Citations

Abstract Introduction The 2022 WHO/ICC classifications of myeloid neoplasms (MNs) incorporated genomics into the existing clinicopathologic framework, defining new (mono)genetic entities. However, this iterative approach resulted in a mix of pathologically and genomically-defined entities, reliant on arbitrary thresholds and historically-derived boundaries between entities. We hypothesised that integrating genomics with other features, de novo from first principles, might better incorporate modern molecular knowledge to define the biological continuum, evolutionary links and overlapping features across MN. Methods The discovery cohort comprised 6484 thoroughly annotated pts. Contemporary diagnoses included 1817 AML, 1695 MDS, 737 MPN, and 1101 MDS/MPN. Non-malignant pts (AA/CHIP/CCUS/ICUS) were included to explore beyond current neoplastic boundaries. 1407 pts had ≥1 follow-up sample/s. Validation was performed in an independent international cohort (n=2012). An unsupervised random forest algorithm was used to integrate status (and VAF) for 28 mutations, karyotypes, CBC features, sex and age (total parameters 144). Features were selected for potential to be independent of BM sampling. Proximity-based multidimensional scaling/PCA were used to visualize latent structure and identify variance-driving features. Results The model projected pts onto a continuous 3-dimensional space. We first applied clustering seeking 1st-order structure, revealing 4 major clusters (C1–C4). These were further subdivided into 58 distinct subclusters (SCs) by an unsupervised iterative clustering approach. All SCs were enriched for distinctive features, with diverse associations linking genomics to clinicopathological/outcome features. Notably, contemporary diagnoses were distributed widely throughout this landscape, with 9/58 SCs containing cases spanning multiple WHO/ICC MN categories. C1 displayed the most internal heterogeneity, with admixed AML, MDS and MDS/MPN pts. It naturally subdivided down to 4th-order subclustering. Ten SCs were dominated by splicing factor mutations. For example, SF3B1MT segregated into 3 SCs, alone or with high-VAF TET2/ASXL1 or DNMT3A mutations. A separate TET2/SRSF2 SC associated with elevated monocyte%, reflecting a discrete CMML-phenotype genomic entity. NPM1MT formed a distinct SC with FLT3-ITD, distinguished further by VAFs of FLT3, TET2, and NRAS. Current genomically-defined AML subtypes separated in the 4th subclustering. C2 encompassed classical MPN driver mutations across 6 SCs, including a distinct CALRMT group and others defined by variable JAK2 VAFs, co-mutation patterns and other CBC features: eg high-VAF SF3B1MT correlated with PB blast%, and concurrent TET2MT with higher Hb/monocyte counts. C3 was characterized by TP53 alterations, with 5 SCs differing by TP53MT burden, 17p lesions, karyotypic complexity and age. Two SCs, one marked by high TP53 VAF+complex karyotype, the other by ch17 lesions, were associated with the worst OS in the whole cohort. C4 contained most known non-malignant pts, dividing into 4 SCs: 2 largely comprising CCUS and AA, while 2 reflect overlaps/convergence between AA and MDS and MPN, respectively. Repurposing single-cell pseudotime analysis suggested multiple disease origins, with various progression trajectories converging on C3. Projecting them onto the model longitudinal samples moved along these derived paths, consistent with their known progression/remission changes, validating the model's biological relevance and predictive utility. Remarkably, the 58 SCs displayed distinct risks of clonal progression and survival. To maximize potential clinical utility we created a pan-MN prognostic score integrating these features. It performed robustly (c-index 0.84), matching/exceeding existing prognostic tools and validated in an independent dataset. Conclusion Integrating clinicopathologic and genomic data we developed ab initio a continuum model of MNs that transcends historical diagnostic boundaries, captures disease evolution and stratifies clinical outcomes. It may better reflect the core biology and natural histories of specific cases, placing more rational boundaries between discrete entities. Potential advantages extend to treatment selection/trial design (in the era of molecularly-targeted therapies) and personalised prognostication throughout each disease course. Expanded validation is needed to resolve complexity in some areas (notably in C2/C4) and validate/refine this prototype framework.

Abstract Myeloid neoplasia encompasses a heterogeneous and complex molecular landscape whereby the distinct combinatorial patterns associated with clinical phenotypes are difficult to delineate. Given that genetic heterogeneity can be a consequence of the topology of the fitness landscape (peaked/non-peaked=high vs low fitness), we investigated co-mutational patterns in TP53 context as an example of hallmark genomic heterogeneity. Indeed, TP53 gene is characterized by hypomorphic/loss-of-function lesions, truncating mutations (frameshifts, stop codons), missense mutations often having a dominant-negative effect and loss of heterozygosity by chromosome 17p deletion driving clonal expansion. Clinical phenotypes of TP53 mutants are also heterogeneous. Here, we stratify TP53 mutations based on our previous published data1 whereby patients with single-hit TP53 and variant allelic frequency (VAF) >50% were classified as obligatory biallelic, patients with VAF between 23-50% as probable biallelic and <23% as probable monoallelic. A threshold of VAF 23% was optimal to separate monoallelic vs biallelic and was based on all-cause mortality. A tree-based model (RandomForestSRC) was used to build a survival model with VAF as a single covariate and minimum node size set to 15 to optimize the cut-off. Using this cut-off, we delineate the epistatic landscape and potential interactions among different TP53 mutational spectra and its fitness. We curated a cohort of 800 patients with TP53 mutations from our institution. In total 36% of the cases carried single hits while 64% had double hits genomic configuration. About 70% of the mutations were missense and were detected at canonical sites (R175H, Y220C, M237I, R273H, R282W, R248Q). We took into consideration 35 features and clustered our cohort of TP53 mutants using factor analysis. When we stratified the cohort based on our predetermined VAF threshold, we found that majority of the variants with high VAF, to be deemed as obligatory biallelic, co-occurred with complex karyotype. These cases were very homogeneous hence had on average a low number of additional variants, likely due to TP53 clones having reduced fitness in the presence of additional mutations. Conversely, patients without complex karyotype were mostly assigned to the monoallelic group due to low to median VAFs. Consequently, these samples had on average a higher number of additional hits, hence a heterogeneous molecular landscape. To substantiate this finding, we noticed that among monoallelic patients two characteristic pairs were observed (TP53-TET2 and TP53-SF3B1) and showed different patterns according to karyotypic associations. Indeed, both pairs in normal karyotype (TP53-TET2, 65%; TP53-SF3B1, 23%) had the highest number of additional mutations on average compared to other monoallelic hits in complex karyotype suggesting that clones resulting by these pairs were advantageous and produced higher fitness driving heterogeneity when together with other mutations. As a preliminary analysis to characterize the fitness landscape of canonical missense TP53 mutations, we investigated whether distinct TP53 mutations conferred differential clonal fitness by implementing a previously published model of stochastic hematopoietic stem cell growth based on the distribution of allelic frequencies across different age groups. Given a fixed stem cell population pool and a constant mutation rate, the distribution of allelic frequencies in the population of corresponding mutations across age can inform the fitness/selection coefficient. The model predicts that high fit mutations will expand more in the population (high VAF) depending on the time the mutation is allowed to expand (age). Based on the literature, we set the stem cell pool to 100,000 and the mutation rate to 1.4E-8.2We limited our analysis to mutations found in at least 10 individual in our cohort and to single hits due to potential epistatic interactions across multiple mutations in the same gene. Given this criterion two mutations R273H and R248Q were analyzed. Interestingly, we observed a 15% increase in fitness gain for R273H compared to R248Q. In summary, mutational heterogeneity and clonal fitness might provide clues to the diversity of TP53 mutational configurations. Our model will be further optimized for the upcoming ASH meeting by incorporating temporal sampling and increasing sample size to define differences in fitness according to mutation site.

Abstract Introduction: Axi-cel, an autologous anti-CD19 CAR T-cell therapy has shown high and durable response rates and a manageable safety profile among R/R FL pts in the ZUMA-5 trial (Jacobson et al. 2022; Neelapu et al. 2024). Evidence from real-world data showed favorable early outcomes in a broader population using CIBMTR data, with comparable outcomes by ZUMA-5 eligibility, age, lines of therapy (LOT), and prior bendamustine (benda) use (Jacobson et al. 2023). This study investigated long-term outcomes and the association between age, performance status, comorbidities, and therapies given prior to infusion among R/R FL pts treated with axi-cel. Methods: Pts with R/R FL who received commercial axi-cel between 03/2021–10/2023 in the US were identified from the CIBMTR® registry; pts without consent, with prior non-transplant cellular therapy, and FL grade 3B or 3A/3B unspecified or unknown were excluded. Descriptive analyses were done among all pts and by age at infusion (<65 vs ≥65 y), Karnofsky performance score (KPS), presence of hepatic, cardiovascular (CV), or moderate to severe pulmonary comorbidities, prior treatments (benda pre-leukapheresis, autologous hematopoietic stem cell transplant [autoHSCT]), and lymphodepletion (LD) therapy. Multivariable (MV) Cox and logistic regression were used to adjust for confounders. Results: In total, 238 pts from 68 centers were included (data cut-off October 2024). Median age at infusion was 61 yr (range, 29-83; ≥65 yr, 38%), and 79% were non-Hispanic White. KPS of pts was ≤70% (11%), 80% (35%), or 90-100% (54%); 2% had ECOG ≥2. Most (75%) had ≥1 clinically significant comorbidity (hepatic, 6%; CV, 15%; pulmonary, 18%). Median (min, max) prior LOT was 4 (1,13); 74% received benda pre-leukapheresis, and 6% had benda LD therapy. At a median follow-up of 24.1 months, objective response rate (ORR) was 96% (complete response [CR] rate, 91%). The 2-yr (95% CI) DOR, PFS, and OS were 70% (63-77), 64% (57-71), and 84% (78-89) respectively. Grade ≥3 cytokine release syndrome (CRS) and immune effector cell-associated neurotoxicity syndrome (ICANS) occurred in 4% and 18% of pts (any grade, 74% and 42%), respectively. Prolonged cytopenias by day 30 occurred in 14% of pts (neutropenia [10%] and thrombocytopenia [8%]) while 29% had clinically significant infections at 6 months. Second primary malignancies occurred in 16 pts (7%), with 7 (2%) being therapy-related myeloid neoplasm. The leading primary causes of death (n=34) were relapse/progression (10; 29%), organ failure (7; 21%), and infection 5 (15%). Cumulative incidence of non-relapse mortality at 2-yr was 9%. Outcomes were generally comparable among age, autoHSCT, and comorbidity subgroups. However, effectiveness outcomes differed by prior benda use (Yes vs No): ORR (95% vs 98%); CR (88% vs 98%); DOR (65% vs 89%), PFS (58% vs 84%), and OS (82% vs 91%) at 2 years. By LD therapy (single agent benda vs cyclophosphamide + fludarabine [Cy + Flu]): the ORR was 93% vs 96%; CR rate was 57% vs 93%. On MV analysis, prior benda use was associated with (OR/HR [95% CI]): worse CR (0.02 [<0.01-0.43]), DOR (3.69 [1.51-9.02], and PFS (2.21 [1.12-4.38]). Pts given benda LD therapy had (OR/HR [95% CI]): worse CR rate (0.02 [<0.01-0.16]), DOR (7.59 [2.33-24.72]), and PFS (4.89 [1.79-13.39]) compared to those who received Cy + Flu. CRS and ICANS were lower among those with prior benda use (Yes vs No): any-grade CRS (70% vs 87%); Grade ≥3 CRS (3% vs 8%); any-grade ICANS (36% vs 61%); and grade ≥3 ICANS (17% vs 25%). By LD therapy (single agent benda vs Cy + Flu): the Grade ≥3 CRS and ≥3 ICANS were 0% vs 5% and 7% vs 19% respectively. Any-grade ICANS was higher among those aged ≥ 65 yr vs <65 yr (53% vs 35%). On MV analysis, pts who had prior benda use were less likely to have any-grade CRS (0.30 [0.12-0.75]), and any-grade ICANS (0.23 [0.11-0.50]. Pts ≥ 65 yr had higher any-grade ICANS (2.31 [1.18 – 4.50]). Summary/Conclusion: This long-term follow up of axi-cel in R/R FL shows durable responses and manageable safety similar to ZUMA-5. Outcomes among the elderly and those with comorbidities were generally comparable to the overall R/R FL population. Although benda use pre-leukapheresis was associated with less durable responses, we were unable to determine whether this association is limited to use close to axi-cel infusion, as data on timing of use was unavailable. The associations for benda LD should be interpreted with caution given the small sample size.

Abstract Chronic idiopathic neutropenia (CIN) is characterized by a persistently reduced absolute neutrophil count, typically <1.5×10⁹/L for ≥3 months, without identifiable infectious, nutritional, autoimmune, clonal, congenital, or drug-related causes. It most commonly affects adult women, carries a variable risk of infection, and is frequently managed expectantly in the absence of severe or recurrent infections. An index case of CIN with irregular menses and normalization of counts during pregnancy prompted an institution-wide review of adult neutropenia. U[p front we excluded cases of known congenital and drug-induced neutropenia. Among 238 presumed CIN patients, 88 had large granular lymphocytic (LGL) leukemia–associated neutropenia, 63 had autoimmune neutropenia defined by the presence of anti-neutrophil antibodies, and 87 met criteria for idiopathic neutropenia. Within the presumptive CIN group, extended blood antigen screening identified 12 patients with a Duffy-null phenotype, who were excluded from further idiopathic analysis (final n=75). This included 10 African American, 1 Caucasian, and 1 Asian patient. Extended blood-group profiling (Kidd, Colton, Lutheran, Dombrock, LW, ABO) showed no significant deviation from population frequencies. In the remaining non-Duffy CIN patients, remarkably 54/75 were female with a mean age of 45±16 years. At presentation, mean WBC was 2.84±0.58×10⁹/L and ANC was 0.92±0.39×10⁹/L, Hgb was 13.5±1.2g/dL and platelets were 229±83×10⁹/L. Antinuclear antibodies were assessed in 73 patients, with 63 negative and 10 positive, predominantly speckled (66%) but rheumatologic consultation did not yield systemic autoimmune diagnoses. Hypothyroidism was noted in two CIN cases. Irregular menses were reported in 50% of female CIN patients with documented histories, and among those, 80% exhibited higher or normal neutrophil counts during gestation. Physiologically, pregnancy is a progesterone-high state associated with neutrophilia and physiologic leukocytosis; in addition, progesterone can dampen cytotoxic T-cell activity and inflammatory signaling while supporting marrow niche function. Furthermore, progesterone binds PR on marrow stromal cells and can upregulate CSF3 (G-CSF) and possibly other hematopoietic growth factors, thus regulating granulopoiesis. By contrast, anovulatory or irregular cycles often reflect luteal progesterone deficiency, which may predispose susceptible patients to lower ANC prompting us to formulate a theory that excess of CIN in females may be due to a progesterone-responsive CIN subtype. From our cohort, there were no patients on progesterone-supplement to evaluate if there would be responsiveness secondary to its utilization. To further support this theory we turned to metanalytic resources. TriNetX1allowed us search and identify women receiving exogenous progesterone versus a control receiving non-hormonal contraceptives and assign to them a corresponding ANC. When we compared ANC in 1:1 greedy propensity-score matching to control for covariates (demographics, BMI, and disease confounders e.g., malignancy). balance between comparator groups was confirmed by standardized mean differences <0.10. After matching (n=18,561 per arm), the exogenous progesterone group had a significantly higher neutrophil count compared to non-hormonal contraception (1.9±3.7 vs 1.5±1.7; t=3.5, p=.0004). The cohort age range was similar to our patient population 44 ±19. Our observations motivate prospective evaluation of progesterone-high states as potential modifiers of ANC in otherwise idiopathic cases and particularly refractory cases Cycle-synchronized CBC with paired progesterone and estradiol measurements, together with controlled progesterone augmentation trials, can quantify ANC changes and clinical outcomes in this subset. We thank TriNetX and all participants for their contribution, without whom this research would not have been possible. ReferencesRobertson SA, Mayrhofer G, Seamark RF. Ovarian steroid hormones regulate granulocyte-macrophage colony-stimulating factor synthesis by uterine epithelial cells in the mouse. Biol Reprod. 1996 Jan;54(1):183-96. doi: 10.1095/biolreprod54.1.183. PMID: 8838016.

Abstract Background People of color (POC) and patients (pts) from socioeconomically disadvantaged backgrounds often face financial, geographic, and systemic barriers, limiting access to advanced treatments (Tx). A survey was conducted to better understand how race and socioeconomic factors affect pt awareness of and access to bispecific antibodies (BsAbs) and chimeric antigen receptor T-cell (CAR-T) therapies in the US. Methods This study used 30-minute online surveys (March-June 2024) of 1301 pts with RRMM across 7 countries. Results were analyzed using descriptive statistics and χ2 tests, with P<.01 for all comparisons unless specified; these are presented for the 305 US pts. Results The 305 US pts identified as White (n=227) or POC (n=78), which included Black/African American (n=42); Hispanic/Latino (n=24); and Asian, Pacific Islander, or Arab (n=12). Pts self-reported as having easy/very easy (n=92), neutral (n=117), or difficult/very difficult (n=96) financial burden, being employed (n=142) or not employed (n=163), and having ≤secondary (n=72) or >secondary education (n=232). In the US, more POC reported difficult/very difficult financial circumstances than White pts (47% v 26%). Fewer POC stated they were in remission (28% v 49%) or had consulted an MM specialist (41% v 59%, P=.028), even after adjusting for self-reported good financial circumstances. Among pts with neutral-very easy financial situations, stated remission rates were still lower for POC (n=41) v White pts (n=168) (34% v 59%, P=.026), as were MM specialist visits (41% v 66%, P=.022). Pts with >secondary education (n=232) and those who were employed (n=142) had higher stated remission rates than those with ≤secondary education (n=72) and those who were not employed (n=163) (47% v 32%, P=.025 and 66% v 24%, respectively). Physical burden was experienced by more POC v White pts (91% v 66%), even after adjusting for financial circumstances (90% v 65%, P=.011, for POC v White pts in neutral/very easy financial circumstances). POC and pts with difficult financial circumstances (including POC and White pts) perceived their Tx as less effective than expected across several measures, including emotional and mental health, overall impact on daily life, side effects, Tx costs, and the effect of Tx schedule on everyday life. Awareness of BsAbs and CAR-T was lower among POC v White pts (BsAb: 49% v 77%; CAR-T: 67% v 81%, P=.032), pts who were not employed v employed (BsAb: 63% v 77%, P=.015; CAR-T: 74% v 81%, P=.046), pts with ≤secondary v >secondary education (CAR-T only: 75% v 78%, P=.021), and those in difficult/very difficult v easy/very easy financial circumstances (BsAb: 54% v 90%; CAR-T: 64% v 90%). Among pts aware of BsAbs, 18% (n=39) reported that the Tx was offered by their physician. More employed v not employed pts were offered BsAbs (26% v 10%). There were non-statistically significant differences in the proportion offered BsAbs based on race (POC 8% v White pts 21%, P=.065), financial status (difficult/very difficult 15% v easy/very easy 23%, P=.288), or level of education (≤secondary education 15% v >secondary education 20%, P=.428). Among pts aware of CAR-T, 24% (n=56) reported that the Tx was offered by their physician. Fewer POC than White pts were offered CAR-T (6% v 29%), even after adjusting for financial status (10% v 32%, P=.04 for pts with good finances). Among those aware of CAR-T, fewer pts not employed v employed (12% v 37%), pts with ≤secondary v >secondary education (11% v 27%, P=.015), and pts with financial burden (difficult/very difficult 10% v easy/very easy 31%) were offered CAR-T. Overall, fewer POC received CAR-T than White pts (1.3% v 10.7%, P=.03). Additionally, more employed v not employed pts received CAR-T (15.2% v 2.5%) or BsAbs (23.5% v 4.4%). Conclusions Consistent with existing health equity inequalities (Chen et al, Int J Equity Health, 2025), POC and pts in poorer socioeconomic circumstances had less awareness of and access to BsAbs and CAR-T. To address these disparities, partnering with trusted messengers and pt advocacy groups supporting Black, Hispanic, and Asian pts and those with socioeconomic hardships can enhance healthcare infrastructure, support initiatives to help pts navigate advanced Tx options, and develop pt- and physician-targeted education. These strategies can improve awareness and promote Tx equity, ultimately ensuring that all pts with MM receive optimal care regardless of their socioeconomic status and race.

Abstract Background: Germline predisposition states (GPS), including inherited bone marrow failure syndromes (IBMFS) are seen in 5-10% of individuals with myeloid neoplasms (MN). Given overlap with somatic driver genes, blood, saliva, and buccal swabs are suboptimal specimens for GPS testing in MN; the latter two due to contamination with blood cells(Jerez, 2024). Skin biopsy with fibroblast culture-derived DNA remains the gold standard, but the process is expensive, takes 6-8 weeks to complete, and fibroblast culture failure can occur in some patients with telomere biology disorders. Given the need to rapidly screen donors for HSCT and adjust therapy/conditioning in certain IBMFS, we developed a rapid hematologic germline testing algorithm using hair follicle-derived DNA. Methods The study was conducted after IRB approval through the Mayo Clinic GPS/IBMFS clinic. To perform PCR-based hair follicle testing, we obtained 15-25 hair follicles (bulbs) per patient. The bulbs were placed in a microcentrifuge tube and subjected to a 24-hour digestion and extraction protocol using a modified version of the QIAGEN DNA Purification from Dried Blood Spots protocol. DNA quality was assessed by Nanodrop and Qubit.Testing included either validation of known or suspected germline variants (e.g., RUNX1, DDX41, ETV6), or panel testing (e.g., GPS or IBMFS). Pathogenic variants were validated by repeat testing in a CAP/CLIA certified lab prior to medical decision making. 23 patients underwent whole exome sequencing (WES) in a CAP/CLIA lab, and 13 patients had concurrent germline testing using alternate DNA sources (8 skin biopsies, 1 saliva, 4 buccal swabs). Results Ninety-three patients (49 male, 53%) underwent hair follicle-derived germline DNA testing (median age 63 years). Indications for germline testing included the presence of a suspected variant on somatic testing with variant allele frequency (VAF) between 35%-60% ( n= 66, 71%), patient age <50 years (n=26, 28%), antecedent thrombocytopenia (n=15, 16%), presence of syndromic features (n=4, 4%), patient history of multiple malignancies (n=4, 4%), and positive family history (n=15, 16%). Time to reporting variants after receipt of hair follicle-derived DNA was <14 days. There were zero complications associated with the procedure. DNA quality as assessed by Nanodrop revealed a median nucleic acid concentration of 25.64 ng/μL. The median A260/A280 ratio was 1.86 (range 0.701-2.133) and the median A260/A230 ratio was 1.27 (range -8.193-9.223). DNA quality was insufficient for chromosomal microarray (CMA) assessments. Of 93 patients evaluated, 67 (72%) had ≥1 germline variant, with 3 having >1 germline variant for a total of 72 variants. Pathogenic/likely pathogenic variants identified included: DDX41 (30, 41.7%), TP53 (4, 5.6%), ANKRD26 (4, 5.6%), RUNX1 (4, 5.6%), GATA2 (3, 4.2%), TERT (3, 4.2%), JAK3 (2, 2.8%), SAMD9/SAMD9L (2, 2.8%), ATM (2, 2.8%), and 1 each (1.4%) in BCL2, BCOR, BPGM, CDKN2A, CEBPA, CHEK2, CSF3R, CXCR4, DNMT3A, ETV6, GATA1, MPL, MPO, POT1, PTPN11, RPL5, and SH2B3. In the 13 patients that had concurrent germline testing, results were identical in all cases, except for 1 false negative in a buccal specimen (PTPN11) and 1 case of germline mosaicism, where the TP53 variant was identified in the blood and hair follicle DNA but not in skin fibroblast DNA. After testing, 30 (44.7%) patients had a change in their management plan: 8 (27%) with DDX41-GPS were observed due to known latency of DDX41-mutant MN, 6 (20%) were referred for HSCT based on the germline variant (CEBPA, DDX41, GATA1, GATA2, RPL5, TP53), 6 (20%) were placed on an enhanced surveillance plan for cancer screening (1 ANKRD26, 3 TERT, 2 TP53), 4 (13%) patients undergoing HSCT had related donors removed from consideration as they were carriers (2 DDX41, 1 ANKRD26, and 1 SAMD9), 2 (7%) patients with neutropenia and underlying germline variants (1 ATM, 1 DDX41) had G-CSF therapy discontinued due to concerns for clonal stimulation, and 1 (3%) patient with a germline CDKN2A mutation (hematological diagnosis- CMML) was recommended to avoid radiation therapy for prostate cancer. Conclusion In summary, we validate a rapid and simple hair follicle-derived DNA based germline assessment for patients with hematological disorders and demonstrate a positive impact on clinical care in 44% of patients. We are currently optimizing DNA quality so that germline copy number alterations can be better detected using CMA.

Abstract Introduction: Only 30% of patients (pts) presenting with abnormal bleeding symptoms receive a clear diagnosis, with many classified as having bleeding disorder of unknown cause, or BDUC (Baker et al. 2021). Currently, the recommended diagnostic workup for BDUC by the International Society on Thrombosis and Haemostasis (ISTH) includes plasmatic assays for coagulation factors, von Willebrand factor (vWF) antigen/activity, and platelet function testing (PFT), specifically platelet function analyzer-100 (PFA-100) and light transmission aggregometry (LTA). However, PFTs are not widely available and cannot be mailed to reference laboratories. We studied the diagnostic yield of an expanded testing panel which includes quantitative platelet glycoprotein flow cytometry (GpFL) and platelet electron microscopy (PTEM), which we have optimized for specimen mailing. Methods: We conducted a minimal risk, retrospective study by reviewing the electronic health records of pts (18 years and older) who were seen in the Coagulation Clinic of a tertiary academic medical center for evaluation of a bleeding disorder between October 2017 and June 2025. Testing included plasma-based assays including PT, APTT, vWF assay, FVIII, FIX, FXIII screen, and thrombin time (and additional reflex assays as needed). At the discretion of the treating clinician, PFTs (PFA-100 and LTA), GpFL, PTEM, and fibrinolysis assays (plasminogen activator inhibitor-1 antigen [PAI-1 Ag] and alpha-2 plasmin inhibitor) were included. We abstracted clinical data on pt demographics, ISTH bleeding scores, and the results of coagulation testing. Pts with an established diagnosis of a bleeding disorder, underlying malignancy, and those who did not have plasma-based coagulation testing were excluded from this study. Results: 109 pts met study criteria, and 82.6% were females (n = 90) with a median age of 45 years (range = 18-88 years). The median ISTH-BAT score was 7 (range: 2-21). About half of the pts, 49.5% (n = 54), had normal coagulation profiles and PFTs. All 54 had PTEM performed, of which 14.8% (n = 8) were abnormal (alpha and/or dense granule deficiencies). 85.2% (n = 46) had GpFL testing performed, with one showing reduced Gp2b/CD42 and Gp3a/CD61 expression, four showing reduced Gp1a/CD49b expression, and three showing reduced GpVI expression. Half of the pts, 50.5% (n = 55) had an abnormal coagulation profile from plasma and/or PFTs, of which 20% (n = 11) had a clinically significant coagulation factor deficiency (FV, FVII, FX). Roughly 9.1% (n = 5) had type 1 vWD of which 1 also had PAI-1 deficiency. One pt had isolated PAI-1 deficiency. Abnormal coagulation profiles were noted in 53 pts who had PFA-100 and LTA done, and both tests were normal in 22.6% (n = 12). Within the abnormal coagulation profile group, 10.9% (n = 6) had ultrastructural abnormalities on PTEM (dense and alpha granule abnormalities). Majority of the pts (n = 46) had GpFL done, and one had abnormal reductions in Gp1b-aCD42b, three in Gp1aCD49b, and seven in GPVI. Comparison of the ISTH BAT score between the normal and abnormal coagulation profiles/PFTs groups by non-parametric (Mann-Whitney U test) and parametric (Welch's t-test) showed no significant difference (p = 0.56 and p = 0.87) respectively. Conclusion: In this cohort of pts with abnormal bleeding, standard recommended testing resulted in a diagnosis in 66.4% pts. The remainder would have been classified as BDUC. The addition of GpFL and PTEM resulted in establishing a diagnosis that explains the bleeding phenotype in 14.8% of pts with an otherwise normal coagulation profile and PFT. Although abnormal PFTs indicate a platelet function defect, GpFL and PTEM may further define the abnormalities particularly differentiating syndromic from non-syndromic inherited platelet disorders. Additional studies are needed to confirm our findings and explore the possibility of addition of GpFL and PTEM for patients with BDUC.

Abstract Background Accurate reconstruction of electronic health record (EHR) treatment sequences is essential for leveraging real-world data (RWD) in clinical research and trial-eligibility platforms in multiple myeloma (MM). However, inconsistencies in RWD treatment documentation and the complexity of line-of-treatment (LOT) assignments in MM hinder reproducibility and limit comparisons against published trials. To address these limitations, we developed HEAL-MM, an automated rule-based algorithm that systematically parses structured medication data to calculate LOTs and segment treatment into standardized, clinically meaningful phases. The algorithm is designed to be interpretable, adaptable to evolving therapeutic frameworks, and compatible with widely adopted EHR data standards. Here, we report its real-world validation against expert-adjudicated treatment sequences to assess concordance, identify edge-case failure points, and support RWD integration. Methods A stratified cohort of 100 MM patients (9,136 structured treatment events) was curated from 114 unique healthcare systems compiled from the multi-institutional HealthTree Foundation harmonized registry. Cohort selection was randomized to ensure coverage across diagnostic eras (pre-2010, 2015–2020, 2022–2025) and treatment exposures, including CAR T-cell therapies, bispecific antibodies, and anti-CD38-based regimens. HEAL-MM sequenced MM regimens chronologically and applied predefined logic rules to identify LOT transitions, the initiation of a new therapeutic course based on drug changes, treatment gaps, and procedural anchors such as stem cell transplant or CAR T. Within each LOT, the algorithm segments and labels therapy into phases, clinically distinct intervals (e.g., induction and maintenance) using rule-based clinical logic. Outputs were benchmarked against expert-labeled adjudications. Concordance was evaluated using concordance index (C-index), stratified by patient, LOT depth and diagnostic era. Results: HEAL-MM demonstrated high concordance with expert-labeled treatment sequences: 0.94 for LOT identification, 0.98 for treatment phase segmentation, and 0.96 for phase label assignment. Achieving complete agreement with all expert annotations in 90% of patients for LOT assignment, 94% for the number of treatment phases identified, 77% for the specific labels applied to each phase, and 75% across all three dimensions simultaneously. Among discordant patients, the absolute difference in final LOT count was 0.5 ± 0.9. Performance was highest in early lines (LOTs 1–3; C-index: 0.97), with seven patients showing discrepancies at this stage. Concordance declined in later lines (LOT ≥4; C-index: 0.87), where 50% of the discordant cases (n=4) were attributable to misclassifications in earlier LOTs, such as medication restarts following >3-month gaps, demonstrating the compounding effect of early errors on longitudinal accuracy. Temporal stratification revealed improved accuracy in post-2020 cases (C-index: 0.94) compared to 2015–2020 cohorts (0.91), reflecting the increasing adoption of structured treatment standards and EHR data quality improvements. To assess HEAL-MM performance at clinically significant junctures, we analyzed treatment transitions that initiated a new LOT or marked a change in phase, achieving C-indices of 0.97 for LOT transitions, 0.97 for treatment phase shifts, and 0.94 for phase label assignment. Conclusions: HEAL-MM provides a validated, scalable solution for standardizing MM treatment structures in RWD environments, as it accurately detects the exact treatment entry of a new LOT 97% of the time. This rule-based framework enables reproducible LOT and phase assignment across heterogeneous EHR systems, supporting real-time cohort identification across institutions and EHR platforms. The algorithm's modular design allows for continuous integration of novel therapeutic categories and evolving treatment logic. While the algorithm maintained high fidelity overall, early-stage misclassifications consistent with increased heterogeneity and documentation ambiguity occasionally propagated downstream, underscoring the compounding effect of upstream errors in longitudinal reconstruction. With its generalizable structure and compatibility with industry-standard data models, HEAL-MM lays the foundation for structured treatment reconstruction in MM across RWD infrastructure and serves as a transferable blueprint for other hematologic malignancies.

Abstract Introduction: Iptacopan, the first oral complement inhibitor, offers an attractive alternative to parenteral complement blockers in paroxysmal nocturnal hemoglobinuria (PNH). While clinical trials have confirmed its efficacy vs terminal C5 inhibition, real-world data on breakthrough hemolysis (BTH), complement-activating conditions (CACs), and switching patients with satisfactory response to prior therapy (hemoglobin [Hgb] ≥10 g/dL) are limited. We studied a large multi-institutional PNH cohort treated with iptacopan. Methods: We performed a retrospective analysis of 62 patients with PNH who received iptacopan for ≥3 months between FDA approval in December 2023 and April 2025 (mean exposure, 1.01 years; 62 patient-years). Patients from the Cleveland Clinic network and Mayo Clinic were analyzed. Demographics, prior therapies, reasons for transition, Hgb, lactate dehydrogenase (LDH), platelet counts, thrombotic events, CACs, BTH, and adverse events were extracted. Efficacy was assessed separately for treatment-naive patients and treatment-experienced patients (sub-optimal responders [Hgb <10 g/dL] and optimal responders to prior therapy). Results: Overall, 12 of 62 patients were treatment naive and 50 switched from prior therapy (of whom 21 had sub-optimal responses and 29 had optimal responses). In the 50 patients who switched, 60% transitioned from ravulizumab, 30% from pegcetacoplan, 8% from eculizumab, and 2% from ravulizumab and danicopan. The primary reasons for switching were the convenience of oral medications (n=17), extravascular hemolysis or BTH (n=10), prior medication side effects (n=5), desire to further improve Hgb (n=6), and not documented (n=12). A total of 4 patients discontinued iptacopan (2 pregnancies, 1 insurance reversal, 1 intolerable gastrointestinal toxicity). Three patients reported headaches, and 1 reported abdominal pain; all resolved within 1 week from treatment start. Across the 62 patient-years, no thrombotic events occurred, 18 CAC episodes were managed with iptacopan 200 mg BID (10 infections, 1 heart-failure exacerbation, 2 minor surgeries, 1 traumatic brain injury, 2 pancreatitis, 2 pregnancies), and none triggered BTH. Overall, 3 clinically significant BTH events (in 3 patients; 4.8% annualized) were recorded: 2 infection-related (managed outpatient) and 1 alcoholic pancreatitis; all resolved with a 1- to 2-day increase to iptacopan 400 mg BID ± single-dose eculizumab. Two hemolytic events secondary to non-adherence were reported (4 days after stopping iptacopan). These resolved after resuming iptacopan 200 mg BID without need for hospitalization. In treatment-naive patients, mean Hgb increased significantly by 1.87 g/dL from iptacopan initiation (baseline) to 3 months (9.9±1.9 to 11.8±1.3 g/dL; P=.005), sustained until last follow-up at 12 months. LDH decreased by 369 U/L at 3 months (P=.058), sustained through 12 months. No significant change was seen in platelets, absolute neutrophil count (ANC), or white blood cell (WBC) count. In treatment-experienced sub-optimal responders, mean Hgb increased significantly by 2.16 g/dL from baseline to 3 months (8.6±.89 to 10.8±2.1; P<0.001). At 12 months, 85% of patients had increased Hgb compared with baseline (median increase: 3.31±1.62 g/dL). LDH decreased significantly from baseline to 3 months by 229 U/L (P=.03), with no significant changes noted in LDH from 3 to 12 months or in platelets, ANC, or WBC counts. In previously treated complement inhibitor responders, mean Hgb increased significantly by 0.75 g/dL from baseline to 3 months (12.0±1.3 to 12.8±1.7 g/dL; P=.004), with 79% showing improvements from baseline at 12-month follow-up (median increase: 1.16±0.82 g/dL). LDH decreased significantly by 45 U/L from baseline to 3 months (P=.03), with no further significant changes from 3 to 12 months. Conclusions: In this real-world cohort, iptacopan provided substantial and durable hemoglobin improvement across naive and previously treated patients with PNH, with meaningful reduction in hemolytic parameters, absence of thrombosis, and low BTH rate predominantly linked to infection. Patients with previous satisfactory responses also showed improved Hgb levels. The favorable safety profile and high treatment persistence underscore iptacopan's role as an effective first-line or switch therapy and support its incorporation into evidence-based sequencing algorithms in the evolving PNH treatment landscape.

Abstract Introduction: The therapeutic landscape for paroxysmal nocturnal hemoglobinuria (PNH) has rapidly evolved with multiple proximal complement inhibitors now available, including pegcetacoplan (C3 inhibitor) and iptacopan (oral factor B inhibitor). While clinical trials have established individual drug efficacy compared with terminal complement inhibitors, real-world evidence regarding therapeutic transitions between proximal complement inhibitors remains extremely limited. As patients and clinicians increasingly seek to optimize treatment through sequential therapy approaches, understanding the outcomes of transitioning from pegcetacoplan to iptacopan becomes critical for evidence-based treatment sequencing in this rare hematologic disorder. Methods: We conducted a retrospective multicenter analysis across 3 academic medical centers (Cleveland Clinic, Mayo Clinic, Levine Cancer Institute) that evaluated 15 consecutive patients with PNH who were considered for transition from pegcetacoplan to iptacopan. Patients had confirmed PNH by flow cytometry and ≥3 months pegcetacoplan exposure. After switching to iptacopan, we assessed treatment acceptance rates, demographic characteristics, clinical outcomes including hemoglobin and lactate dehydrogenase (LDH) levels, and safety parameters. Responses to iptacopan were classified as optimal (hemoglobin >10.5 g/dL with clinical improvement) or suboptimal. Statistical analysis used paired t tests for continuous variables. Results: Of the 15 patients evaluated (median age [range]: 53 [22-81] years; 73% female), 14 patients (93.3%) elected to transition to iptacopan, demonstrating high treatment acceptance. Disease subtypes included classic PNH (36%) and PNH (64%) in the setting of another bone marrow disorder (n=7), multiple myeloma (n=1), and myelofibrosis (n=1). Median (range) duration of pegcetacoplan treatment pre-switch was 3 months (2-7 months), and median (range) duration of iptacopan treatment was 24 months (6-36 months). Among patients who transitioned, 79% (11/14) achieved hemoglobin improvement, with a mean increase from 9.2±1.8 to 10.8±2.1 g/dL (P=.028). Overall, optimal response was achieved in 64% (9/14) of patients. Response rates varied significantly by disease subtype: 80% in patients with classic PNH vs 56% in patients with PNH and aplastic anemia, with particularly poor outcomes in patients with concurrent hematologic malignancies (0%). LDH levels improved in 86% of patients, decreasing from 400±152 to 310±95 U/L (P=.015). PNH clone sizes remained stable throughout transition (erythrocyte: 75.1%±9.2% vs 75.4%±9.4%, P=.62; granulocyte: 95.0%±3.9% versus 95.2%±4.0%, P=.45). Treatment was well tolerated with no serious adverse events, breakthrough hemolysis, thrombosis, or discontinuations required. Two patients experienced mild self-limited gastrointestinal symptoms. Conclusions: This first multicenter real-world analysis demonstrates that the pegcetacoplan-to-iptacopan transition provides clinical benefit in the majority of this initial set of patients with PNH, with significant improvements in hemoglobin and an excellent safety profile while maintaining clone stability. The high acceptance rate suggests that patients prefer oral therapy over subcutaneous administration. These findings address a critical knowledge gap in proximal complement inhibitor sequencing, suggesting that iptacopan is an effective therapeutic option for patients with inadequate pegcetacoplan response and supporting the development of evidence-based treatment algorithms for optimal PNH care in the era of multiple complement inhibitor options.