and cardiovascular events in kidney transplantation

Abstract Background and Aims Despite offering superior outcomes for patients with end-stage kidney disease, kidney transplantation poses significant cardiovascular risks. Recently, histopathological findings in chronic kidney disease patients have been associated with all-cause mortality and cardiovascular events, but there is scant data on this subject in kidney transplant recipients. This study assesses the relationship between histopathological findings in protocol biopsies of kidney grafts and cardiovascular events, graft loss, and mortality in renal transplant recipients. Method A prospective observational study included 530 renal transplant recipients at the Hospital Clínic de Barcelona from March 2015 to 2019, with follow-up until March 2023. Data included demographics, comorbidities, laboratory tests, and protocol allograft biopsies at 3 and 12 months post-transplant. Associations between histopathological findings and outcomes (cardiovascular events, graft loss, mortality) were analyzed. Results Chronic vascular lesions (CV) were significantly correlated with cardiovascular death and major adverse cardiovascular events (MACE) (OR 10.4 (1.6–66.4); p 0.002). Arteriolar hyalinosis and interstitial fibrosis were independently associated with all-cause mortality (OR 4.9 (1.1-21.4); p 0.02, and 1.2 (1.03-1.3), p 0.005; respectively) regardless of the estimated glomerular filtration rate (eGFR). Associations were also found between pre-transplant factors (diabetes, hypertension, hyperphosphatemia), active smoking, and deceased donors. Notably, post-transplant hypophosphatemia was related to MACE, suggesting a potential association with malnutrition though, this subject requires further investigation. Conclusion Histopathological findings in early protocol biopsies of kidney grafts, especially chronic vascular lesions, arteriolar hyalinosis, and interstitial fibrosis, have a potential predictive value for cardiovascular events, mortality, and graft outcomes in transplant recipients, irrespective of eGFR. These insights emphasize the importance of timely post-transplant histological assessments for risk stratification and personalized interventions. Prospective studies are imperative to validate these findings and improve customized care strategies in this population.

Arteriovenous fistula for haemodialysis as a predictor of de novo heart failure in kidney transplant recipients.

The haemodynamic effects of a functioning haemodialysis arteriovenous fistula (AVF) can cause or exacerbate heart failure (HF). We investigated whether the presence of an AVF at the time of kidney transplant (KT) is associated with de novo HF. This was an observational cohort study including adult patients who received a KT in the West of Scotland between 2010 and 2020. We evaluated the risk and associations of pretransplant factors with de novo HF, alone and as a composite cardiovascular (CV) outcome (including non-fatal myocardial infarction, non-fatal stroke, de novo HF and CV death). Multivariable proportional hazards regression and sensitivity analyses were used to identify independent correlates of the outcomes. Among 1330 included patients, the incident rate of de novo HF after transplantation was 58/1000 person-years [95% confidence interval (CI) 50-67] in AVF patients (n=716) compared with 33/1000 person-years (95% CI 27-41) in non-AVF patients (n=614). De novo HF was associated with the presence of an AVF [adjusted hazard ratio (aHR) 2.14 (95% CI 1.40-3.26)], duration of dialysis [aHR 1.03/year increase (95% CI 1.01-1.04)], age at transplant [aHR 1.03/year increase (95% CI 1.02-1.05)], female sex [aHR 1.93 (95% CI 1.40-2.65)] and pretransplant diabetes [aHR 2.43 (95% CI 1.48-4.01)]. The presence of an AVF was also associated with the composite CV outcome [aHR 1.91 (95% CI 1.31-2.78)]. The presence of an AVF may be an underrecognized modifiable predictor of de novo HF posttransplantation.

Cord Blood Transplantation for Very Early-Onset Inflammatory Bowel Disease Caused by Interleukin-10 Receptor Deficiency.

Interleukin-10 receptor (IL-10R) deficiency can result in life-threatening very early-onset inflammatory bowel disease (VEO-IBD). Umbilical cord blood transplantation (UCBT) is a curative therapy for patients with IL-10R deficiency. This study aimed to investigate the efficacy of UCBT in treating IL-10R deficiency and develop a predictive model based on pre-transplant factors. Eighty patients with IL-10R deficiency who underwent UCBT between July 2015 and April 2023 were retrospectively analyzed. Cox proportional hazards regression and random survival forest were used to develop a predictive model. Median age at transplant was 13.0months (interquartile range [IQR], 8.8-25.3months). With a median follow-up time of 29.4months (IQR, 3.2-57.1months), the overall survival (OS) rate was 65.0% (95% confidence interval [CI], 55.3%-76.3%). The engraftment rate was 85% (95% CI, 77%-93%). The cumulative incidences of acute and chronic graft-versus-host disease were 48.2% (95% CI, 37.1%-59.4%) and 12.2% (95% CI, 4.7%-19.8%), respectively. VEO-IBD-associated clinical symptoms were resolved in all survivors. The multivariate analysis showed that IL-6 and stool occult blood were independent prognostic risk factors. The multivariate Cox proportional hazards regression model with stool occult blood, length- or height-for-age Z-score, medical history of sepsis, and cord blood total nucleated cells showed good discrimination ability, with a bootstrap concordance index of 0.767-0.775 in predicting OS. Better inflammation control before transplantation and higher cord blood total nucleated cell levels can improve patient prognosis. The nomogram can successfully predict OS in patients with IL-10R deficiency undergoing UCBT.

Do pre-transplant cultural factors predict health-related quality of life after kidney transplantation?

Post-transplant health-related quality of life (HRQOL) is associated with health outcomes for kidney transplant (KT) recipients. However, pretransplant predictors of improvements in post-transplant HRQOL remain incompletely understood. Namely, important pretransplant cultural factors, such as experience of discrimination, perceived racism in healthcare, or mistrust of the healthcare system, have not been examined as potential HRQOL predictors. Also, few have examined predictors of decline in HRQOL post-transplant. Using data from a prospective cohort study, we examined HRQOL change pre- to post-transplant, and novel cultural predictors of the change. We measured physical, mental, and kidney-specific HRQOL as outcomes, and used cultural factors as predictors, controlling for demographic, clinical, psychosocial, and transplant knowledge covariates. Among 166 KT recipients (57% male; mean age 50.6 years; 61.4%>high school graduates; 80% non-Hispanic White), we found mental and physical, but not kidney-specific, HRQOL significantly improved post-transplant. No culturally related factors outside of medical mistrust significantly predicted change in any HRQOL outcome. Instead, demographic, knowledge, and clinical factors significantly predicted decline in each HRQOL domain: physical HRQOL-older age, more post-KT complications, higher pre-KT physical HRQOL; mental HRQOL-having less information pre-KT, greater pre-KT mental HRQOL; and, kidney-specific HRQOL-poorer kidney functioning post-KT, lower expectations for physical condition to improve, and higher pre-KT kidney-specific HRQOL. Instead of cultural factors, predictors of HRQOL decline included demographic, knowledge, and clinical factors. These findings are useful for identifying patient groups that may be at greater risk of poorer post-transplant outcomes, in order to target individualized support to patients.

Machine Learning Validates Risk Biomarkers of Chronic Graft-Versus-Host Disease in 936 Patients from BMT CTN 0201 & 1202 Cohorts

Introduction Our previous work identified susceptibility/risk biomarkers for developing chronic GVHD (cGVHD) in individuals without clinically apparent disease (Logan et al. 2023, JCI), which is a major contributor to morbidity and mortality following allogeneic hematopoietic cell transplant (HCT). In this study, we used machine learning (ML) algorithms to build biomarker-based prediction models for development of cGVHD and non-relapse mortality (NRM). Methods Data were obtained on 9 pre-transplant factors and 7 plasma proteins at Day 90 post HCT in 936 HCT recipients from the BMT CTN 0201 and 1202 studies. The study population was split into separate training (80%) and validation (20%) datasets. Associations of each protein marker with the hazards of cGVHD and NRM were evaluated using Cox proportional hazards (PH) models. To evaluate the predictive ability of the proteins, ML models were constructed from them and the time varying Area Under the ROC curve (AUCt) was estimated at Days 180, 270, 360, and 540 post HCT. We considered ML approaches within the PH model framework, including Boosting (XGBoost), Group SCAD, and Adaptive Group Lasso, as well as methods avoiding the PH assumption, including Random Survival Forests and Bayesian Additive Regression Trees (BART). DeepSurv and DeepHit models were also used in the first application of deep learning to GVHD biomarker risk evaluation to our knowledge. A p-value cutoff of 0.05 determined statistical significance. Results Of the 7 proteins tested, 5 (CXCL9, CXCL10, MMP3, DKK3, and CD163) were associated with cGVHD risk, while 4 (MMP3, DKK3, ST2, CD163) were correlated with NRM (p&amp;lt;0.05 for all). Moreover, effects of some markers varied depending on the graft type, with higher MMP3 found to have a larger, deleterious effect on cGVHD risk in patients with bone marrow (BM) compared to peripheral blood (PB) graft (p=0.03). CD163 had a similar interaction with graft type such that its effects on cGVHD and NRM risk are significant with BM graft but not with PB graft (p&amp;lt;0.05 for both). The abilities of the ML methods to risk stratify cGVHD and NRM were assessed and contrasted to a Group SCAD model having clinical factors only. Because graft type was found to impact both the risks of cGVHD and NRM as well as the biomarkers' effects, the ML models considered markers, graft type, and their interactions. In modeling cGVHD risk, the Group SCAD model with only clinical factors selected 4 variables: age, graft type, donor-recipient sex-mismatch, and GVHD prophylaxis; while Adaptive Group Lasso and Group SCAD with biomarkers selected 5 proteins: CXCL9, CXCL10, MMP3, ST2, and CD163. In the validation dataset, all ML methods with biomarkers provided similar or higher AUCt for cGVHD after Day 270 compared to clinical factors only, suggesting that plasma proteins measured as early as Day 90 can inform underlying cGVHD biology that has not manifested clinically ( Fig). BART and Boosting yielded the highest AUCt and were better than the model with only clinical factors, attaining AUCt &amp;gt; 0.60 from Day 270-540. To assess the variables' importance in ML, we examined BART's posterior probabilities of selection, which describe how frequently each variable is used in the BART tree ensemble. For cGVHD, variables with selection probabilities &amp;gt; 0.10 were graft type, CXCL9, and MMP3. Notably, the protein markers that were significant in separate models also had the largest selection probabilities of all markers. The AUCt for NRM was stable across time points in the 0.65-0.72 range and superior to clinical factors after Day 180 ( Fig). For NRM, variables with selection probabilities &amp;gt; 0.10 were graft type, ST2, MMP3, CD163, and DKK3. Conclusions ML methods using non-invasive plasma proteins can successfully identify and validate risk biomarkers of cGVHD. ML algorithms using objective and early measurements of soluble markers including CXCL9, CXCL10, MMP3, DKK3, and ST2 perform better in predicting cGVHD than ML with known clinical factors only. ML with MMP3, DKK3, ST2, and CD163 improved NRM prediction. Deep learning models did not outperform more classical ML methods, possibly due to a limited sample size that could not reveal intricate relationships between proteins and cGVHD/NRM risk. Several proteins represent potential therapeutic targets. These data support future research to further validate these biomarkers and to develop ML algorithms to identify patients at risk for developing cGVHD and NRM.

Improve the prediction of liver transplant mortality based on pre-transplant factors: A multi-center study from China: Mortality prediction of LT

AimsTo designed a new model using pre-transplant data to predict post-transplant mortality for Chinese population and compared its performance to that of existing models. MethodsIn this multicenter study, 544 recipients of liver transplants for non-tumor indications were enrolled in the training group and 276 patients in the validation group. The new Simplified Mortality Prediction Scores (SMOPS) model was compared to the MELD and four existing models using the C-statistic. ResultsSMOPS model used 6 independent pre-transplantation risk factors screened from the training group (chronic liver failure/organ failure scores, fever > 37.6 ℃, ABO blood-type compatibility, arterial lactate level, leukocyte count and re-transplantation). The SMOPS accurately predicted patients' 30-day, 90-day and 365-day mortality following liver transplantation, and its' scores were more accurate than those of the other models. The SMOPS generated four levels of risk: low risk (<10 points), moderate risk (11–20 points), high risk (21–25 points) and futile risk (≥26 points). The survival within all risk levels was not different between MELD=40 and MELD<40. The survival within moderate-, high- or extreme-risk ALF was not different between ALF and non-ALF. ConclusionThe SMOPS model uses pre-transplant risk factors to stratify post-transplant survival and is superior to current models for Chinese population, and has the potential to contribute to improvements in organ-allocation policies.

Day 100 Risk Assessment Tool Predicts 1 Year Survival in Allogeneic Hematopoietic Cell Transplant Patients

Introduction Allogeneic hematopoietic cell transplant (HCT) is a potentially curative therapy for many advanced malignancies; however, it is associated with a significant risk of non-relapse mortality. Several validated measures have been developed to estimate 1-year overall survival (OS) and non-relapse mortality (NRM), but these rely solely on pre-transplant factors to estimate risk. We previously described a “Day 100 risk assessment tool” (PMID 34628474) that aimed to identify the most effective way to deliver high quality care. The score is based on factors primarily occurring within the first 100 days of HCT, demonstrating that, independent of traditional pre-transplant variables, factors identified at day 100 significantly impacted longer term outcomes. This previous analysis included 163 patients who were transplanted from 2015-2018. We now aim to validate our scoring system in a larger, more contemporary cohort. Methods The Day 100 risk tool includes 11 binary variables: HCT-comorbidity index ≥ 3, distance from transplant center &amp;gt; 1 hour, day 100 ECOG performance status (PS &amp;gt; 2), acute GVHD requiring systemic corticosteroids, infection requiring intravenous antibiotics, concerns regarding caregiver support, coping skills, substance use, poor health literacy, medication compliance, and “other” concerns from the care team. Patients were given a point for each factor (0 or 1) and total points were summed as the risk score for analysis. Patients who survived at least 100 days were included in analysis. One year survival estimates were analyzed using the Kaplan-Meier method (overall survival [OS]) and cumulative incidence methods (non-relapse mortality [NRM]). Prognostic factors were identified with Cox regression (OS) or Fine and Gray regression (NRM). All patients who died after 1-year were censored at 12 months. Results From 1/2018-7/2022, 407 patients underwent first allogeneic HCT and survived at least 100 days without progression of disease. Median age of patients was 61 years old (range 20 - 76) and the majority of patients were: Male (54.3%, N=221), White (88.7%, N=361), diagnosed with acute myelogenous leukemia (AML) (45%, N=183), received peripheral blood stem cells (72%, n=294) had a matched unrelated donor (62.7%, n=255), underwent reduced intensity conditioning (64%, n=259), and received post-transplant cyclophosphamide graft-versus-host disease prophylaxis (52.6%, n=214). Stratified according to best fit for survival, 46.7% (n=190) were classified as “low risk” (0-1), 42.5% (n=173) “intermediate risk” (2-3), and 10.8% (n=44) as “high risk” (≥4) based on Day 100 score. One-year OS was significantly worse for the high risk ≥4) compared to low risk (0-1) and intermediate risk (2-3) (Figure 1). Multivariable analysis demonstrated that the high-risk Day 100 score was significantly associated with 1-year OS and NRM (Table 1). Conclusion In a larger contemporary cohort, we validate our Day 100 risk assessment tool as prognostic for 1-year outcomes. Future dynamic scoring systems incorporating post-transplant events may help to identify high risk patients and potential interventions to improve longer-term outcomes.

Long-Term Toxicity after Total Body Irradiation-Based Conditioning Regimens for Allogeneic Stem Cell Transplantation

Total body irradiation (TBI) is an integral component of many conditioning regimens prior to allogeneic hematopoietic stem cell transplantation (HSCT). Few studies have investigated long-term sequelae. A large series of patients undergoing myeloablative and non-myeloablative regimens was studied. Adult patients undergoing allogeneic HSCT utilizing TBI-based conditioning regimens from 1995-2020 at our institution were included. Baseline treatment-related factors and long-term toxicities (developing, or persisting beyond, 6 months after HSCT) were collected. The cumulative incidence of long-term toxicities and overall survival (OS) were calculated. Cox regression was used to assess for predictors of toxicity. Five hundred fifty-two patients were analyzed: 378 myeloablative (typically 13.5 Gy/9fx) and 174 non-myeloablative (typically 2 Gy/1fx) TBI recipients. Median follow-up was 7.4 years for surviving patients. Cumulative incidences of long-term toxicities at 5 and 10 years are included in the Table. The most common toxicities were: pulmonary- infectious pneumonia and respiratory failure NOS; cardiac- heart failure and myocardial infarction; other endocrine- adrenal insufficiency and testosterone deficiency. The most common secondary malignancy was non-melanoma skin cancer. The proportion of all toxicities that were high-grade (3-5) for myeloablative and non-myeloablative regimens, respectively, were: pulmonary (65%, 52%), cardiac (66%, 39%), renal (23%, 27%), and other endocrine (3%, 18%). Increasing number of chemotherapy regimens (p = 0.05) and umbilical cord donor (p = 0.02) were associated with long-term pulmonary toxicity. Male sex (p = 0.03), increasing number of chemotherapy regimens (p<0.01), and elevated creatinine after transplant (p<0.01) were associated with long-term renal toxicity. Cataract development was associated with increasing age at transplant (p = 0.02). OS (5 years) was 40% (42% -myeloablative; 33%-non-myeloablative). Allogeneic HSCT, often preceded by TBI-based conditioning regimens, has significant survivorship challenges. Recipients of non-myeloablative regimens are still at risk of significant long-term multisystem toxicity despite much lower doses of TBI and chemotherapy. Pre-transplant factors such as cumulative chemotherapy exposure and age at transplant were associated with some toxicities.

#6910 PREDICTORS OF KIDNEY FUNCTION DECLINE IN LIVING KIDNEY TRANSPLANTATION DONORS

Abstract Background and Aims After nephrectomy kidney transplant donors lose 50% of their renal mass. Shortage of donors and long waiting list for deceased donor transplantation expanded the living donor criteria. The aim of this study to identify pretransplant donor related factors associated with renal function decline. Method We retrospectively studied LDKT donors from one transplant center in the period 2013 -2022. Data was retrieved from medical history charts and national electronic database system. Demographic characteristics as age, gender and relation to the recipient, patients preference to donate the kidney with higher measured split GFR, the presence of diabetes, hypertension, hyperlipidemia and BMI &amp;gt;30kg/m2 were analysed. Estimated GFR by CKD EPI was notified prior donation, one and two years afterwards. In a multivariate regression analysis the reduction ratio of CKD EPI was explored as dependent variable. Results We studied 121 donors. The average age at time of transplant was 59.18 ± 10.99 years. Donors’ average eGFR was 91.53 ± 18.62 mL/min. Donor's age and eGFR were significantly correlated (p &amp;lt; 0.0001, r=r−0.529). Male donors were 37 (30%), 11 (9%) were unrelated to recipients, 9(7%) had BMI&amp;gt;30, 17 (14%) diabetes, 53 (44%) hypertension 5 (4% hyperlipidemia), and 65 (52%) had more then one comorbidity combined. Eight of donors (7%) decided to donate the better kidney. CKD EPI declined to 68.17±18.62 ml/min at first and 66.01±21.29 ml/min at the second year. The RR of 24.53 ± 20.60 % and 27.62±18.76% raised on yearly bases, respectively. In the univariate analysis of the GFR declination at the first year BMI&amp;gt;30 kg/m2 was associated with higher reduction of GFR (β=0.318, P = .003). At the second year the presence of diabetes emerged as worsening factor of GFR (β=0.227, P = .034) and BMI&amp;gt;30 kg/m2 kept its significance (β=0.426, P = .000). All the other parameters showed no significant associations to the GFR decline. In the multivariate analysis BMI&amp;gt;30 kg/m2 remained as most powerful predictor at 12 months reduction of eGFR. Conclusion Patients with diabetes and especially with obesity are at higher risk of rapid decline in kidney function after kidney donation. Careful assessment prior kidney donation should weight the risks.

Effect of Age on Liver Transplantation Recipient Outcomes: Two Centers’ Experience

Liver diseases epidemiology has changed with advances in perioperative care. Transplantation at large centers is favorable among older and younger recipients. Local limitations on transplantation for recipients older than 65 years were cancelled in 2014. This study evaluates the effects of age on the transplantation outcome of Israeli patients in the era after removal of the limitations on recipient age. This retrospective analysis examined prospective data on patients older than 18 years who underwent liver or liver-kidney transplantation between 2014 and 2019 at 2 transplantation centers. Patients were divided into 4 age groups (group 1: ≤59 years; group 2: 60-64 years; group 3: 65-69 years; and group 4: ≥70 years). Each group's associations of pretransplantation factors with outcome and survival were examined. Two hundred sixty-one recipients underwent 269 transplantations (mean age: 53 ± 12.61 y). There were 181 male (67.8%) and 88 female recipients (67.28%). Overall, 207 patients (79.6%) survived ≥12 months. One-year survival rates were 82.9%, 73.2%, 71.4%, and 93.8% for groups 1 to 4, respectively (not statistically significant; P=.11). One-year graft survival was similar between groups. More patients with chronic obstructive pulmonary disease, diabetes mellitus, or ischemic heart disease tended to survive <12 months. Cardiovascular complication was more common in older groups and affected survival. Patient age alone should not be used to deny access to transplantation, which could benefit older nonfrail individuals. However, risk factors such as male sex, chronic obstructive pulmonary disease, ischemic heart disease, diabetes mellitus, and concomitant kidney-liver transplantation should be carefully considered.

The Impact of Selection Bias in Transplant Research Intended to Inform Patient Selection: An Example and Potential Solutions.

The Impact of Selection Bias in Transplant Research Intended to Inform Patient Selection: An Example and Potential Solutions.

PB2007: FACTORS ASSOCIATED WITH EARLY RELAPSE IN MYELOMA PATIENTS AFTER AUTOLOGOUS HEMATOPOIETIC STEM CELL TRANSPLANTATION

Background: Multiple myeloma (MM) is a clonal disease characterized by a neoplastic proliferation of plasma cells that make up approximately 10% of hematologic malignancies. Autologous hematopoietic stem cell transplantation (ASCT) after an induction regimen using combination of immunomodulatory drugs, proteasome inhibitors and dexamethasone is considered the standard treatment of newly diagnosed multiple myeloma in eligible patients. Aims: To demonstrate the pre-transplant factors associated with early relapse in MM patients undergoing ASCT. Methods: 27 adult MM patients who underwent ASCT at The Stem Cell Transplant Center of Dokuz Eylul University Hospital between October 2011 and August 2021 and who relapsed within 18 months of transplantation were included in this study. The data were compiled from the Dokuz Eylul Hematology archive and the Hospital Information Management System at Dokuz Eylul University Hospital and analyzed with SPSS v.24 (Statistical Package for Social Sciences). Mann-Whitney U test is used to compare kappa/lambda ratios, Kaplan Meier test is used to analyze survival and log-rank test is used to test significant difference between survival of two groups. Results: The median age at diagnosis is 57 (42-68) and 52% of patients were male (n=14). Patients received a median one line of treatment before ASCT (1-3). According to the ISS staging system, 9 patients were stage I, 9 patients were stage II and 9 patients were stage III. In 43% of patients (n=12), extramedullary (EM) disease involvement was present at the diagnosis. 33% had hypercalcemia (n=9), 19% had kidney involvement (n=5), 57% had anemia (n=16), and 75% had bone (n=21) at the time of diagnosis. Two patients achieved complete remission (CR) after 2 courses of induction therapy. But they lost this response pre-ASCT and they relapsed in 5th and 6th month after ASCT respectively. The median time to relapse post-ASCT was 6 (2-17) months. In 63% of these patients, clinical relapse was observed, treatment was started due to aggressive biochemical relapse in the rest. 25% (n=7) had EM disease involvement in relapse. In this patient group, the median survival after ASCT is 32 months (5-120). In 3 out of 10 patients with biochemical relapse, EM disease was not observed despite being present at the time of diagnosis. In 9 of the 17 patients with clinical relapse and EM disease at diagnosis, 7 patients relapsed with EM disease. Median Kappa/Lambda ratios at the time of diagnosis were 13.84 and 13.1 at the time of relapse. There was no statistically significant difference in kappa/lambda rates at the time of diagnosis and relapse of patients with biochemical and clinical relapse. Median progression-free survival (PFS) was 5 months in those with clinical relapse and 8 months in patients with biochemical relapse. Median overall survival (OS) was 19.2 months in those with clinical relapse and it was not reached in those with biochemical relapse (p=0.001) (Fig. 1). Image:Summary/Conclusion: It is known that in multiple myeloma, ASCT prolongs PFS. Early loss of response in patients who achieved CR after 2 courses of treatment may be a prognostic clue. OS and PFS are shorter in those with clinical relapses while biochemical relapses are more indolent. The fact that 43% of our patients have EM disease involvement in diagnosis indicates that this feature may be associated with early relapse. Outcomes of single and tandem ASCT in these patients should be examined in further studies.

FC 111: A Comorbidity Index and Pretransplant Physical Status Predict Survival in Older Kidney Transplant Recipients

Abstract BACKGROUND AND AIMS Regardless of age, kidney transplantation (KT) is considered the optimal treatment for patients with end-stage kidney disease (ESKD). In the increasing elderly ESKD population, KT should be reserved for carefully selected candidates who are expected to experience favorable outcomes. We aimed to prospectively evaluate pre-transplant recipient factors that may predict post-transplant patient survival and can eventually guide therapeutic decisions in elderly with ESKD. METHOD Recipient factors were evaluated in KT candidates aged ≥65 years, who were enlisted for KT between January 2013 and November 2016 at the Norwegian national transplant centre. Pretransplant comorbidity was assessed at waitlisting, according to the Liu Comorbidity Index (LCI). Self-reported health-related quality of life was assessed using the Kidney Disease Quality of Life Short Form version 1.3 (KDQOL-SF). The Cox proportional hazard regression was used to evaluate predictors of patient survival. RESULTS We included 289 waitlisted candidates, of whom 192 received a deceased brain-dead donor kidney. Mean age at KT was 72 (4.1) years, 133 (69%) were male, 47 (24%) were transplanted preemptively and 80% received an expanded criteria donor organ. During a median observation time of 4.6 (3.2–6.3) years post-KT, 66 recipients died. LCI ≤ 3 was observed in 136 recipients (71%), between 4–6 in 39 recipients (20%) and 17 recipients (9%) had LCI ≥ 7. Elevated LCI ≥ 4 predicted poor patient survival, and was associated with a 2.2-times increase in mortality risk (Figure 1). In recipients with LCI ≥ 4, dialysis ≥2 years comprised a 2.5-fold higher mortality risk, compared with recipients on dialysis ≤2 years (Figure 2). Self-reported pretransplant physical function was also proven to be a significant positive predictor of survival, with scores ≤60 being associated with a 2-fold increase in mortality risk. CONCLUSION The implementation of LCI and a physical function score during the evaluation of older kidney transplant candidates may improve the selection and thereby optimize post-transplant outcomes.

The fundamentals of sex-based disparity in liver transplantation: Understanding can lead to change.

Liver transplantation (LT) is the definitive treatment for end-stage liver disease. Unfortunately, women are disadvantaged at every stage of the LT process. We conducted a literature review to increase the understanding of this disparity. Hormonal differences, psychological factors, and Model for End-Stage Liver Disease (MELD) score inequalities are some pretransplantation factors that contribute to this disparity. In the posttransplantation setting, women have differing risk than men in most major outcomes (perioperative complications, rejection, long-term renal dysfunction, and malignancy) and assessing the two groups together is disadvantageous. Herein, we propose interventions including standardized criteria for LT referral, using an alternate MELD, education for support of women, and motivating women to seek living donors. Understanding sex-based differences will allow us to improve access, tailor management, and improve overall outcomes for all patients, particularly women.

Predicting Post-Heart Transplant Composite Renal Outcome Risk in Adults: A Machine Learning Decision Tool

Predicting Post-Heart Transplant Composite Renal Outcome Risk in Adults: A Machine Learning Decision Tool