HemaSphere最新文献

Central nervous system multiple myeloma (CNS-MM) is a rare and aggressive extramedullary manifestation of multiple myeloma, associated with poor prognosis and significant treatment challenges. Due to its rarity, data on incidence, risk factors, optimal therapeutic approaches, and long-term outcomes remain limited. This review aims to elucidate the current diagnostic and therapeutic challenges of CNS-MM and provide practical insights into real-life management strategies.

Given the evolving understanding of genetic risk factors in multiple myeloma (MM), this paper assesses whether next-generation sequencing (NGS) could complement or even replace fluorescence in situ hybridization (FISH) at diagnosis. A structured consensus process within European Myeloma Network (EMN) clinical and laboratory groups was conducted to establish recommendations on routine clinical deployment of NGS in MM risk assessment. Four key questions were addressed: (1) should NGS be used in addition to, or alternatively to FISH in identifying prognostic genetic markers, (2) which prognostic markers are most relevant for analysis by NGS, (3) which patients should be offered NGS testing, and (4) what is the optimal timing for performing NGS. The panel reviewed current literature, evaluated available NGS technologies, and compared their performance with that of FISH-based methodologies. The paper reviews current standard NGS protocols, quality control measures, and provides practical points for the implementation of an NGS diagnosis in MM. While NGS shows promise in improving risk stratification, challenges such as cost, accessibility, and clinical workflow integration must be addressed. The consensus supports the initial incorporation of NGS as a complementary tool to FISH. Recommendations emphasize that: a broader list of genetic events should be incorporated into such a test than what currently requested by risk scores; the test should be offered at least to the fit patients who could be candidates for modern triplet or quadruplet treatments; the test should be repeated at the time relapse, especially in the future when targeted treatments may mandate the use of predictive markers of response. This consensus provides a foundation for future research and policy development, guiding the adoption of NGS in MM risk assessment.

Koschmieder S. Novel approaches in myelofibrosis. HemaSphere. 2024;8(12):e70056. doi:10.1002/hem3.70056

A funder was not acknowledged in the original article. The following statement has now been added in the Funding section: “Open Access funding enabled and organized by Projekt DEAL.”

The original article has been updated. We apologize for this error.

Traditional risk stratification in multiple myeloma (MM) relies on clinical and cytogenetic parameters but has limited predictive accuracy. Machine learning (ML) offers a novel approach by leveraging large datasets and complex variable interactions. This study aimed to develop and validate novel ML-driven prognostic scores for newly diagnosed MM (NDMM), with the goal of improving upon existing ones. To this end, we analyzed data from the EMN–HARMONY MM cohort, comprising 14,345 patients, including 10,843 NDMM patients enrolled across 16 clinical trials. Three ML models were developed: (1) a comprehensive model incorporating 20 variables, (2) a reduced model including six key variables (age, hemoglobin, β2-microglobulin, albumin, 1q gain, and 17p deletion), and (3) a cytogenetics-free model. All models were internally validated using out-of-bag cross-validation and externally validated with data from the Myeloma XI trial. Model performance was evaluated using the concordance index (C-index) and time-dependent area under the receiver operating characteristic curve (ROC-AUC). The comprehensive model achieved C-index values of 0.666 (training) and 0.667 (test) for overall survival (OS) and 0.620/0.627 for progression-free survival (PFS). The reduced model maintained accuracy (OS: 0.658/0.657; PFS: 0.608/0.614). The cytogenetics-free model showed C-index values of 0.636/0.643 for OS and 0.600/0.610 for PFS. Incorporating treatment type and best response to first-line treatment further improved performance. The new prognostic models improved over the International Staging System (ISS), Revised International Staging System (R-ISS), and Second Revision of the International Staging System (R2-ISS) and were reproducible in real-world and relapsed/refractory MM, including daratumumab-treated patients. This ML-based risk stratification strategy provides individualized risk predictions, surpassing traditional group-based methods and demonstrating broad applicability across patient subgroups. An online calculator is available at https://taxonomy.harmony-platform.eu/riskcalculator/.

Kazianka L, Pichler A, Agreiter C, et al. Comparing functional and genomic-based precision medicine in blood cancer patients. HemaSphere. 2025;9(4):e70129. doi:10.1002/hem3.70129

A funder was not acknowledged in the original article. The following statement has now been added in the Funding section: “Open Access funding provided by Medizinische Universitat Wien/KEMÖ.”

The original article has been updated. We apologize for this error.

Follicular lymphoma (FL) is the second most common non-Hodgkin lymphoma (NHL) in Western countries, accounting for about 10%–20% of all newly diagnosed NHLs and 70% of all indolent lymphomas.^{1, 2}

The clinical course of FL is typically indolent and is characterized by a waxing and waning course. Most patients eventually need treatment, and responses to initial chemo-immunotherapy (CIT) are usually impressive. Nevertheless, relapses occur, requiring additional therapeutic interventions that result in shorter remission duration and an increased risk of drug resistance.³ At present, progression-free survival (PFS) after CIT in advanced stage FL ranges from 73% to 86% at 3 years,^{4, 5} and overall survival (OS) at 5 years varies between 68% and 90%, depending on the patient's age group.^{6, 7}

Disease progression or relapse within 2 years from first-line CIT (POD24_1) identifies a group of FL patients with significantly inferior outcomes (12% event-free survival at 5 years)^{6, 8} and hence with an unmet medical need. Current knowledge is insufficient to identify patients with high-risk disease upfront, nor can it guide initial treatment decisions. Second-line treatments employed in patients with relapsed/refractory (R/R) FL, which differ greatly from country to country and even within single institutions, are guided by initial therapy, patient's age and fitness, and disease characteristics.^9-12

For the design of more uniform treatment guidelines, it is important to better understand which specific combinations of first- and second-line treatments result in the most favorable outcome in specific FL patient populations.

Thanks to the extraordinary commitment of Dr. Steve Ansell, the Coach of the Cantera—2018 edition, and his fantastic training ability, it took just a few days for 20 individuals (the Cantera Players) to become one single, compact group: the Lupiae team (Figure 1).

The magic blend of these young brains soon produced the Lupiae study, an observational study whose aim was to define the disease course of R/R FL after first-line CIT, report current real-life approaches in various countries, and provide a rationale for the identification of novel treatment strategies. The Cantera Headquarter and EHA LyG enthusiastically supported this project, and in March 2019, the LUPIAE registry (NCT04587388) opened enrollment.

Patients with a histologically confirmed initial diagnosis of Grades 1–3a FL who were refractory to first-line CIT or who had relapsed or transformed to aggressive lymphoma were eligible and registered at the time of the first event (documented by biopsy, imaging, or clinical evaluation). Events were defined as (1) FL progression during induction or maintenance therapy; (2) FL relapse or progression after the achievement of at least partial remission (PR); and

We read with great interest the study by Veenstra et al.¹ validating the 17 immunophenotypic core marker panel (ELN Scoring System), defined by the ELN-iMDS-Flow Working Group (ELN-iMDS).² It includes aberrancies in myeloid progenitor cells (MPCs), neutrophils, monocytes, and nucleated erythroid cells. The presence of at least three aberrancies was indicative of either myelodysplastic neoplasm (MDS) or chronic myelomonocytic leukemia (CMML). Veenstra et al. could diagnose MDS with a sensitivity of 90% compared to an integrated diagnostic approach, which was also maintained within low-risk MDS (<5% bone marrow blasts) at 87%. This is comparable to the established comprehensive Integrated Flow Score (iFS)³ (all MDS: 91%) and represents a significant improvement compared to the 4-parameter Ogata-score⁴ (all MDS: 66%). In pathological controls (i.e., non-clonal cytopenias), concordance of ELN Scoring System was achieved in 76% (41/54) of patients. Some aberrancies were restricted to MDS patients but absent in pathological controls (aberrant expression of CD5, CD7, or CD56 on MPC and abnormal expression of CD33 on neutrophils). Exclusion of four markers predominantly associated with CMML (low side scatter and aberrant CD33 expression on neutrophils, aberrant percentage and CD13 expression of monocytes) (Kern et al.²) increased specificity to 96%.

We aimed to confirm the applicability and therefore the significance of the ELN Scoring System in routine diagnostics. To do this, we analyzed a large, independent cohort of MDS (359 patients) and pathological controls (41 patients with non-clonal cytopenias, for details see legend of Figure 1). In addition to the study by Veenstra et al., samples of 38 CMML patients and 32 healthy bone marrow (HBM, hip surgery patients) were included. The antibody panel, staining, acquisition, and data analysis have been previously delineated.⁵

Applying the ELN Scoring System to our MDS cohort, the diagnosis was confirmed in 89% of all MDS cases (Figure 1A). High sensitivity was also maintained in the low-risk MDS group (<5% blasts: 84%; low-to-moderate low IPSS-M: 86%). These results were in line with those reported by Veenstra et al. Regarding false negative cases (38/359), 42% of these would have been assigned to MDS by alternative scoring systems (Ogata-score: 8%, iFS: 21%, both simultaneously: 13%). Almost all CMML samples (97%) had an ELN Score compatible with MDS/CMML, in line with the ELN-iMDS study by Kern et al.² We also confirmed the four parameters described above as significantly associated with CMML.

As determined in pathological controls, the specificity of the ELN Scoring System was notably higher in our cohort than in the Veenstra and Kern studies (98%, 75%, and 78%, respectively). However, this high sp