Citations

ABSTRACT Patients with newly‐diagnosed acute myeloid leukemia (ND‐AML) derive variable survival benefit from venetoclax (Ven) plus hypomethylating agent (HMA) therapy, and the optimal Ven duration across genetic risk groups remains undefined. Among 540 ND‐AML patients receiving Ven‐HMA at Mayo Clinic, outcomes were compared across Ven 7‐ ( n = 33), 14‐ ( n = 117), 21‐ ( n = 96), and 28‐day ( n = 294) schedules during Cycle 1 and stratified by ELN 2024 and Mayo genetic risk groups. At a median follow‐up of 37.7 months, allogeneic stem cell transplant (ASCT) rates were similar across Ven duration groups (15%, 18%, 18%, and 20% for 7‐, 14‐, 21‐, and 28‐day; p = 0.86). Median transplant‐censored survival was comparable across Ven durations (13.3, 11.9, 16.8, and 13.2 months for 7, 14, 21, 28 days, respectively; p = 0.65), with outcomes driven by ELN risk (6.3, 11.5, 18.3 months for high, intermediate, low; p < 0.01) and Mayo genetic risk (6.9, 17.8 months, not reached; p < 0.01). Survival was comparable across Ven durations within ELN intermediate/low‐risk and all Mayo risk groups. Among ELN high‐risk patients, 14‐day Ven was associated with inferior transplant‐censored survival compared to 21‐ and 28‐day schedules ( p < 0.01). Notably, 30‐ and 60‐day mortality were higher with shorter Ven schedules (7‐day: 9%/18%; 14‐day: 7%/15%) versus 28‐day (2%/6%), which likely reflects treatment selection bias. In ND‐AML, no significant difference in transplant‐censored survival was observed across the 7‐, 14‐, 21‐, and 28‐day Ven schedules; prognosis was determined primarily by Mayo and ELN 2024 genetic risk rather than by Ven duration. Prospective trials are needed to establish risk‐adapted Ven dosing strategies.

Abstract Background Optimal treatment following first-line immunotherapy for advanced hepatocellular carcinoma (HCC) remains uncertain. This study evaluated futibatinib, a pan-FGFR inhibitor, combined with pembrolizumab in previously treated patients with FGF19-expressing HCC. Methods Eligible patients were ≥18 years old with advanced HCC, prior systemic therapy, Child-Pugh A-B7 liver function, ECOG 0–2, and FGF19 overexpression. Patients received futibatinib 20 mg orally daily plus pembrolizumab 200 mg intravenously every 3 weeks. The primary endpoint was progression-free survival at 6 months (PFS6). Secondary endpoints included overall survival (OS), objective response rate (ORR), quality of life, and safety. Results Between August 2021 and March 2024, 14 patients enrolled and 13 were evaluable. Median age was 72 years (range, 60–87), 53.8% were male, 92.3% had Child-Pugh A liver function, and all had received prior immunotherapy. Median progression-free survival was 15 weeks (95% CI, 9.0–NE), with a PFS6 rate of 23.1% (95% CI, 8.6–62.3%). ORR was 0% (95% CI, 0–24.7%), while stable disease was observed in 53.9% of patients. Median OS was 55.7 weeks (95% CI, 47.3–NE). Grade ≥3 adverse events occurred in 69.2% of patients, and grade ≥4 adverse events in 15.4%. One grade 5 event (acute-on-chronic kidney injury) was deemed unrelated to treatment. Common adverse events included hyperphosphatemia, fatigue, diarrhea, elevated transaminases, dry eye, nail changes, rash, and oral mucositis. Conclusions Futibatinib plus pembrolizumab demonstrated an acceptable safety profile but did not meet efficacy thresholds supporting further study in FGF19-expressing HCC. Effective post-immunotherapy treatment strategies remain an unmet need.

Adult optic nerve axon regeneration has traditionally been framed as a problem of limited intrinsic growth capacity in central nervous system neurons. However, growing evidence suggests that intrinsic factors alone cannot account for regenerative failure: restrictive extrinsic environmental factors largely govern optic nerve regeneration, dictating the intrinsic capacity axons can express. In this review, we frame the extrinsic optic nerve environment as a dynamic regenerative niche, in which vascular, immune, glial, matrix, and metabolic compartments are spatially co-localized and temporally coordinated rather than acting as independent barriers. These compartments follow a shared trajectory, broadly protective in the acute phase, then inhibitory once the underlying response fails to resolve, while also actively driving one another, such as reactive astrocytes promoting the matrix remodeling that subsequently restricts axon regrowth. Consequently, the niche’s overall permissiveness for regeneration reflects the aggregate and interdependent state of these compartments rather than the action of any single barrier. This review integrates current evidence on extrinsic barriers, intervention opportunities, and disease-specific variability relevant to RGC axon regeneration after injury. These interventions must incorporate the spatial, temporal, and metabolic factors that shape the goal of functional recovery and vision restoration.

Background: Several breast cancer (BC) risk prediction models have been developed to provide personal risk assessments. Though individually validated, their performance has not been systematically evaluated across a wide range of populations or ages. Methods: We harmonized individual-level baseline questionnaire data and incident BC diagnoses from 21 cohorts from North America, Europe, and Australia participating in the Breast Cancer Risk Prediction Project. Five-year absolute risk of invasive BC was estimated for five established risk prediction models using classical risk factors only. Discrimination was evaluated by area under the curve (AUC). Calibration was assessed using average and risk-decile specific expected to observed (E/O) ratios. Performance metrics were meta-analyzed across cohorts and models. Metaregression tested associations between cohort characteristics and performance metrics. Results: This analysis included 1,595,977 women aged 20-75 years, enrolled in studies between 1976-2015, with 19,062 (1.2%) invasive BC cases ascertained within 5 years from exposure assessment. Age-adjusted AUCs were similar across models and cohorts (pooled AUCs by model: 0.57-0.58), while E/O ratios varied substantially (pooled E/O ratios by model: 0.83-1.25). Overestimation was common among predicted high-risk individuals (>3%). No appreciable differences in model performance by cohort age, birth year, race, and variable missingness emerged. Calibration improved after assigning race-specific incidence rates. Conclusion: Existing BC risk prediction models provided similar risk discrimination across multiple cohorts, although there was overestimation of risk for high-risk individuals. Performance variation across cohorts was not driven by specific characteristics, which supports development of a unified risk model for diverse populations that leverages appropriate incidence rates.

Polycythemia vera is characterized by erythrocytosis and increased risk of thrombosis. Sapablursen is an antisense oligonucleotide that suppresses transmembrane serine protease 6 (TMPRSS6), increases hepcidin production, and reduces iron availability for erythropoiesis. IMPRSSION; an ongoing phase 2a, randomized, open-label study includes patients meeting 2016 WHO criteria for polycythemia vera, requiring ≥3 phlebotomies within 6 months of screening and ≥1 phlebotomy within the last 12 weeks. Cohort A (120 or 80 mg) and Cohort B (40 mg) received sapablursen subcutaneously once every 4 weeks (Q4W). The primary efficacy endpoint was the reduction in phlebotomy frequency from baseline to weeks 17-37 in patients who received ≥1 dose. Forty-nine patients received ≥1 sapablursen dose (median age 61 years; 82% male). The baseline mean±SD weekly phlebotomy rate was 0.15±0.07 in Cohort A; 0.17±0.07 in Cohort B and was reduced by -0.10 (95%CI, -0.13, -0.07; n=32;p&lt;0.0001) in Cohort A; -0.10 (95%CI, -0.14, -0.06; n=17;p=0.0001) in Cohort B. Sapablursen reduced the median (IQR) number of phlebotomies from 5.0 (3.0-6.0,Cohort A; 3.5-6.5,Cohort B) at baseline (26-weeks) to 0 (0-1.0) in the efficacy evaluation window (20-weeks) in Cohort A and 1.5 (0-2.5) in Cohort B. Most adverse events were mild or moderate; anemia and fatigue were most common. The mean change in MPN-SAF-TSS at week 37 was -6.21 points (95%CI: -10.56, -1.85, p=0.0052) in Cohort A; -2.71 points in Cohort B (95% CI: -8.33, 2.91, p=0.34). Sapablursen reduced phlebotomy need, improved symptoms, and was safe and well-tolerated in patients with polycythemia vera. (Funded by Ionis Pharmaceuticals; ClinicalTrials.gov: NCT05143957)

Lay Summary Glioblastoma is an aggressive brain cancer, and it can be difficult to tell whether changes seen on scans after radiation treatment represent tumor growth or treatment-related effects. The authors of this study wanted to evaluate whether a specialized imaging test called PSMA PET could help define tumor boundaries for radiation planning and distinguish tumor progression from treatment-related changes. To do this, they performed PSMA PET scans in 27 patients with high-grade gliomas, including patients undergoing radiation planning and patients being evaluated for possible tumor recurrence. They found that tumors showed higher PSMA PET signal than surrounding tissue, that PSMA PET sometimes identified tumor beyond what was visible on standard MRI, and that it correctly distinguished tumor progression from treatment-related changes in most patients.

ABSTRACT The recently published BLAST clinical risk model for chronic myelomonocytic leukemia (CMML) and its molecular version (BLAST‐Mol) differentiate low, intermediate, and high‐risk groups. The objective of the current retrospective study was to examine the survival impact of allogeneic stem cell transplant (ASCT) in a consecutive series of Mayo Clinic patients ( n = 775; 68% males, median age 71 years) with CMML, overall and adjusted for baseline BLAST/BLAST‐Mol risk categories. At a median follow‐up of 77 months, 151 (20%) patients underwent ASCT. Overall survival (OS) was longer in the ASCT compared to the non‐ASCT cohorts (median 77 vs. 28 months; p < 0.01). The significant difference in OS between the ASCT and non‐ASCT cohorts was retained after adjusting for BLAST clinical risk groups: high‐risk (median 50 vs. 14 months; p < 0.01), intermediate‐risk (81 vs. 28 months; p < 0.01), and low‐risk (111 vs. 65 months; p = 0.04), respectively. The same was mostly the case when OS comparison was adjusted for BLAST‐Mol with respective p values of < 0.01, < 0.01, and 0.08, respectively. Time‐dependent cox models confirmed the favorable survival impact of ASCT in the BLAST/BLAST‐Mol high‐ and intermediate‐risk groups. The current study highlights the benefit of ASCT for BLAST/BLAST‐Mol high‐ and intermediate‐risk groups in CMML and its potential to overcome the adverse impact of some high risk cytogenetic or molecular abnormalities. These observations support the early use of ASCT in CMML, ideally before BT and regardless of genetic characteristics.

ABSTRACT We examined the prognostic value of routine NGS data in newly diagnosed acute myeloid leukemia (AML) treated with intensive (7 + 3 backbone) induction, specified by AML subtype. A contemporary (2015–2025) series of 545 Mayo Clinic patients (median age 56 years, females 44%) was considered. Median follow‐up was 49 months with 341 (63%) allogeneic hematopoietic stem cell transplantations (AHSCT) recorded. AML subtypes included core‐binding factor (CBF; N = 72; 13%), primary non‐CBF ( N = 403; 74%), post‐myelodysplastic syndromes (MDS) or post‐myelodysplastic/myeloproliferative neoplasms (post‐MDS‐MDS/MPN; N = 28; 5%), post‐MPN ( N = 15; 3%), and therapy‐related (t‐AML; N = 27; 5%). Corresponding complete remission rates, with/without count recovery (CR/CRi), were 89%, 76%, 64%, 27%, and 78% ( p < 0.01) and 5‐year transplant‐censored survival rates 68%, 57%, 21%, 0%, and 55% ( p < 0.01). In multivariable analyses, the prognostic value of specific mutations was mostly limited to primary non‐CBF AML where adverse karyotype (OR 1.9; p = 0.04) predicted inferior and FLT3 ‐ITD (OR 0.4; p < 0.01) or NPM1 MUT / FLT3 WT (OR 0.1; p < 0.01) superior CR/CRi while KRAS MUT (HR 8.8; p < 0.01), TP53 MUT (HR 5.4; p < 0.01), and TET2 MUT (HR 2.3; p = 0.01) predicted inferior and NPM1 MUT / FLT3 WT (HR 0.3; p = 0.01) superior survival. Prognostication in intensively‐treated AML should start with subtype specification and recognition of the limited value of NGS in non‐primary AML. Post‐MPN AML is particularly associated with dismal outcomes and should be prognostically distinguished from post‐MDS‐MDS/MPN AML. In primary non‐CBF AML, in addition to previously established risk factors, the favorable impact of FLT3 ‐ITD on achieving CR/CRi and the unfavorable impact of KRAS MUT and TET2 MUT on transplant‐censored survival were noted and require confirmation from additional studies.

Abstract Background Diagnosis and risk stratification in rare hematologic malignancies such as myeloproliferative neoplasms (MPNs) – polycythemia vera (PV), essential thrombocythemia (ET), and myelofibrosis (MF) – require expert review of longitudinal, heterogeneous clinical records. This process is cognitively demanding, inconsistently applied, and difficult to scale beyond tertiary centers. No automated phenotyping workflow currently exists for hematologic malignancies. Methods A HIPAA-compliant large language model (LLM) framework for phenotyping MPN was developed to integrate (i) rule-based retrieval of bone marrow biopsy reports, clinical notes, and structured laboratory results from the electronic health record (EHR); (ii) zero-shot extraction of diagnostic and prognostic variables from unstructured text using GPT-4 Turbo; (iii) a clinician-informed source-prioritization algorithm to reconcile conflicting multi-source data; (iv) WHO/ICC-criteria–based diagnostic classification; and (v) NCCN-based risk stratification using the conventional risk model for PV, IPSET-thrombosis for ET, and DIPSS, DIPSS-plus, and MIPSS70/MIPSS70+ v2 for MF. Patients were identified via MPN-related ICD-9/10 codes; cases met 2017 WHO criteria or had a hematologist-documented diagnosis, and controls did not. The cohort was split into a prompt-development set (n = 60) and a held-out test set (n = 450; 75 cases and 75 controls per disease). Ground truth was established by independent dual-clinician chart review with consensus adjudication. LLM performance was evaluated against the ground truth: variable-level extraction using accuracy, F1 score, and Cohen’s kappa; patient-level diagnostic classification using sensitivity, specificity, and Cohen’s kappa; and prognostic risk stratification (among confirmed cases) using accuracy, weighted F1 score, and quadratic-weighted Cohen’s kappa. Wilson 95% confidence intervals (CIs) were used for proportions and bootstrap 95% CIs with 500 resamples for F1 scores. Results The held-out test set included 450 patients (PV: 150; ET: 150; MF: 150) with pathology reports and structured laboratory results, and 172 patients (PV: 52; ET: 55; MF: 65) with clinical notes. From pathology reports, overall variable extraction accuracy and F1 score were 99% (95% CI, 98–100) and 1.00 (0.99–1.00) for PV, 100% (99–100) and 0.99 (0.96–1.00) for ET, and 100% (99–100) and 0.99 (0.97–1.00) for MF. From clinical notes, overall accuracy and F1 score were 96% (91–100) and 0.94 (0.85–1.00) for PV, 100% (100–100) and 1.00 (1.00–1.00) for ET, and 100% (99–100) and 0.98 (0.95–1.00) for MF. Diagnostic sensitivity was 100% (95% CI, 95.1–100.0) for PV, ET, and MF; specificity was 98.7% (92.8–99.8) for PV and 100% (95.1–100.0) for both ET and MF, with Cohen’s kappa of 0.99 for PV and 1.00 for ET and MF. Risk stratification accuracy was 100% with weighted F1 score of 1.00 and quadratic-weighted Cohen’s kappa of 1.00 across all three diseases. A pre-specified source-ablation analysis showed that pathology reports alone were sufficient for diagnosis (sensitivity 98.7% for PV, 100% for ET, 96.0% for MF; specificity 100% across all three subtypes) but inadequate for prognostication (accuracy 69.3% for PV, 93.3% for ET, 77.3% for MF). Adding clinical notes to pathology reports recovered full prognostic accuracy of 100% across all three diseases. Conclusions This first-in-class automated framework achieved expert-level performance for MPN diagnosis and risk stratification from real-world EHR data, establishing a foundation for scalable, standardized phenotyping in rare hematologic malignancies. Prospective, multi-site validation is warranted before clinical deployment.