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Abstract Objective Dravet syndrome (DS) is a developmental and epileptic encephalopathy characterized by high seizure burden, treatment‐resistant epilepsy, and developmental stagnation. Family members rate communication deficits among the most impactful disease manifestations. We evaluated seizure burden and language/communication development in children with DS. Methods ENVISION was a prospective, observational study evaluating children with DS associated with SCN1A pathogenic variants ( SCN1A + DS) enrolled at age ≤5 years. Seizure burden and antiseizure medications were assessed every 3 months and communication and language every 6 months with the Bayley Scales of Infant and Toddler Development 3rd edition and the parent‐reported Vineland Adaptive Behavior Scales 3rd edition. We report data from the first year of observation, including analyses stratified by age at Baseline: 0:6–2:0 years:months (Y:M; youngest), 2:1–3:6 Y:M (middle), and 3:7–5:0 Y:M (oldest). Results Between December 2020 and March 2023, 58 children with DS enrolled at 16 sites internationally. Median follow‐up was 17.5 months (range = .0–24.0), with 54 of 58 (93.1%) followed for at least 6 months and 51 of 58 (87.9%) for 12 months. Monthly countable seizure frequency (MCSF) increased with age (median [minimum–maximum] = 1.0 in the youngest [1.0–70.0] and middle [1.0–242.0] age groups and 4.5 [.0–2647.0] in the oldest age group), and remained high, despite use of currently approved antiseizure medications. Language/communication delays were observed early, and developmental stagnation occurred after age 2 years with both instruments. In predictive modeling, chronologic age was the only significant covariate of seizure frequency (effect size = .52, p = .024). MCSF, number of antiseizure medications, age at first seizure, and convulsive status epilepticus were not predictors of language/communication raw scores. Significance In infants and young children with SCN1A + DS, language/communication delay and stagnation were independent of seizure burden. Our findings emphasize that the optimal therapeutic window to prevent language/communication delay is before 3 years of age.

Abstract Purpose: The 2024 ASHP Pharmacy Forecast identifies and contextualizes emerging issues and trends that will influence healthcare, health systems, and the pharmacy profession and provides recommendations to inform long-term strategic planning that should prompt action by pharmacists and health-system leaders. Methods: Drawing on the “wisdom of crowds” concept, a survey was constructed with 6 general themes, each with 6 to 9 focused statements and a seventh theme on preparedness (58 survey items in total). The size of and representation within the survey panel were intended to capture opinions from a wide range of pharmacy leaders. The survey instructed panelists to consider the likelihood of the events/scenarios described in the statements occurring in the next 5 years as being likely, somewhat likely, somewhat unlikely, or very unlikely. Then, survey panelists assessed the preparedness (from very unprepared to very prepared) for 12 of the statements. Results: The 6 survey themes identified were Urgent Public Health Priorities, Responding to the Mental Health Crisis, Achieving Care Equity, New Disease Paradigms and Treatment Innovations, Workforce: Focus on Culture for the Future, and Artificial Intelligence: Can Ethics and Regulators Catch Up? The survey was completed by 250 respondents, yielding an 88% response rate. Analysis of survey results was provided by chapter authors along with strategic recommendations to guide actions for each theme. Conclusion: The focus of the Pharmacy Forecast is on large-scale, long-term trends that will influence healthcare and the pharmacy profession over months and years and not on day-to-day situational dynamics. The report provides insight to stimulate thinking and discussion and provides a starting point to proactively position leaders, their teams, and departments for potential future events and trends.

Context.— Machine learning applications in the pathology clinical domain are emerging rapidly. As decision support systems continue to mature, laboratories will increasingly need guidance to evaluate their performance in clinical practice. Currently there are no formal guidelines to assist pathology laboratories in verification and/or validation of such systems. These recommendations are being proposed for the evaluation of machine learning systems in the clinical practice of pathology. Objective.— To propose recommendations for performance evaluation of in vitro diagnostic tests on patient samples that incorporate machine learning as part of the preanalytical, analytical, or postanalytical phases of the laboratory workflow. Topics described include considerations for machine learning model evaluation including risk assessment, predeployment requirements, data sourcing and curation, verification and validation, change control management, human-computer interaction, practitioner training, and competency evaluation. Data Sources.— An expert panel performed a review of the literature, Clinical and Laboratory Standards Institute guidance, and laboratory and government regulatory frameworks. Conclusions.— Review of the literature and existing documents enabled the development of proposed recommendations. This white paper pertains to performance evaluation of machine learning systems intended to be implemented for clinical patient testing. Further studies with real-world clinical data are encouraged to support these proposed recommendations. Performance evaluation of machine learning models is critical to verification and/or validation of in vitro diagnostic tests using machine learning intended for clinical practice.

OBJECTIVE Diabetes mellitus (DM) is a known risk factor for postsurgical and systemic complications after lumbar spinal surgery. Smaller studies have also demonstrated diminished improvements in patient-reported outcomes (PROs), with increased reoperation and readmission rates after lumbar surgery in patients with DM. The authors aimed to examine longer-term PROs in patients with DM undergoing lumbar decompression and/or arthrodesis for degenerative pathology. METHODS The Quality Outcomes Database was queried for patients undergoing elective lumbar decompression and/or arthrodesis for degenerative pathology. Patients were grouped into DM and non-DM groups and optimally matched in a 1:1 ratio on 31 baseline variables, including the number of operated levels. Outcomes of interest were readmissions and reoperations at 30 and 90 days after surgery in addition to improvements in Oswestry Disability Index, back pain, and leg pain scores and quality-adjusted life-years at 90 days after surgery. RESULTS The matched decompression cohort comprised 7836 patients (3236 [41.3] females) with a mean age of 63.5 ± 12.6 years, and the matched arthrodesis cohort comprised 7336 patients (3907 [53.3%] females) with a mean age of 64.8 ± 10.3 years. In patients undergoing lumbar decompression, no significant differences in nonroutine discharge, length of stay (LOS), readmissions, reoperations, and PROs were observed. In patients undergoing lumbar arthrodesis, nonroutine discharge (15.7% vs 13.4%, p < 0.01), LOS (3.2 ± 2.0 vs 3.0 ± 3.5 days, p < 0.01), 30-day (6.5% vs 4.4%, p < 0.01) and 90-day (9.1% vs 7.0%, p < 0.01) readmission rates, and the 90-day reoperation rate (4.3% vs 3.2%, p = 0.01) were all significantly higher in the DM group. For DM patients undergoing lumbar arthrodesis, subgroup analyses demonstrated a significantly higher risk of poor surgical outcomes with the open approach. CONCLUSIONS Patients with and without DM undergoing lumbar spinal decompression alone have comparable readmission and reoperation rates, while those undergoing arthrodesis procedures have a higher risk of poor surgical outcomes up to 90 days after surgery. Surgeons should target optimal DM control preoperatively, particularly for patients undergoing elective lumbar arthrodesis.

Background. Some patients who present with clinical features consistent with idiopathic hypereosinophilic syndrome (HES; absolute eosinophil count (AEC) ≥1.5 x 10 9/L with related end organ damage) are ultimately diagnosed with a myeloid neoplasm. Although FIP1L1::PDGFRA is the most common molecular abnormality in this setting, many other fusion genes, point mutations and cytogenetic abnormalities have been implicated in driving primary (neoplastic) eosinophilia. Given the poor prognosis of these disorders in the absence of treatment and the availability of targeted therapies for many of the driver mutations, it is becoming increasingly important to rapidly identify the underlying genetic alteration. In this regard, the expense and variable sensitivity of molecular diagnostic tests remains problematic. Although clinical features have been reported to distinguish between PDGFRA-associated myeloid neoplasms and D816V KIT-positive systemic mastocytosis with hypereosinophilia, little is known about the clinical phenotypes of other subsets of patients. This multicenter retrospective study aimed to assemble a large cohort of patients with HES secondary to a myeloid neoplasm to explore the utility of clinical and laboratory features in predicting the underlying molecular abnormality. Methods. Retrospective, de-identified data from 16 centers were collected via an online Research Electronic Data Capture repository. Patients and associated data were obtained from in-house research databases and/or electronic medical record searches at each site. Clinical and laboratory data were entered in accordance with local Institutional Review Boards. Inclusion criteria were peripheral blood hypereosinophilia (AEC &gt;1.5 x 10 9/L) on at least two occasions and one of the following: ≥1 confirmed genetic abnormality recurrently associated with primary myeloid neoplasms, other evidence of clonal eosinophilia, or increased blasts (≥2% in the blood or &gt;5% but &lt;20% in the marrow). Patients with acute myeloid leukemia were excluded. Results. A total of 277 patients followed between 1990 and 2022 were included in the analysis. Median length of follow up was 31 months (range &lt;1-356), and 217/277 (78%) were alive at last follow up. The most common genetic abnormality was FIP1L1::PDGFRA (n=131) followed by D816V KIT mutations (n=39) and alterations involving JAK2 (n=22) (Figure 1). Five patients had genetic abnormalities involving two distinct genes recurrently associated with eosinophilic myeloid neoplasms. The overall median age at diagnosis was 55 years (range 12-89) and 79% of the patients were male. When patients with abnormalities involving PDGFRA and PDGFRB were excluded from the analysis, the male predominance was significantly lower at 62% (p&lt;0.001, Fisher's exact test as compared to the data set as a whole). The overall pattern of organ system involvement was similar irrespective of the underlying genetic abnormality with a few notable exceptions. Cardiac involvement was most common in patients with FIP1L1:: PDGFRA, abnormalities involving JAK2 or without pathologic alterations identified (reported in 22%, 32% and 30%, respectively); whereas skin and gastrointestinal involvement, lymphadenopathy and splenomegaly were most frequent in patients with KIT D816V. Laboratory abnormalities also differed between groups. Whereas anemia was the most common blood abnormality (reported in &gt;50% of patients), erythrocytosis was noted primarily in patients with abnormalities involving JAK2. In contrast, circulating blasts were identified in 70% of patient with BCR::ABL1 and 29% of patients with chromosomal abnormalities or KIT D816V, but in &lt;15% of patients in any of the other groups. Whereas peak AEC alone did not discriminate between the different patient groups, the AEC/tryptase ratio was increased in patients with PDGFRA-associated myeloid neoplasms, molecular abnormalities involving JAK2, or chromosomal abnormalities as compared to those with KIT mutations (Figure 2). Conclusions. Despite the limitations of retrospective data analysis, the data from this large multicenter cohort of patients with HES due to a chronic myeloid neoplasm suggest that routine demographic, clinical and laboratory features vary depending on the underlying molecular abnormality. This approach could ultimately help guide empiric therapy when molecular studies are negative or unavailable.

Background: Myelodysplastic/Myeloproliferative neoplasms (MDS/MPN) represent a group of rare hematologic malignancies, distinguished by their concurrent dysplastic and proliferative features. Patients with these neoplasms have an increased risk of acute leukemia transformation and often present with extramedullary and constitutional symptoms. The only approved therapies for MDS/MPNs are hydroxyurea, decitabine (oral decitabine/cedazuridine and parenteral decitabine) or azacitidine (parenteral) for pts with CMML. Given the rarity and the heterogeneity of MDS/MPNs, prospective studies focusing specifically on MDS/MPN have been uncommon, and refining treatment strategies has been difficult. ABNL-MARRO ( A Basket study of Nove l therapy for untreated MDS/MPN and Relapsed/ Refractory Overlap Syndromes) is an international cooperative effort that leverages the expertise of the MDS/MPN International Working Group (IWG) and provides a framework for collaborative studies around the world to advance treatment of MDS/MPN and to explore clinical and pathologic markers of disease severity, prognosis, and treatment response (Moyo TK et.al BMC Cancer. 2022). Methods: ABNL-MARRO 001 (AM-001) is an open-label, phase 1b/2 study testing the treatment combination of ASTX727 (days 1-5), a fixed dose oral combination pill containing 35 mg of the DNMTi decitabine (DEC) and 100 mg of the cytidine deaminase inhibitor cedazuridine (CED), together with a series of active agents in myeloid disease (see Figure 1a) for MDS/MPN. In arm A, ASTX727 is combined with itacitinib 300 mg (days 1-28), a selective JAK1 inhibitor in newly diagnosed and relapsed/refractory (R/R) pts. Here we report results from the 3+3 dose de-escalation phase 1b portion used to determine the recommended Phase 2 dose (RP2D) in arm A. Dose-limiting toxicities (DLTs) were assessed in cycle 1. Disease response was assessed by the MDS/MPN IWG response criteria (Savona et.al., Blood. 2015). Results: Seven patients were enrolled with a median age 75 (range 32-82) years with newly diagnosed (4 pts) or R/R (3 pts) MDS/MPN. Three patients had CMML, 2 had MDS/MPN-U, and 2 had refractory MDS/MPN RST. One patient was not DLT evaluable given severe disease-induced cytopenia, and was not included in the assessment (patient 4 in Figure 1b). The majority of pts experienced a treatment-emergent adverse event (TEAE) of any grade; the most common (≥30% of pts) were thrombocytopenia (50%), neutropenia (30%), and constipation (30%); 50% of pts experienced a Grade ≥3 TEAE; the most common was neutropenia (30%). No DLTs were reported, and these AEs were consistent with what has been reported in the use of ASTX727 (Savona et al. Blood. 2022). One patient achieved a CR, and two additional patients had the best overall response of optimal marrow response after receiving 6 cycles of treatment. All patients are alive with a median follow-up of 12 months (range 6-17 months). The clinical responses and time-on-treatment of all pts in phase 1b are summarized in Figure 1b. Summary/Conclusion: Based on the preliminary results of the phase 1b study, the dosing schedule of 35 mg DEC / 100 mg CED daily for 5 days in combination with itacitinib 300 mg daily for 28 days was selected as the RP2D as it balanced clinical efficacy with an acceptable and manageable safety profile. This regimen and dose are being utilized in a 28-day cycle in the ongoing global, multi-center phase 2 study (NCT04061421).

Introduction: Telomere biology disorders (TBD) are multisystem diseases often associated with bone marrow failure (BMF) and pulmonary fibrosis. TBD are clinically diagnosed when mean telomere lengths (TL) in blood cells measured by clinical flowFISH assays fall &lt;1 st percentile, in comparison to age-matched reference controls. This information has limitations, e.g. TL in blood cells may not represent TL in other organs (e.g. lung, liver) and moreover, individuals with high clinical suspicion of TBD can show borderline average TL which complicates their diagnosis. The likely reason for this is that cell senescence can be triggered by shortening of a subset, or even a single chromosome arm telomere, a situation that may be missed when measuring average TL. Previous approaches to measure individual chromosome-arm telomere length (CA-TL) are only available for a small number of chromosome arms or can only estimate the number of shortened telomeres without matching them to specific chromosome arms. Taking advantage of recent developments in long-read next generation sequencing (NGS) and the availability of the recently published telomere-to-telomere (T2T) reference human genome, our group developed Telogator, (Stephens Z. et al, 2022) a bioinformatic tool that estimates CA-TL for most chromosome arms using long-read NGS data. Here we use Telogator to describe for the first time the CA-TL pattern in TBD patients in comparison with a control non-TBD cohort. Methods: TBD patients were identified through the Pre-Myeloid and Bone Marrow Failure Specialty Clinic at Mayo Clinic. All patients underwent flowFISH and genetic testing. Age-matched non-TBD patients identified at the Center for Individualized Medicine (Mayo Clinic) were used as reference controls. Informed consent was obtained from all individuals with approval from the Mayo Clinic Institutional Review Board. DNA from peripheral blood mononuclear cells was sequenced using PacBio Sequel II following the manufacturer indications for HiFi sequencing. BAM files were aligned to the T2T reference and CA-TL was calculated using Telogator as described in Stephens Z. et al. 2022. Average TL, CA-TL, and percent of short telomeres (both defined as &lt;5 kb and &lt;3.2 kb) were calculated. Comparisons of average TL and percent of short telomeres were performed using t-test, while Wilcoxon rank-sum test was used to compare CA-TL. Results: Four TBD patients [median age = 58.5 (52-60), 50% female] and 6 non-TBD controls [Median age = 56 (50-63), 33% female] were included in the analysis. All TBD patients presented average TL below the 1 st centile in both lymphocytes and granulocytes, and TBD-related phenotype (100% with pulmonary fibrosis, 50% with BMF, 25% with liver fibrosis). Three had a pathogenic variant in a TBD related genes [2 in TERT (NM_198253.3: c.2030G&gt;A, p.(Gly677Asp) and c.2515_2533del, p.(Thr839Alafs*29)) and 1 in NHP2 (NM_017838.3: c.459_460delAT; p.(X154Argext29))]. The average TL calculated by Telogator showed high correlation with flowFISH values (r 2 = 0.9883, p = 0.0059) and was lower in TBD patients than controls (p = 0.0012). Next, when comparing individual CA-TL between groups, only half of CA-TL was statistically different in the TBD group compared to controls (1p, 3q, 4p, 5p, 5q, 6q, 7p, 7q, 8q, 9p, 9q, 10q, 11p, 12q, 12q, 16p, 16q, 18q, 19p, 19q, 20p, 20q, 21q - Figure 1). The percentage of telomeres &lt;5kb and &lt;3 kb was significantly increased in TBD patients compared to controls (p= 0.014 and 0.0333, respectively). Discussion: Using a novel informatic tool, we replicate previous results obtained using classic approaches and were able to expand on these studies by measuring specific CA-TL in TBD patients. We identified statistically significant differences at the CA-TL level in these patients when compared to age-matched controls, while other CA-TL were not statistically different. Future studies and the inclusion of additional TBD patients will help define the clinical relevance of the differential CA-TL shortening and its prevalence among TBD patients. While limited by the small number of samples in the study, we show the feasibility of using this approach to study TL with unprecedented resolution and show that Telogator offers important advantages compared to classic methods to study telomere biology that can be used in other relevant fields like aging and/or cancer. Our results pave the way to advance the mechanistic understanding of TBD.

Background: Anaplastic large cell lymphomas (ALCLs) are CD30-positive T-cell lymphomas that share pathologic features but differ in clinical presentation, outcome, and molecular features. The World Health Organization (WHO) and International Consensus Classification (ICC) classify ALCLs by presence or absence of ALK rearrangements (R) and clinical presentation (systemic, cutaneous [c], or breast implant-associated [BIA]). ICC, but not WHO, recognizes DUSP22-R as defining a new genetic subtype of ALK- ALCL. The classifications otherwise do not reflect additional molecular heterogeneity in genetics (e.g., TP63-R) or therapeutic vulnerabilities (e.g., JAK-STAT3 pathway activation). Methods: ALCLs (N=689) underwent expert consensus review (WHO/ICC) through the Lymphoma/Leukemia Molecular Profiling Project (LLMPP). All cases also underwent genetic subtyping (ALK, DUSP22, TP63, and triple-negative [TN]) using fluorescence in situ hybridization (FISH) and immunohistochemistry (IHC), as well as IHC for phospho-STAT3 Tyr705 (pSTAT3). RNAseq was performed and evaluable in 393 cases; the remaining cases had insufficient tissue, tumor content, RNA yield or quality, and/or sequencing data quality. Sequenced and non-sequenced sub-cohorts had similar demographics and subtype distribution. Results: Unsupervised gene expression profiling (GEP) identified 2 main molecular types of ALCL. Type I ALCLs predominantly included ALK+ ALCLs, BIA-ALCLs, and a subset of TN ALCLs (designated TN-I), whereas Type II ALCLs predominantly included ALCLs with DUSP22-R, TP63-R, or both (double-hit; DH), and the remaining TN ALCLs (TN-II). Type I ALCLs were strongly associated with pSTAT3 expression (74.2±26.4% positive malignant cells vs 9.9±22.7% for Type II; P&lt;0.0001). An independently derived pSTAT3 staining threshold of 30% assigned Type I vs II with 91% accuracy. A third cluster of ALCLs, mostly cALCL, showed an epithelial GEP signature rather than a lymphoma signature; these cases were assigned to Types I or II based on pSTAT3 IHC. Distinct sub-signatures were identified for ALK+, DUSP22-R, TP63-R, and BIA ALCL (Fig. 1), but not ALK- ALCL or cALCL. Gene set enrichment analysis showed Type I ALCLs to be enriched for JAK-STAT3 signaling genes (normalized enrichment score [NES], 2.22; FDR&lt;0.0001) and related pathways, such as TNFα-NFκB signaling (NES, 2.21; FDR&lt;0.0001). In contrast, Type II ALCLs were enriched for cell cycle, DNA repair, epigenetic, and metabolic pathway genes, but not for major tyrosine kinase-mediated signaling pathway genes. Enriched epigenetic pathways included chromatin modifying enzymes (NES, -1.86; FDR=0.002) and histone methylation (NES, -1.71; FDR=0.002). EZH2 was the most overexpressed gene in Type II ALCLs (fold-change, 7.74; FDR=8.84×10 -306). At the protein level, EZH2 IHC H-scores were 275±45 in Type II and 168±70 in Type I ALCLs (P&lt;0.0001); H3K27me3 H-scores were 170±81 and 76±63, respectively (P&lt;0.001). The top metabolic gene set involved cholesterol biosynthesis (NES, -1.88; FDR=0.002). Overall survival (OS) data were available in 257 systemic ALCL patients (145 sequenced and 112 non-sequenced; cALCL and BIA-ALCL were excluded). Non-sequenced TN ALCLs were assigned to TN-I or TN-II using pSTAT3 IHC. The results supported earlier data indicating favorable prognosis of DUSP22-R ALCL (5 y OS, 95%) and ALK+ ALCL (87%), intermediate prognosis of TN ALCL (TN-I, 52% and TN-II, 38%; P=NS), and poor prognosis of TP63-R/DH ALCL (0%)(P&lt;0.0001; Fig. 2). Conclusions: Two overarching molecular types of ALCL exist, predominantly associated with the presence (Type I) or absence (Type II) of the JAK-STAT3 signaling program. Distinct GEP signatures exist for ALK+ ALCL and BIA-ALCL (predominantly Type I), and DUSP22-R ALCL and TP63-R ALCL (predominantly Type II). TN ALCLs lacking ALK-R, DUSP22-R, and TP63-R can be stratified into TN-I and TN-II subtypes. pSTAT3 IHC has &gt;90% accuracy as a surrogate for GEP-based subtyping. ALK- ALCL and cALCL cluster by molecular subtype rather than by defining GEP signatures. Type II ALCLs are enriched for targetable epigenetic and metabolic pathways, including EZH2/histone methylation and cholesterol biosynthesis. This molecular classification is diagnostically, prognostically, and potentially therapeutically relevant, and can be applied using FISH and IHC in routine practice and in the clinical trial setting.