Citations

ABSTRACT Background The Society of Pediatric Liver Transplantation (SPLIT) has undergone tremendous growth with > 45 sites contributing data focusing on improving outcomes in pediatric liver transplantation (LT). We report and compare outcomes from the SPLIT Registry. Methods Patients < 18 years with first‐time LT only enrolled into the SPLIT Registry between 2011 and 2023 were included. Data was stratified into eras from the last published registry update (era 1: 2011–2018, era 2: 2018–2023). Results Three thousand five hundred four participants from 47 centers were included (era 1: n = 2159; era 2: n = 1345). Age distribution differed with more children < 1 year. of age at LT in era 2 (era 1: 29% vs. era 2: 33%, p = 0.01). Indications for LT were similar, with biliary atresia (38.8%) and metabolic disease (16.0%) being most common. Exception point use was higher in era 2 (era 1: 45% vs. era 2: 56%, p < 0.001). No difference in graft type (deceased: 81% era 1 vs. 78% era 2, p = 0.78), patient survival at 90 days (era 1: 98.7% vs. era 2: 98.3%), 1 year (era 1: 97.2 vs. era 2: 96.8%), or 3 years (era 1: 95.3% vs. era 2: 95.2%) was noted. Rate of hepatic artery thrombosis was lower in era 2 (era 1: 7% vs. era 2: 5%, p = 0.02). Conclusions Trends in pediatric LT within SPLIT note similar LT indications and graft type, higher utilization of exception points, and lower HAT rates despite transplanting more children < 10 kg. This data underscores the evolution of pediatric LT toward higher survivability and overall patient outcomes.

Abstract This review explores the pivotal role of preanalytical variables in bringing liquid biopsy approaches into the clinic for brain tumors. Preanalytical variables encompass a range of critical issues, from blood sample collection and handling to the impact of tumor heterogeneity and patient-specific factors. These variables introduce challenges such as false positives, false negatives, and variability in the analysis of tumor signals, which can hinder the diagnostic and prognostic utility of liquid biopsies. Understanding the nuances of preanalytical variables is essential for the successful implementation of liquid biopsy in clinical settings. This paper delves into strategies aimed at mitigating the influence of preanalytical variables by emphasizing the importance of standardized sample collection protocols, optimized sample processing and storage, quality control measures, and the integration of multiple liquid biopsy modalities.

Despite significant improvements in survival of patients with multiple myeloma (MM), outcomes remain heterogeneous, and a significant proportion of patients experience suboptimal outcomes. Importantly, traditional prognostic factors based on data from patients treated with older therapies no longer capture prognosis accurately in the contemporary era of novel triplet or quadruplet therapies. Therefore, risk stratification requires refinement in the context of available and investigational treatment options in routine practice and clinical trials, respectively. The current identification of high-risk MM (HRMM) in routine practice is based on the Revised International Staging System, which stratifies patients using a combination of widely available serum biomarkers and chromosomal abnormalities assessed via fluorescence in situ hybridization. In recent years, a substantial body of evidence concerning additional clinical, biological, and molecular/genomic prognostic factors has accumulated, along with new MM risk stratification tools and consensus reports. The International Myeloma Society, along with the International Myeloma Working Group, convened an Expert Panel with the primary aim of revisiting the definition of HRMM and formulating a practical and data-driven consensus definition, based on new evidence from molecular/genomic assays, updated clinical data, and contemporary risk stratification concepts. The Panel proposes the following Consensus Genomic Staging (CGS) of HRMM which relies upon the presence of at least one of these abnormalities: (1) del(17p), with a cutoff of >20% clonal fraction, and/or TP53 mutation; (2) an IgH translocation including t(4;14), t(14;16), or t(14;20) along with 1q+ and/or del(1p32); (3) monoallelic del(1p32) along with 1q+ or biallelic del(1p32); or (4) β2 microglobulin ≥5.5 mg/L with normal creatinine (<1.2 mg/dL).

Objective: To establish comprehensive recommendations on the management of perihilar cholangiocarcinoma (pCCA) and to identify areas in need of future investigation. Summary Background Data: The lack of consensus in management of pCCA across institutions worldwide impairs optimal patient care and best-achievable oncological outcome. A holistic and critical assessment of the body of evidence and collaborative guidance are required. Methods: The Consensus4pCCA conference developed unbiased consensus using the Zurich-Danish model. An impartial and multidisciplinary jury adopted comprehensive recommendations grounded on the work of eight expert panels answering predefined clinical questions and considering the best-quality evidence through a systematic review. The development of recommendations complied with GRADE and SIGN50 methodologies. Results: Seventy-one international experts considered 570 studies. Ten jury members concluded 71 recommendations covering definition and diagnosis, preoperative assessment and optimization, surgical resection, liver transplantation, and outcome reporting for pCCA patients. The consensus underscored that making patients amenable to high-quality curative resection and reducing its associated morbidity must be of highest priority. As such, multidisciplinary expertise and centralized care at all stages of disease management are critical to ensure both safety and oncological adequacy. To overcome the evidence-gap for rare diseases like pCCA, the jury urged large-scale registries to address open questions across the disease continuum and highlighted priorities for future investigation. Conclusion: The Consensus4pCCA represents an unprecedented commitment to collectively harmonize global treatment strategies for pCCA. This collective effort bridges the gap between expert opinions and clinical evidence and holds great promise to improve patient outcomes in the future.

Abstract How do brain networks limit seizure activity? In the interictal suppression hypothesis, we recently postulated that high inward connectivity to seizure onset zones (SOZs) from non-involved zones (NIZs) is a sign of broader network suppression. If broad networks appear to be responsible for interictal SOZ suppression, what changes during seizure initiation, spread and termination? For patients with drug-resistant epilepsy, intracranial monitoring offers a view into the electrographic networks that organize around and in response to the SOZ. In this manuscript, we investigate network dynamics in the peri-ictal periods to assess possible mechanisms of seizure suppression and the consequences of this suppression being overwhelmed. Peri-ictal network dynamics were derived from stereo electroencephalography recordings from 75 patients with drug-resistant epilepsy undergoing presurgical evaluation at Vanderbilt University Medical Center. We computed directed connectivity from 5 s windows in the periods between, immediately before, during and after 668 seizures. We aligned connectivity matrices across seizures and patients, then calculated net connectivity changes from the SOZ, propagative zone and NIZ. Across all seizure types, we observed two phases: a rapid increase in directed communication towards the SOZ, followed by a collapse in network connectivity. During the first phase, SOZs could be distinguished from all other regions (one-way ANOVA, P = 8.32 × 10−19–2.22 × 10−7). In the second phase and post-ictal period, SOZ inward connectivity decreased yet remained distinct (one-way ANOVA, P = 2.58 × 10−10–1.66 × 10−2). NIZs appeared to drive increased SOZ connectivity while intra-NIZ connectivity decreased concordantly. Stratifying by seizure subtype, we found that consciousness-impairing seizures decrease inward connectivity from the NIZ earlier than consciousness-sparing seizures (one-way ANOVA, P &lt; 0.01 after false discovery correction). Tracking network reorganization against a surrogate for seizure involvement highlighted a possible antagonism between seizure propagation and the ability of the NIZ to maintain high connectivity to the SOZ. Finally, we found that inclusion of peri-ictal connectivity improved the accuracy of SOZ classification from previous models to a combined area under the curve of 93%. Overall, NIZs appear actively to increase inhibitory signaling towards the SOZ during seizure onset, possibly to thwart seizure activity. Although inhibition appears insufficient to prevent seizure onset, the inability to restrict seizure propagation might contribute to loss of consciousness during larger seizures. Dynamic connectivity patterns uncovered in this work might: (i) facilitate accurate delineation of surgical targets in focal epilepsy; (ii) reveal why interictal suppression of SOZs might be insufficient to prevent all seizures; and (iii) provide insight into mechanisms of loss of consciousness during certain seizures.

Barriers to incorporating pharmacogenetics into routine clinical practice in the United States are well documented. Initial surveys by the Clinical Pharmacogenetics Implementation Consortium (CPIC) in 2009 and 2010 identified barriers across four key domains that have hindered the widespread adoption of clinical pharmacogenetic testing. These are presented verbatim as: (i) absence of a definition of the processes required to interpret genotype information and to translate genetic information into clinical actions; (ii) need for recommended drug/gene pairs to implement clinically now; (iii) clinician resistance to consider pharmacogenetic information at the bedside; and (iv) concerns about test costs and reimbursement. Over time, many of these challenges have been overcome, and clinical pharmacogenetic testing has subsequently reached broader implementation. Despite this progress, several barriers remain that block further adoption. This narrative review used authors' expertise and experience to identify and describe current barriers to pharmacogenetic implementation across seven domains in the United States: equity and inclusion; guidelines and supporting evidence; regulatory agency oversight; payer coverage and insurance; availability of quality pharmacogenetic tests; electronic health records; and provider and patient education. Within each domain, it revisits past successes and challenges and explores remaining barriers. We also propose solutions to address ongoing challenges across these domains, including further expansion of recommendations beyond pharmacogenetic‐specific guidelines, standards for designing clinical decision support tools, and broader pharmacogenetics education. Addressing these remaining obstacles directs work to enable broader adoption of clinical pharmacogenetic implementation to ultimately improve patient outcomes.

Abstract Accurate prediction of risk of progression from smoldering (SMM) to active multiple myeloma (MM) is paramount to individualized early therapeutic strategies with minimum risk of overtreatment. Current risk stratification models do not account for evolving biomarker trajectories. We assembled the largest cohort to date of 2,270 SMM patients from six international centers with longitudinal clinical and biological data to train and validate the PANGEA 2.0 risk models. Four evolving biomarkers were significantly associated with shorter time-to-progression: M-protein increase ≥0.2g/dL, involved:uninvolved serum free light chain ratio increase ≥20, creatinine increase >25%, and hemoglobin decrease ≥1.5g/dL. PANGEA 2.0 outperforms established models including the 20/2/20 and IMWG models by more accurately predicting progression (C-statistics=0.69–0.84), even without biomarker history (C-statistics=0.69–0.83) or recent bone marrow biopsy. PANGEA 2.0 is an easy-to-use, open-access tool (https://ghobrial.shinyapps.io/pangea_2_calculator) to improve and individualize SMM risk stratification. Validation tools are available to compare PANGEA 2.0 to established models (https://ghobrial.shinyapps.io/pangea_validation).

PURPOSE To report the results of the multicenter, open-label IRAKLIA trial (ClinicalTrials.gov identifier: NCT05405166 ) of isatuximab subcutaneous (SC) versus intravenous (IV), plus pomalidomide and dexamethasone, in relapsed/refractory multiple myeloma (MM), to our knowledge, the first phase III MM trial using an on-body injector (OBI). METHODS Patients with ≥1 prior line of therapy were randomly assigned 1:1 to Isa OBI (1,400 mg) or IV (10 mg/kg) once weekly in cycle (C)1 and then every 2 weeks, plus pomalidomide (4 mg once daily, day [D]1-21) and dexamethasone (40 mg once weekly [age ≥75: 20 mg]) and treated until progression, unacceptable toxicity, or patient request. Coprimary end points were overall response rate (ORR; noninferiority margin, 0.839) and Isa C trough (C6D1 predose; noninferiority margin, 0.8). Noninferiority of OBI versus IV was demonstrated if both coprimary end points achieved noninferiority. RESULTS IRAKLIA randomly assigned 531 patients (OBI, n=263; IV, n=268). After 12-month median follow-up, the ORR was 71.1% (OBI) and 70.5% (IV; relative risk, 1.008 [95% CI, 0.903 to 1.126]; lower CI exceeded noninferiority margin). The mean (standard deviation) C6D1 C trough was 499 (259) μg/mL (OBI) and 340 (169) μg/mL (IV). The C trough geometric mean ratio (90% CI) was 1.532 (1.316 to 1.784); lower CI exceeded noninferiority margin. Grade ≥3 treatment-emergent adverse event incidences were 81.7% (OBI) and 76.1% (IV); infusion reaction incidences were 1.5% and 25.0%. Injection site reactions occurred in 0.4% of OBI injections (all grade 1-2); 99.9% of injections completed without interruption. CONCLUSION IRAKLIA demonstrated efficacy and pharmacokinetic noninferiority between Isa OBI and IV. No unexpected safety signal was observed, with excellent local tolerability of Isa OBI. Efficacy and safety were comparable with Isa IV in ICARIA-MM, except the lower OBI infusion reaction rate. These results support potential use of the OBI, designed to improve practice efficiency.

e13154 Background: Triple-negative breast cancer (TNBC) is a less common but highly aggressive subtype of breast cancer with poor prognosis and limited therapeutic options. Despite advancements in oncology, significant survival disparities persist among racial, histologic, and socio-demographic groups. This study investigates these disparities and identifies factors contributing to unequal outcomes, providing actionable insights for improving care. Methods: Data on TNBC cases from 2000 to 2021 were extracted from the Surveillance, Epidemiology, and End Results (SEER) database, encompassing 17 registries and 76,265 patients. Patients were categorized by stage, marital status, age, race, and histology. Kaplan-Meier survival analysis was used to estimate median survival with 95% confidence intervals (CI), and the log-rank test assessed differences across groups. Cox proportional hazards regression determined the magnitude of disparities. A p-value < 0.05 was considered statistically significant. Results: Among the 76,265 patients analyzed, those with distant-stage disease had the poorest median survival (51 months; 95% CI: 46–60), compared to localized-stage patients (128 months; 95% CI: 127–129). The youngest cohort (15–19 years) exhibited the lowest survival (43 months), while individuals aged 80–84 had a median survival of 79 months (95% CI: 76–84). South Asians, particularly Pakistani individuals, had the shortest survival among racial groups (83 months). Single patients had lower survival (116 months) compared to married or divorced individuals. Histologically, median survival was 113 months (95% CI: 103–120) for epithelial neoplasms and 78 months for mucoepidermoid neoplasms. All observed differences were statistically significant (p < 0.05). Conclusions: Localized-stage TNBC, individuals aged 40–44, and patients from White or Black racial groups exhibited better survival outcomes, as did those with cystic, mucinous, or serous histologies compared to epithelial neoplasms. Addressing these disparities through tailored treatment strategies and improved access to care is critical. Limitations of this study include the lack of treatment-level data and the potential influence of unmeasured confounders. Stage Marital Status Age Group at Diagnosis Distant Localized Single Divorced 15-19 40-44 80-84 Median Survival(LCL-UCL) 51(46-60) 128(127-129) 116(114-118) 127(124-129) 43(14-NA) 132(130-135) 79(76-84) Neoplasm Histology Race Epithelial Muco-epidermoid Cystic, Mucinous& Serous Pakistani OtherAsian Black White Median Survival(LCL-UCL) 113 (103-120) 78(63-NA) 142(123-NA) 83 (63-NA) 97(91-108) 123 (121-125) 126 (125-127) LCL= Lower Confidence Limit, UCL= Upper Confidence Limit.

2558 Background: Clinical validation studies have shown that early dynamic changes in circulating tumor DNA (ctDNA) tumor fraction (TF) can predict clinical outcomes. Yet few studies have evaluated the clinical value of longitudinal monitoring throughout the course of treatment. Here we evaluate longitudinal changes in ctDNA TF and clinical outcomes in an advanced real-world pan-cancer cohort of patients (pts) treated with immune checkpoint inhibitors (ICIs). Methods: The cohort included deidentified pts from the Tempus clinicogenomic database with stage IIIB or IV solid tumors who underwent ctDNA NGS and were treated with an FDA-approved ICI +/- chemotherapy (CT). Pts had a pre-treatment baseline liquid biopsy (T0) and ≥1 on-treatment sample Ti within 21-180 days of ICI. xM for treatment response monitoring estimates TF via an ensemble algorithm that incorporates variant and copy number information. Response status was determined at each on-treatment timepoint Ti relative to T0. Pts were classified as a Molecular Responder (MR) if TF < 1% at T0 and Ti or if TF decreased by ≥ 50% from T0 to Ti; otherwise, they were classified as a Molecular Non-Responder (nMR). Pts with TF < 0.09% at T0 and Ti were classified as ctDNA not detected. The longitudinal cohort included pts with ≥2 on-treatment timepoints, further classified based on the most frequent classification across each Ti as longitudinal MR, longitudinal nMR and longitudinal ctDNA not detected. If no classification was dominant, the most recent classification was used. Real-world overall survival (rwOS) was defined from T1 to death and assessed by log-rank test. Results: The full cohort of 84 pts with > 10 solid tumors included 34.5% (n = 29) NSCLC and 16.7% (n = 14) SCLC. The majority of pts (59.5%, n = 50) received ICI+CT, (64.0% first-line [1L]), and 40.5% (n = 34) ICI-only (35.3% 1L). rwOS was longer for 53 MRs vs. 18 nMRs (median not reached vs. 7.0 months, P < 0.005); 13 pts had no ctDNA detected. The longitudinal subcohort of 35 pts was 31.4% (n = 11) NSCLC, 20.0% (n = 7) prostate cancer, and 14.3% (n = 5) SCLC; 45.7% (n = 16) ICI+CT (56.3% 1L), 54.3% (n = 19) ICI-only (31.6% 1L). On average, pts had 3 on-treatment liquid biopsies, with a median time between on-treatment samples of 91 days. Twelve pts were longitudinal nMRs (10 MR or ctDNA not detected at T1), 18 longitudinal MRs, and 5 longitudinal no ctDNA detected. There were 6 death events in the longitudinal nMRs, 3 in the longitudinal MRs (all > 18 months after T1), and no death events in the longitudinal no ctDNA detected group. Longitudinal MRs had longer rwOS than longitudinal nMRs (median 37.4 months vs 8.7 months, P < 0.005). Conclusions: Longitudinal nMR was associated with worse survival compared to longitudinal MR. Longitudinal, molecular biomarker dynamics may be a useful clinical treatment decision tool for monitoring treatment response to ICI therapy.