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Background: While myeloproliferative neoplasms (MPN), including essential thrombocythemia (ET), polycythemia vera (PV), and primary myelofibrosis (MF), are usually sporadic, adult-onset neoplasms, an increasing number of germline risk alleles have been described (e.g. EGLN1, ETV6, SH2B3, and ATM) in these disorders. DDX41MT Germline Predisposition Syndrome (GPS) is the most common myeloid GPS in adults and while there is extensive data on MDS/AML, little is known regarding MPN occurring in this context. We carried out this study to define the prevalence and characteristics of DDX41MT-GPS associated MPN. Methods: After IRB approval, we retrospectively assessed the Mayo Clinic cohort of 174 patients with DDX41MT-GPS, which included both pathogenic and clinically relevant germline variants of undetermined significance (VUS), based on our previous analysis (Badar et al Haematologica 2023). Standard statistical measures were applied. Results: We identified 12 (6.9%) patients with MPN (ET-5, PV-2, PMF-4, MPN-NOS-1). The median age at MPN diagnosis was 61.2 years (range, 8.-70.4); 58.3% (n=7) were male, and 83.3% (n=10) were Caucasian. A family history of hematologic malignancy was present in 16.7% (n=2, AML and T-LGL), while 50% (n=6) had a family history of visceral malignancies and 41.7% (n=5) had no family history of malignancies. Among ET patients (n=5) with DDX41MT-GPS, JAK2V617F was the MPN driver in 4 (80%) while type 1-CALR (L367fs*46) was a driver in 1 (20%). This included a 9-year-old child diagnosed with JAK2V617FMT ET. The DDX41 variant was classified as pathogenic in 40% (n=2; E113Kfs*14, D140Gfs*2) and VUS in 60% (n=3; V544L, V591I, P38L). Bone marrow (BM) aspirates in the ET patients were hypercellular in 40% (n=2), normocellular in 40% (n=2) and hypocellular in 20% (n=1), and none had increased blasts, or reticulin fibrosis (RF). In addition to JAK2V617F, somatic mutations seen included SF3B1 (K666T, VAF 16%) in 1 patient and IDH2 (R140Q, VAF 6%) and DNMT3A (R882H, VAF 7%) in 1 patient, respectively. With a median follow-up from diagnosis of 3.9yrs (range 2.9-8.9), there were no thrombotic events and no disease progressions was documented. There were 2 patients with JAK2V167FMT PV in whom the DDX41MT were clinically significant VUS (c.138+5G>T and M155I). Both patients had hypercellular BM, with no increase in blasts, no RF, normal karyotypes and no additional somatic mutations. With a median follow up of 7.5yrs (range, 2.1-12.9), 1 patient developed a deep vein thrombosis (DVT) and there were no fibrotic or leukemic transformations. There were 4 patients with PMF; 3 (75%) with JAK2V617F and 1(25%) with a type 1-CALR driver mutation (L367fs*46). DIPPS-plus scores ranged from 1 to 4 (median 2.5). The DDX41 variants were pathogenic in 50% (n=2, E256K and P78Qfs*3) and VUS in 50% (n=2, P510S and M155I). The median grade of RF at PMF diagnosis was grade 2 (range, 2-3). BM were hypercellular in 75% (n=3) and hypocellular in 25% (n=1), and 1 patient had 3% peripheral blasts (and no BM blasts). Somatic co-mutations included TET2 in 1 patient with a JAK2V617F, and CBL, EZH2 and SRSF2 in 1 patient with a CALR driver-mutation, respectively. PMF patients were treated with ruxolitinib (n=3), stem cell transplant (n=1), and pIFNα (n=1). With a median follow up of 3.9yrs (range,1.1-21.9), all patients were alive, and none had leukemia transformation. There was 1 patient with a JAK2V617F MPN-NOS with trisomy 9, where the DDX41MT-GPS was a VUS (I215L). There were no somatic co-mutations and at last follow up (3.1 years), there was no evidence for progression. Conclusions: While associations between late onset MDS/AML and DDX41MT-GPS has been well established, we systematically describe the MPN landscape seen in this context. MPN was diagnosed in 7% of our cohort, with JAK2V617F being the most common driver mutation. Most importantly, unlike in AML/MDS, where somatic DDX41 mutations are frequently associated with neoplastic transformation (30-50%; R525H being most common), none of our MPN patients had a somatic DDX41 mutation. Our work underscores the importance of germline mutation testing in patients with MPN.

Background: Chromosomal rearrangements involving the KMT2A gene and mutations involving the nucleophosmin (NPM1) gene have been associated with response to menin inhibitors in multiple studies of acute myeloid leukemia (AML) patients characterized by these genetic alterations. Both alterations are more common in younger AML patients and those with NPM1 mutations historically perform better. However, the prevalence and outcomes of older (≥60 years) AML patients with these alterations who are treated with current therapies is less well understood. We present results from the Beat AML Master Trial (BAMT) that analyze the outcomes of this large, but less common subset of patients in an older AML population. Methods: Patients were consented and enrolled on this precision medicine-based Beat AML Master Trial (NCT03013998) from November 2016 to June 2024. Patients were included in this analysis if they harbor either the classic NPM1 mutation or a KMT2A rearrangement (over 10 different gene partners). Additionally, 2 patients with a NUP98 rearrangement were included with the KMT2A cohort as they are known to have similar biology in terms of menin dependence. These patients were treated with the following therapies: a sub-study specific targeted therapy for the dominant clone, venetoclax + hypomethylating agent (Ven/HMA), intensive chemotherapy (IC), alternative non-intensive therapy (NIT), or no therapy. Clinical/genetic characteristics and median overall survival (OS) were analyzed in each group separately. Overall survival (OS) was calculated from master consent and estimated using the Kaplan-Meier method. Results: Of 1096 AML patients enrolled on the BAMT, 246 patients had either an NPM1 (N=207, 18.9%) or KMT2A (N=39, 3.6%) genetic alteration. The baseline characteristics for the NPM1 cohort were median age 72 years (range: 60-92), 50% female, and ECOG performance status: 0-16%, 1-58%, 2-25% and 3-1%. Additional disease characteristics include treatment related AML at 11% and complex karyotype (≥3 abnormalities) at 3%. Median OS for the entire NPM1 cohort was 18.4 months (95% CI: 14.2-24.7). Patients were treated on a sub-study (35%), Ven/HMA (19%), IC (26%), NIT (8%) or no treatment (9%). Between treatment groups, median OS was 21 months (95% CI: 12.8-31.7) for those treated on a sub-study, 22 months (95% CI: 12.6-not reached (NR)) for Ven/HMA, 41.6 months (95% CI: 18.2-NR) for IC, and 6.3 months (95% CI: 1.3-23) for NIT, which was significantly different (p<0.0001). The baseline characteristics for the KMT2A cohort were median age 69 years (range: 60-88), 44% female, and ECOG performance status: 0-19%, 1-45%, 2-35% and 3-0%. Treatment related AML occurred in 23% of patients and complex karyotype in 31%. Median OS for the KMT2A cohort was 6.5 months (95% CI: 3.6-31.6). Patients were treated on a sub-study (38%), Ven/HMA (15%), IC (15%), NIT (15%), or no treatment (5%). Between treatment groups, median OS was 31.6 months (95% CI: 3.2-NR) for sub-study, 5.0 months (95% CI: 3.0-NR) for Ven/HMA, 12.7 months (95% CI: 4.9-NR) for IC, and 2.9 months (95% CI: 1.5-NR) for NIT, which was also significantly different (p<0.0001). Conclusions: In this cohort of older AML patients who possess NPM1 or KMT2A mutations, initial demographics and clinical characteristics upon presentation are as expected. Within each cohort and depending on the type of therapy received, there were interesting differences in survival. Median OS was the highest for the NPM1 cohort that received IC while the KMT2A cohort had the highest median OS when enrolled on a KMT2A targeted sub-study; a finding that supports precision-based medicine for this high-risk KMT2A group characterized by poor outcomes. As menin inhibitor combinations with induction chemotherapy or Ven/HMA move to the frontline setting, we anticipate seeing significant improvement in outcomes for AML patients in both of these genomic subsets. Further multivariable analysis will be performed to validate treatment effect on OS. Our analyses for these two cohorts also provide valuable outcome benchmarks for the design of future precision oncology studies that seek to improve survival in these subsets of older AML patients.

Background: Chronic lymphocytic leukemia (CLL) is one of the most common leukemias in the United States (US), with an estimated incidence of 20,700 cases in 2024. Population-based studies conducted in Olmsted County (OC), Minnesota, reported an increase in CLL incidence over a 55-year period (1935 through 1989), which was attributed to increased detection of early-stage cases in individuals over age 50. In an updated study from 2000 to 2010 in OC, we reported no further increase in the incidence of CLL using the 2008 International Workshop on CLL (IWCLL 2008) guidelines. Additionally, when we compared the 1996 National Cancer Institute Working Group (NCI-WG 96) criteria with the IWCLL 2008 guidelines incorporating the monoclonal B-cell lymphocytosis designation, we found that the use of the IWCLL 2008 guidelines reduced the overt CLL incidence, modified the distribution of Rai Stages at diagnosis, and shortened the median time to first treatment (TTFT). Over the last two decades, 5-year survival for CLL has increased due to new therapies and improved supportive care. Herein we provide updated data on the incidence, prevalence, and natural progression of CLL in OC and studied similar features in an expanded 6-county region around Mayo Clinic, Rochester. Methods: We utilized the Rochester Epidemiology Project (REP), a population-based medical records linkage system, to identify CLL cases from 2000 to 2020 using International Classification of Diseases codes. We included individuals residing in OC and the expanded 7-county region (REP-7, including OC), for which data became available starting in 2010. CLL cases were included if they met the IWCLL 2008 criteria. All CLL diagnoses were confirmed by manual review of medical records and data on CLL-related factors were collected, including treatment status, prior history of other cancers, and overall survival (OS). Age- and sex-specific incidence rates were derived from REP census data and adjusted to the 2020 US white population. OS analyses were conducted using the Kaplan-Meier method. TTFT was calculated with death as a competing risk. Cox regression was used to evaluate the effect of decade on TTFT and OS among patients in OC. Results: From 2010-2020, 242 patients were diagnosed with CLL in REP-7, and between 2000-2020, 174 patients were diagnosed in OC. Among the 242 CLL patients in REP-7, the median age at diagnosis was 71 years (range 30-96),158 (65%) were male, 236 (99%) were white, and 74 (31%) had a history of other cancer, with non-melanoma skin cancer being the most common. After age and sex adjustment to the 2020 US white population, the CLL incidence in REP-7 and OC from 2010 to 2020 was 7.8 and 8.1 per 100,000 individuals, respectively. In OC, the age- and sex-adjusted CLL incidence from 2000 to 2020 was 7.5 per 100,000 individuals, showing no significant trend changes over time. Among the 242 patients diagnosed with CLL in REP-7 between 2010 and 2020, 102 received treatment with a median TTFT of 9.8 years. In OC from 2000 to 2020, 79 out of 174 patients received treatment with a median TTFT of 9.4 years. When comparing across two decades in OC, the median TTFT was 12.8 years for the period from 2000 to 2009, decreasing to 5.9 years between 2010 and 2020, but was not significantly different after accounting for age and sex. The median OS for patients diagnosed with CLL in REP-7 from 2010 to 2020 was 11 years. The median OS for patients in OC between 2000 to 2020 was 12.6 years. When comparing across decades in OC, the median OS was 8.9 years for the period from 2000 to 2009, increasing to 13.6 years for those diagnosed between 2010 and 2020, but this trend was not significantly different after accounting for age and sex. Prevalence data for REP-7 and OC were analyzed as of 01/01/2020. Additionally, prevalence data for OC were available for 01/01/2010. In REP-7, the prevalence of CLL was 97 per 100,000 individuals on 01/01/2020. In OC, the CLL prevalence was 86 per 100,000 individuals on 01/01/2010, and 100 per 100,000 individuals on 01/01/2020. Conclusions: We observed no substantial increase in the incidence rates of CLL in REP-7 from 2010 to 2020, nor in the 20 years of available data from OC. However, the prevalence of CLL in OC increased by 16% from 2010 to 2020. Additionally, evidence indicated a longer OS among newly diagnosed CLL cases in OC compared to previous decades, suggesting a potential impact of improved therapeutic approaches on OS.

Importance Neoadjuvant therapy (NT) is an increasingly used treatment strategy for patients with localized pancreatic ductal adenocarcinoma (PDAC). Little research has been conducted on cancer care delivery during NT, and the standards for optimal delivery of NT have not been defined. Objective To develop consensus best practices for delivering NT to patients with localized PDAC. Design, Setting, and Participants This study used a modified Delphi approach consisting of 2 rounds of voting, and a series of virtual conferences (from October to December 2023) to reach expert consensus on candidate best practice statements generated from a systematic review of the literature and expert opinion. An interdisciplinary panel was formed including 47 North American experts from surgical, medical, and radiation oncology, radiology, pathology, gastroenterology, integrative oncology, anesthesia, pharmacy, nursing, cancer care delivery research, and nutrition as well as patient and caregiver stakeholders. Main Outcome and Measures Statements that reached 75% agreement or greater were included in final consensus statements. Results Of the 47 participating panel members, 27 (57.64%) were male, and the mean (SD) age was 47.6 (8.2) years. Physicians reported completing training a mean (SD) 14.6 (8.6) years prior and seeing a mean (SD) 110.6 (38.4) patients with PDAC annually; 35 (77.7%) were in academic practice. Final consensus was reached on 82 best practices for delivering NT. Of these, 38 statements focused on pre-NT practices, including diagnosis and staging (n = 15), evaluation and optimization (n = 20), and decision-making (n = 3); 29 statements defined best practices during NT, including initiation (n = 3), delivery of therapy (n = 8), restaging practices (n = 12), and management of complications during NT (n = 6); and 15 best practices were identified to guide treatment post-NT, focusing on surgery (n = 7), pathology (n = 4), and follow-up (n = 3). Conclusions Using a modified Delphi consensus technique, best practice guidelines were developed focusing on the optimal standards for delivering NT to patients with localized PDAC. Given the prognostic importance of completing multimodality therapy, efforts to standardize and optimize the delivery of NT represent an immediate opportunity to decrease care variation and improve outcomes for patients with PDAC. Future research should focus on validating and implementing best practice standards into clinical practice.

Abstract Rationale Idiopathic pulmonary fibrosis (IPF) is a complex and heterogeneous disease. Given this, we reasoned that differences in genetic profiles may be associated with unique clinical and radiologic features. Computational image analysis, sometimes referred to as radiomics, provides objective, quantitative assessments of radiologic features in subjects with pulmonary fibrosis. Objectives To determine if the genetic risk profile of patients with IPF identifies unique computational imaging phenotypes. Methods Participants with IPF were included in this study if they had genotype data and computed tomography (CT) scans of the chest available for computational image analysis. The extent of lung fibrosis and the likelihood of a usual interstitial pneumonia (UIP) pattern were scored automatically using two separate, previously validated deep learning techniques for CT analysis. UIP pattern was also classified visually by radiologists according to established criteria. Results Among 329 participants with IPF, MUC5B and ZKSCAN1 were independently associated with the deep learning–based UIP score. None of the common variants were associated with fibrosis extent by computational imaging. We did not find an association between MUC5B or ZKSCAN1 and visually assessed UIP pattern. Conclusions Select genetic variants are associated with computer-based classification of UIP on CT in this IPF cohort. Analysis of radiologic features using deep learning may enhance our ability to identify important genotype–phenotype associations in fibrotic lung diseases.

Abstract GBM AGILE(NCT03970447) is a phase 2/3 Bayesian adaptive registration platform trial testing multiple therapies against a common control. Paxalisib, a PI3K/mTOR inhibitor, is the 3rd arm in the trial to conclude evaluation. METHODS Paxalisib was open to patients with newly diagnosed unmethylated (NDU) and recurrent (RD) glioblastoma, with three possible signatures: NDU, RD, and All(NDU+RD). Arm enrollment occurred Dec2020 through May2022. Control patients were enrolled from study initiation (July2019) and were treated with temozolomide(NDU) or lomustine(RD). GBM AGILE investigational arms have 1 or 2 stages, with adaptive randomization in stage 1 and fixed randomization if arms continue to stage 2. Efficacy is based on OS hazard ratio(HR) of Arm/Control. Efficacy goal is final Bayesian probability ≥ 98% for HR<1.00 in combined Stages. An Arm continues to Stage 2 if Bayesian predictive power (PP) ≥ 0.8. An Arm stops accruing in Stage 1 if it reaches maximal sample size(N) or does not meet a minimum efficacy threshold (PP<0.25 for all signatures when N>50). Clinical cut-off is 12 months after accrual stops. The maximum N for paxalisib was approximately 150(Stage 1) and 50(Stage 2). RESULTS After paxalisib reached >150 patients in Stage 1, accrual stopped [Paxalisib/control N 54/75(NDU), 100/188(RD)]. Neither PP thresholds for moving to Stage 2 nor stopping for minimum efficacy were met. Following an unplanned public disclosure that the arm did not continue to stage 2, clinical cut-off for final analysis (planned May2023) was updated to public disclosure date (August2022). At final analysis mean HRs were 0.89(NDU), 1.25(RD), 1.05(All), probabilities of HR<1.00 of 0.72(NDU), 0.076(RD), 0.398(All). Model estimated median OS paxalisib/control (months) were 14.77/13.84(NDU) and 8.58/10.06(RD). CONCLUSION Paxalisib did not show survival benefit over cumulative control in final primary analysis; additional secondary analyses are being considered. GBM AGILE continues to rapidly and efficiently assess therapies in ND and RD glioblastoma.

Background: Abdominal musculature injuries comprise the third most prevalent time-loss injury across professional baseball. Despite increased awareness and prevention attempts in the recent decade, the trends of these abdominal injury numbers in Major League Baseball (MLB) are not fully understood. Purposes: To update the trends in oblique and intercostal injuries, analyze the impact of these injuries based on time out of play, and identify factors that correlate with increased injury severity to help with recovery time prognostication for the sports medicine community. Study Design: Descriptive epidemiology study. Methods: Using the MLB Health and Injury Tracking System, the authors identified all abdominal and core musculature injuries that resulted in time out of play in MLB and Minor League Baseball (MiLB) between the 2011 and 2021 seasons. These were filtered for injuries that resulted in ≥1 days missed (DM) during spring training, the regular season, and postseason. A Student t test was utilized to assess for significant differences for all normally distributed values. Regression analysis was utilized for determining change over time. For all statistical comparisons, the threshold for alpha was set to P < .05. Results: During the study period between 2011 and 2021, there were 4560 total abdominal injuries among 3401 athletes. When filtered for in-season, time-loss injuries defined as spring training, regular season, and postseason, there were 2890 injuries. Of these, 1928 were oblique injuries, 453 were intercostal injuries, and 115 were rectus injuries. The number of oblique injuries each season increased for all of baseball ( P < .001), as well as for MLB ( P = .009) and MiLB ( P = .012) individually. Of the 1928 oblique injuries, 498 (26%) oblique injuries occurred at the MLB level and 1430 (74%) occurred at the MiLB level. Batting and pitching-related injuries comprised 860 (45%) and 729 (38%) oblique injuries, with a total of 18,455 DM and 20,891 DM, respectively. This corresponded to a mean of 22 DM for batting injuries and 29 DM for pitching injuries (mean difference, 7.2; 95% CI, 5.27-9.13; P < .001). Conclusion: This decade-long study on professional baseball revealed a significant increase in abdominal oblique injuries across MLB and MiLB, with the largest number of injuries observed in the 2021 season. Meanwhile, there was a significant decrease in intercostal injuries across professional baseball during these years. Such injuries continue to pose challenges, leading to substantial DM per injury and affecting players from various positions.

BACKGROUND: The ability to predict recovery of left ventricular ejection fraction (LVEF) in response to guideline-directed therapy among patients with nonischemic cardiomyopathy is desired. We sought to determine whether left ventricular endocardial unipolar voltage measured during invasive electroanatomic mapping could be used to predict LVEF recovery among those with recent-onset nonischemic cardiomyopathy. METHODS: We analyzed the left ventricular voltage maps of patients included in the eMAP trial (Electrogram-Guided Myocardial Advanced Phenotyping; NCT03293381), a prospective, nonrandomized, interventional trial conducted at 2 institutions between 2017 and 2020. Patients had recent-onset nonischemic cardiomyopathy defined by LVEF ≤45% and development of symptoms or signs of heart failure within the past 6 months. Detailed voltage maps of the left ventricular endocardium were generated using the Carto electroanatomic mapping system. Abnormal unipolar amplitude was defined as <8.27 mV. The primary end point was recovery of LVEF (Recovery) defined by a 1-year LVEF ≥50% or ≥45% with ≥10% increase from baseline. RESULTS: Of the 29 enrolled patients (median age, 49 years [25th percentile, 39; 75th percentile, 59], 8 females [27.6%]), LVEF recovered in 13 (44.8%) by 1-year follow-up. The percentage of total endocardial surface area with unipolar voltage abnormality (AUA) was significantly lower among Recovery patients than No Recovery patients (18.2% [25th percentile, 6.4; 75th percentile, 22.4] versus 80.0% [25th percentile, 29.5; 75th percentile, 90.9]; P =0.004). Percent AUA was associated with lower likelihood of Recovery (odds ratio, 0.64 per 10% increase in AUA; 95% CI, 0.47–0.88; P =0.006). A 28% cutoff value for percent AUA was 92% sensitive and 75% specific with an area under the receiver operating characteristic curve of 0.81 (95% CI, 0.63–0.99; P =0.001) for predicting recovery versus no recovery. The majority of patients (12 of 13; 92.3%) with a percent AUA >28% did not recover. CONCLUSIONS: Left ventricular unipolar voltage abnormality is a potent predictor of LVEF recovery among patients recently diagnosed with nonischemic cardiomyopathy. Detailed left ventricular unipolar voltage mapping could therefore be used as a valuable prognostic tool in guiding treatment decisions.

Background: As machine learning becomes increasingly utilized in orthopaedic clinical research, the application of machine learning methodology to cohort data from the Multicenter ACL Revision Study (MARS) presents a valuable opportunity to translate data into patient-specific insights. Purpose: To apply novel machine learning methodology to MARS cohort data to determine a predictive model of revision anterior cruciate ligament reconstruction (rACLR) graft failure and features most predictive of failure. Study Design: Cohort study; Level of evidence, 3. Methods: The authors prospectively recruited patients undergoing rACLR from the MARS cohort and obtained preoperative radiographs, surgeon-reported intraoperative findings, and 2- and 6-year follow-up data on patient-reported outcomes, additional surgeries, and graft failure. Machine learning models including logistic regression (LR), XGBoost, gradient boosting (GB), random forest (RF), and a validated ensemble algorithm (AutoPrognosis) were built to predict graft failure by 6 years postoperatively. Validated performance metrics and feature importance measures were used to evaluate model performance. Results: The cohort included 960 patients who completed 6-year follow-up, with 5.7% (n = 55) experiencing graft failure. AutoPrognosis demonstrated the highest discriminative power (model area under the receiver operating characteristic curve: AutoPrognosis, 0.703; RF, 0.618; GB, 0.660; XGBoost, 0.680; LR, 0.592), with well-calibrated scores (model Brier score: AutoPrognosis, 0.053; RF, 0.054; GB, 0.057; XGBoost, 0.058; LR, 0.111). The most important features for AutoPrognosis model performance were prior compromised femoral and tibial tunnels (placement and size) and allograft graft type used in current rACLR. Conclusion: The present study demonstrated the ability of the novel AutoPrognosis machine learning model to best predict the risk of graft failure in patients undergoing rACLR at 6 years postoperatively with moderate predictive ability. Femoral and tibial tunnel size and position in prior ACLR and allograft use in current rACLR were all risk factors for rACLR failure in the context of the AutoPrognosis model. This study describes a unique model that can be externally validated with larger data sets and contribute toward the creation of a robust rACLR bedside risk calculator in future studies. Registration: NCT00625885 (ClinicalTrials.gov identifier).