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Abstract Introduction TP53MT are associated with poor outcomes in MDS, especially in the context of biallelic MT. We have previously reported on outcomes of pts with HR-MDS with TP53MT who received HMA in the VALIDATE dataset (Kewan T et al, ASH 2023). Here we provide expanded analyses focusing on outcomes post allo-HCT, and we explore the prognostic significance of different classification methods for biallelic TP53MT. Methods The VALIDATE database includes 4,732 pts with MDS who received HMA-based frontline therapy from 32 international centers in 9 countries. For this study, only pts with HR-MDS with molecular data at time of diagnosis were included. Biallelic TP53MT status was assessed using three classification schemes: WHO 2022, ICC 2022, and a VAF-based Cleveland Clinic Foundation (CCF) method.1TP53 copy neutral loss of heterozygosity (CN-LOH) was evaluable in 386 pts (118 had TP53MT). Treatment responses were evaluated using IWG 2023 criteria (Zeidan A et al, Blood 2023). Composite complete remission (cCR) was defined as CR+CRbi+CRuni+CRh+CRequivalent. We calculated OS from time of HMA initiation to date of death or last follow up. Unsupervised clustering (MOSAIC framework) was applied to identify molecular subgroups within the TP53MT cohort. The study was funded by an independent grant from Abbvie. Results A total of 1,485 pts were included. Median age was 69 years (IQR: 62–76), with 66% male pts. Median bone marrow blast was 7%, and 28% had a complex karyotype. Treatment regimens included azacitidine (68%), decitabine (15%), HMA/Venetoclax (8%), and other HMA combinations (9%); 34% underwent allo-HCT. Overall, 392 (26%) had TP53MT with 430 TP53 mutations (missense: 316; truncating: 89). Biallelic TP53MT % varied by classification: 72% (WHO), 84% (ICC), and 85% (CCF). Compared to TP53 wild-type (TP53WT) pts, pts with TP53MT had worse OS (median: 11.5 vs. 23.9 months [mo], p< 0.001), were younger (68 vs. 70 years, p=0.039), and had lower counts at diagnosis. Complex karyotype (81% vs. 14%) and chromosomal abnormalities were more frequent in TP53MT pts. Pts with TP53MT also had fewer co-mutations in other genes. Response to HMA was evaluable in 1,094 pts: cCR and CR were 32% and 13%, respectively. TP53MT pts had higher cCR (39% vs. 29%, p=0.001) than TP53WT, but similar CR rates (16% vs. 12%, p=0.093). According to WHO 2022, biallelic TP53MT had higher CR rates than monoallelic TP53MT (18% vs. 8%, p=0.03), but similar cCR. ICC and CCF classifications did not differentiate response rates. Median OS did not differ by TP53MT allelic status using WHO or ICC definitions. However, using the CCF method, pts with biallelic TP53MT had shorter OS than monoallelic TP53MT (10.4 vs. 17.2 mo, p=0.038). In multivariable models adjusted for age, gender, and allo-HCT, only the CCF-defined biallelic TP53MT group had significantly worse OS (HR: 1.6; 95% CI: 1.1–2.4). TP53MT pts undergoing allo-HCT had improved OS regardless of allelic status. Median OS for TP53MT pts with allo-HCT was 18.9 vs. 9.2 mo without all-HCT. This benefit was observed across WHO, ICC, and CCF classifications. However, a TP53MT VAF ≥19% predicted worse OS even post allo-HCT (14.6 vs. 47.1 mo, p<0.001). At 1 year, the survival rate was 78% (95%CI: 69-89%) in TP53MT pts who underwent allo-HCT and had cCR vs. 68% (95%CI: 55-84%) in pts who did not have cCR. However, 1 year survival rate was significantly higher for pts with TP53MT who did not have allo-HCT and achieved cCR (60%, 95%CI: 48-76%) vs. no cCR (26%, 95%CI: 20-35%). Unsupervised clustering of 335 TP53MT pts identified 9 molecular clusters (MCs). MC2, characterized by low TP53MT VAF (median 17%), fewer co-mutations, and frequent del17p, was associated with significantly improved OS (17.9 mo) and predicted favorable outcome (HR for death: 0.6; 95% CI: 0.4–0.8). Other clusters were enriched for adverse features (e.g., high VAF, multi-hit TP53MT).Conclusions The CCF method appears to best classify biallelic TP53MT pts with worse survival in the absence of accurate assessment of LOH status. Treatment response per IWG 2023 for TP53MT pts was associated with OS only in non-transplanted pts. Allo-HCT improved survival across TP53MT subsets, but TP53 VAF ≥19% at diagnosis remained a strong negative prognostic factor. Integrative clustering revealed a less aggresive molecular subset among TP53MT pts, suggesting refined risk stratification may guide therapy in this high-risk population. Ref: 1.Bahaj et al. J Hematol Oncol 2023.

Abstract Introduction: Marrow complete remission (mCR) in 2006 IWG criteria for MDS (Cheson B et al, Blood 2006) reflects achieving bone marrow (BM) blast percentage below 5% but is frequently not associated with meaningful count recovery. While mCR + hematologic improvement (HI) does reflect wide ranges of count improvement or transfusion reductions, HI is difficult to measure accurately in routine clinical practice. The 2023 International Working Group (IWG) response criteria (Zeidan A et al, Blood 2023) eliminated the mCR category without meaningful count recovery and reclassified mCR associated with meaningful count recovery into specific “less-than-CR” categories. Still, many clinical trials continue to use mCR as a secondary efficacy endpoint or as a part of overall response rate (ORR). Within the icMDS VALIDATE database, we assessed the association of mCR with OS in hypomethylating agent (HMA)-treated higher risk (HR)-MDS patients among both (1) transplanted and (2) non-transplanted patients. Methods We included patients with HR-MDS (defined as IPSS ≥1.5 and/or IPSS-R >3.5) who received HMA-based therapies from the international icMDS VALIDATE dataset. We evaluated the best response by IWG 2006 criteria into CR, mCR, or no CR/mCR. We then reclassified patients with mCR per IWG 2023 criteria into either (A) having achieved a composite CR (cCR) defined as CR + CR equivalent (CRequ) + CR with bilineage count recovery (CRbi) + CR with unilineage count recovery (CRuni) + CR with partial hematologic recovery (CRh) or (B) not having achieved cCR (no cCR). OS was calculated from time of HMA initiation to date of death or last follow-up by using 6-month landmark analyses. We used Kaplan-Meier methods to estimate OS, and the Log-rank test to compare OS. VALIDATE is supported by an independent grant from AbbVie. Results A total of1049 patients met eligibility.Median age of patients was 69 (range 21-95), 64% were men. While 61% received azacitidine, 17% received decitabine, and 22% received HMA-based combination therapy. In total, 37% underwent subsequent allogenic stem cell transplantation (allo-HCT). Based on IWG 2006 criteria, 17%, 33%, and 50% achieved CR, mCR, and no CR/mCR as their best response, respectively. Patients achieving CR had superior median OS (25 months, 95% CI: 21-34 months) compared to those with mCR (16 months, 95% CI: 13-18 months; p=0.038) and no CR/mCR (15 months, 95% CI: 12-17 months; p=0.001). In patients who received a subsequent allo-HCT, the median OS for patients with mCR (30 months, 95% CI: 21-54 months; 1 year OS: 71%, 2 year OS: 55%) did not significantly differ compared to patients with CR (59 months, 95% CI: 25 months-not reached, p=0.80; 1 year OS: 73%, 2 year OS 62%) and patients with no CR/mCR (32 months, 95% CI: 21-45 months, p=0.46; 1 year OS: 69%, 2 year OS 54%). In contrast, in patients treated with HMA therapy alone without subsequent allo-HCT, median OS for patients with mCR (11 months, 95% CI: 9-15 months; 1 year OS: 46%, 2 year OS: 23%) did not significantly differ compared to patients with no CR/mCR (11 months, 95% CI: 9-14 months, p=0.85; 1 year OS: 47%, 2 year OS: 22%) but was significantly shorter compared to patients with CR (20 months, 95% CI: 17-28 months, p<0.001; 1 year OS: 69%, 2 year OS: 46%). Patients with mCR by IWG 2006 (N=347) were reclassified per IWG 2023 into having either achieved a cCR (N=219, 63%) or no cCR (N=128, 37%). Specifically, patients with mCR were reclassified per IWG 2023 into CR (4.9%), CRequ (0.6%), CRbi (26.8%), CRuni (29.4%), CRh (1.4%), PR (0%), HI (10%), no response (21.9%) and PD (4.9%). Patients with mCR who were reclassified into cCR had an improved median OS (16 months, 95% CI: 15-26 months; 1 year OS: 62%; 2 year OS: 43%) compared to patients reclassified into no cCR per IWG 2023 (13 months, 95% CI: 11-17 months, p=0.023; 1 year OS: 52%; 2 year OS: 31%). Conclusions Using the large icMDS VALIDATE dataset, we found that achievement of mCR by 2006 IWG criteria was not associated with improved OS compared to patients who did not achieve CR/mCR. Reclassification of mCR using IWG 2023 highlights the heterogeneity within the mCR group and suggests that IWG 2023 criteria stratifies outcomes in patients previously labeled as mCR by IWG 2006. IWG 2023 should be the standard used for ORR assessment in all future clinical trials involving patients with HR-MDS.

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.

Introduction The International Prognostic Scoring System (IPSS) and its revised version (IPSS-R) were developed using datasets from patients (pts) with untreated MDS. The cytogenetic risk groups used in IPSS-R were expanded to 5 groups from the 3 used in IPSS. Among the new groups introduced in IPSS-R is the “very complex” karyotype (VCK) where ≥4 karyotypic abnormalities are seen compared to “complex karyotype (CK)” with only 3 abnormalities. However, the prognostic impact of VCK vs CK, as well as individual cytogenetic abnormalities and TP53 mutation (TP53mut) status within the CK and VCK subgroups in pts with MDS treated with hypomethylating agents (HMAs) has not been well studied. Hence, we analyzed these questions in a large cohort of HMA-treated MDS pts in the icMDS VALIDATE database. Methods The icMDS VALIDATE database contains MDS pts treated with frontline HMA monotherapy or HMA-based combinations from 22 specialized international centers. Pts with unknown HMA type, date of HMA initiation, missing age, missing sex, missing cytogenetic data, bone marrow or peripheral blood blasts ≥20%, or missing survival status were excluded. We performed time-to-event analyses using the Kaplan-Meier method and compared groups by the log-rank test. We measured overall survival (OS) from time of HMA initiation. VALIDATE protocol was exempted, acknowledged, or approved by all centers' IRBs. VALIDATE is supported by an independent grant from Abbvie. Results A total of 1940 pts were included. Median age was 70 (range: 18-99) years and 66% were men. According to IPSS-R cytogenetic risk groups, 1.9% (37) were very good, 43.4% (841) good, 15.5% (301) intermediate, 11.6% (226) poor, and 27.6% (535) very poor. By HMA type, 71% of pts were treated with azacitidine, 14% with decitabine, 6% with HMA and venetoclax, and 9% with another HMA combination. Approximately 28% of pts underwent allogeneic hematopoietic stem cell transplant (alloHSCT). The IPSS-R cytogenetic risk groups had different OS (p<0.001)with median OS (mOS; months [mo], 95% CI) as follows: very good (43.4, 34.7-72.5), good (41.7, 36.4-46.8), intermediate (24.5, 23.1-32.4), poor (24.2, 19.2-28.5), and very poor (13.6, 12.5-14.5). The difference remained significant (p=0.001) after censoring at time of alloHSCT with mOS as follows: very good (40.4, 23.2-64.3), good (24.3, 22.2-26.3), intermediate (19.3, 15.1-22.2), poor (12.2, 10.3-14.8), and very poor (9.1, 8.2-19.7). Interestingly, the difference between mOS for intermediate and poor risk cytogenetics became more apparent after censoring at time of alloHSCT. Next, we compared the outcomes of pts with CK and VCK to non-complex karyotype (NCK) MDS. The mOS for pts with VCK MDS (13.6 mo, 12.5-14.5) was worse compared to pts with CK (19.9 mo, 19.9-16.8; p=0.004) and NCK (36.1 mo, 32.7-37.8; p<0.001) MDS. Among the 1458 pts with available molecular data, more pts with VCK (75%, 330) MDS had a concurrent TP53mut compared to pts with CK (40%, 21; p<0.001) and NCK (7%, 64 p<0.001) MDS. Considering only patients with TP53mut MDS, mOS for pts with VCK (12.2, 11.1-13.9) was worse compared with NCK (24.2, 16-1-53.1; p<0.001) but not with CK (19.9, 9.5-NR; p=0.9); the difference between CK and NCK was not significant (p=0.16). Among pts with TP53 wildtype (TP53WT) MDS, VCK (15.0, 13.2-18.2) had a similar mOS to TP53WT CK (18.8, 12.6-41.1; p=0.19) while both groups had worse mOS compared to TP53WT NCK (33.4, 30.1-37.0) (p=0.01). In a survival analysis of 616 pts with MDS with ≥3 cytogenetic abnormalities, -17/del(17p) (12.8 mo; p=0.009), inv(3)/t(3q)/del(3q) (10.9 mo; p=0.006), and del(7q) (12.1mo; p=0.024), though not -7 (12.6mo; p=0.23), were associated with lower mOS compared to the pts with MDS without these abnormalities (14.3mo). Conclusions Using one of the largest databases of HMA-treated MDS pts, we show that IPSS-R cytogenetic risk categories associate with significantly different survivals among HMA-treated MDS pts, even after censoring at time of alloHSCT. Importantly, VCK MDS was associated with worse mOS compared to CK and NCK MDS but not in pts with a concurrent TP53mut. Among pts with MDS with ≥3 chromosomal abnormalities, having -17/del(17p), inv(3)/t(3q)/del(3q), or del(7q) was associated with worse survival.

Background. Study of myeloid neoplasms (MN) has been rapidly transformed by genome characterization. Gene mutations have been reported to influence disease phenotype and risk of disease progression, and the evaluation of mutational status can provide valuable insights to improve the decision-making process. In this international study, we evaluated the clinical impact of mutational screening in patients with CMML, which is characterized by significant clinical and genomic heterogeneity, including a substantial proportion of patients with poor outcomes and unmet needs. Currently, only limited molecular information has been incorporated into CMML classification and prognostication. Methods. We retrospectively collected 3182 CMML patients. We used MOSAIC, an AI-based framework for multimodal analysis in rare cancers (PMID: 38875514) to develop innovative, molecular-based tools for classification and prognostication. An independent validation of the results on 516 prospectively collected patients was performed. Results. Bayesian Networs and Hierarchical Dirichlet Processes were used to identify genomic associations and define a CMML molecular classification. We identified 11 clusters with distinct clinical and genomic features, including splicing machinery, signal transduction and tyrosine kinase pathways aberrations, and high-risk molecular signatures (i.e., AML-like and TP53 mutations). Up to 15% of patients showed clear genomic overlap with other MN. Importantly, extensive multi-color flow cytometry on T lymphocytes, NK and myeloid cells (BD FACSymphony A5 Cell Analyzer) revealed specific immunologic and inflammation signatures associated with molecular subgroups. We then integrated molecular and clinical information to build an international CMML Prognostic Scoring System (iCPSS). We assessed the performance of different statistical and AI-based methods; L1-penalized Cox Model resulted as the best performing method. Selected features included hematological parameters (WBC, Hb, PLT and marrow blasts), cytogenetic abnormalities, and mutations in 10 genes (ASXL1, DNMT3A, EZH2, NRAS, RUNX1, SETBP1, STAG2, TET2, TP53, U2AF1). By Bayesian thresholds optimization, we identified 5 risk classes (i.e., very-low, low, intermediate, high and very-high) with median overall survival (OS) ranging from 99 to 9 months (P<.001), and median leukemia-free survival (LFS) ranging from 210 to 18 months (P<.001). iCPSS provided better patient discrimination across all clinical endpoints compared to currently available prognostic tools, with a Concordance Index (CI) for OS of 0.75 versus 0.62-0.64, respectively. Notably, compared to available scoring systems, up to 40% of patients were reassigned to higher or lower risk classes by the iCPSS. External validation on an independent prospective cohort confirmed that the performance of iCPSS is superior to existing prognostic models (CI for OS 0.71 vs 0.54-0.61, respectively) To demonstrate the clinical utility of iCPSS, we focused on 753 patients who underwent allogeneic stem cell transplantation (HSCT). In multivariable analysis, iCPSS stratified the probability of OS post-HSCT (P<.001) and identified groups of patients with different probabilities of disease relapse, ranging from 9% to 62% (P<.001). We employed a clinical- and genomic-based decision support system (PMID: 38723212) to determine the optimal timing of HSCT. Preliminary analyses indicated that higher-risk patients according to iCPSS (i.e., intermediate, high, and very high) benefit from an immediate HSCT strategy. Lower-risk patients (i.e., very low and low) had life expectancy maximized with delayed HSCT. Modeling decision analysis using iCPSS compared to conventional scores, resulted in a change in transplantation policy for a significant proportion of patients (up to 25%). Conclusion. Molecular information significantly improves the classification of CMML patients, providing a basis for refining diagnostic boundaries with other MN and for a more rational inclusion of patients in clinical trials. The iCPSS demonstrated superior performance over currently available scoring systems and improved HSCT decision making process.

Introduction: Response assessment is used to evaluate effectiveness of hypomethylating agent (HMA)-based therapy in myelodysplastic syndromes/neoplasms (MDS) in clinical practice and trials. Recently, the clinical response criteria (IWG 2023) and the clinical-molecular risk assessment (IPSS-M) in MDS were published. However, it remains unknown whether the IWG 2023 response criteria have an independent impact on overall survival (OS) when adjusting for baseline IPSS-M risk. Additionally, the association of IWG 2023 response criteria with OS in patients (pts) undergoing allogeneic stem cell transplantation (allo-HCT) versus those who do not is unknown. Lastly, it is unclear if optimal time-to-transplant impacts OS in MDS pts who achieve a IWG 2023 defined remission with HMA therapy. We examined these questions in a large population of MDS pts within the multi-institutional international consortium for MDS (icMDS) VALIDATE database. Methods: High-risk MDS pts with IPSS ≥1.5 or IPSS-R >3.5 treated with HMA-based therapy were included in the study. Baseline IPSS-M risk was stratified into very low/low/moderate low (VL+L+ML), moderate-high/high (MH+H), and very high (VH). Response to treatment was evaluated using the IWG 2023 criteria and grouped into: composite complete response (cCR) and no cCR. cCR included: complete response (CR), CR equivalent (CRequ), CR bilineage (CRbi), CR unilineage (CRuni), and CR with partial hematologic recovery (CRh). We analyzed the differential impact of achieving cCR on HMA-based therapy prior to transplant on OS in pts who either did or did not undergo allo-HCT, while adjusting for their baseline IPSS-M risk in Cox regression analysis. Optimal time-to-transplant was determined based on age and IPSS-M category as described by Tentori et al. (JCO 2024). Pts proceeding to allo-HCT were stratified on whether they underwent transplant within the optimal time-to-transplant timeframe after MDS diagnosis or not. VALIDATE protocol was exempted, acknowledged, or approved by all centers' IRBs. VALIDATE is supported by an independent grant from AbbVie. Results: We analyzed 762 MDS pts. The median age at MDS diagnosis was 68 years (range: 19-95 years) and 64% of pts were male. Distribution of the baseline IPSS-M risk was: VL+L+ML in 110 (14%) pts, MH+H in 347 (46%) pts, VH in 305 (40%) pts. Pts received azacitidine monotherapy, decitabine monotherapy, and HMA-based combination therapy (e.g. HMA + venetoclax) in 52%, 21%, and 28% of cases, respectively. A total of 282/762 (37%) pts achieved cCR as their best response to HMA-based therapy. The median OS for all pts was 18.7 months (95% CI: 16.6-21.3 months). Pts who did not undergo allo-HCT (n=436, 57%) had an improved median OS if they achieved cCR when compared to pts in the no cCR group in all IPSS-M risk groups (VL+L+ML: 23.5 months vs. 10.7 months; MH+H: 20.8 months vs. 11.6 months; VH: 13.8 months vs. 7.5 months). Cox analysis demonstrated an independent effect of cCR on OS in these pts when adjusted for baseline IPSS-M risk (cCR vs. no cCR: HR 0.60, 95% CI 0.48-0.76, p<0.001). In contrast, in pts who subsequently received an allo-HCT (n=326, 43%), achieving cCR with HMA prior to allo-HCT did not provide an additional OS benefit, when adjusted for baseline IPSS-M risk (cCR vs. no cCR: HR 1.00, 95% CI 0.73-1.38, p=0.986). The median time-to-transplant was 6.7 months and 34% of transplanted MDS pts received their allo-HCT during the optimal timeframe. Among pts who achieved cCR with HMA-based therapy prior to allo-HCT, optimal time-to-transplant was associated with significantly improved OS (optimal vs. non-optimal timing: HR 0.55; p=0.033). Conclusion: Baseline IPSS-M risk and allo-HCT had an independent impact on OS, while IWG 2023 defined cCR had an independent effect on OS only in non-transplanted MDS pts. While this retrospective analysis occurred at large academic centers with specific expertise in the management of MDS, our data may have an impact on clinical practice: (i) failure to achieve cCR on HMA therapy prior to transplant should not impact the decision to proceed to allo-HCT, (ii) upfront allo-HCT without prior HMA therapy might also be an option if the clinical situation and availability of donors allow, and (iii) allo-HCT should ideally be performed during the timeframe that is considered optimal as defined by pt age and baseline IPSS-M.

Introduction: The NHLBI National MDS Study (NCT02775383) is a prospective cohort study conducted at 92 community hospitals and 29 academic centers. It enrolls patients undergoing work up for suspected MDS to understand the genetic, epigenetic, and biological factors associated with the initiation and progression of the disease. Previously untreated, cytopenic participants undergo both local and centralized pathology review and are assigned a diagnosis, including MDS, MDS/MPN, AML with blasts < 30%, and "Other". Emerging data suggests that Next Generation Sequencing (NGS), along with cytogenetics and clinical variables, may improve MDS diagnostic precision. Given that our study relies on central review (with additional tertiary pathology review used to adjudicate disagreements), we examined whether targeted gene sequencing data could be used to increase the agreement between local and central pathologic diagnosis of MDS vs. Other. Methods: Peripheral blood and bone marrow (BM) biopsy specimens from cytopenic patients, along with clinical history, CBC, and other results including karyotyping, FISH and pathology reports from local pathologists were reviewed by central pathologists. The updated 2016 WHO classifications were used to diagnose MDS. Targeted exon sequencing of 96 genes was performed using BM specimens. A subset of 648 individuals that were classified as MDS (n=212) or Other (n=436, including 90 CCUS and 89 individuals with other cancers) by pathology assessments were selected. A mean coverage of 1,317X was achieved and variants had a minimum variant allele frequency (VAF) of 2% (except FLT3). Variants for 596 subjects were manually reviewed to retain likely disease-causing variants to build a binary classifier (MDS vs. Other) using the maximum VAF per gene as input (Figure 1). Subjects diagnosed with MDS or Other by both central and local pathology were used for training, validation, and testing, and were considered "gold standard" (GS) cases (n=546). These subjects were split into 4 random groups with equal proportions of MDS cases. 75% of the GS cases were used to train and validate lasso-regularized logistic regression models using 3-fold cross validation. ROC curve analysis was carried out using the remaining 25% of GS cases (Test Set 1) on the best model to identify an optimal probability cut off point for classifying subjects as MDS. Model performance was then tested on 50 subjects for which the central and local pathology diagnosis disagreed (Test Set 2), as well as on 52 additional subjects irrespective of agreement (Test Set 3). Results : The best performing logistic regression model retained 7 genes as most informative in a discriminating diagnosis of MDS from Other based on their VAFs, in order of impact: TP53, SF3B1, U2AF1, ASXL1, TET2,STAG2, and SRSF2. We used this model to assign probabilities for each of the subjects in Test Set 1 and to estimate the performance using ROC analysis (Figure 1), resulting in a high area under the curve (AUC) of 0.89. We chose a probability cut-off of ≥0.17, being associated with a high percentage of correct classification of MDS with a sensitivity and specificity of 0.90 and 0.81, respectively. Among the cohort of 50 subjects with a discordant local and central pathology diagnosis (Test Set 2), the classifier accurately reassigned 37 subjects (accuracy = 74%) from the local to the central pathology. The blinded tertiary pathology reviewer agreed with central in all Test Set 2 cases. This included 24/34 MDS cases that had been labeled as Other by local pathology (positive predictive value [PPV]=0.89). 3/16 final pathology-classified Other cases were mis-classified as MDS by the local pathologist (negative predictive value [NPV] = 0.57). Next, we assessed the ability of the model to predict MDS vs. Other for 52 additional independent subjects using the third pathologist's diagnosis to break any ties (Test Set 3). The classifier correctly predicted 15/21 MDS cases (PPV=0.83) and misclassified 6/31 Others as MDS (NPV=0.82). The overall accuracy was 83%. Conclusions: We identified that VAFs for 7 genes can correctly re-classify subjects as either MDS or Other in 74% of cases that were misclassified between local and central pathology review. Further assessment on an independent cohort showed an accuracy of 83% of the model. Taken together, these data suggest that complementing pathology reviews with targeted sequencing of 7 genes could improve MDS diagnosis. Disclosures Lindsley: MedImmune: Research Funding; Jazz Pharmaceuticals: Consultancy, Research Funding; Bluebird Bio: Consultancy; Takeda Pharmaceuticals: Consultancy. Bejar:Aptose Biosciences: Current Employment; AbbVie/Genentech: Honoraria; Astex/Otsuka: Honoraria; Takeda: Honoraria, Research Funding; Celgene/BMS: Honoraria, Research Funding; Daiichi-Sankyo: Honoraria; Forty-Seven/Gilead: Honoraria; Genoptix/NeoGenomics: Honoraria. DeZern:MEI: Consultancy; Astex: Research Funding; Abbvie: Consultancy; Celgene: Consultancy, Honoraria. Foran:H3Biosciences: Research Funding; Aptose: Research Funding; Kura Oncology: Research Funding; Trillium: Research Funding; Takeda: Research Funding; Revolution Medicine: Consultancy; Xencor: Research Funding; Agios: Honoraria, Research Funding; Aprea: Research Funding; Actinium: Research Funding; Servier: Membership on an entity's Board of Directors or advisory committees; Novartis: Membership on an entity's Board of Directors or advisory committees; Abbvie: Research Funding; BMS: Membership on an entity's Board of Directors or advisory committees; Pfizer: Membership on an entity's Board of Directors or advisory committees; Boehringer Ingelheim: Research Funding. Gore:Abbvie: Consultancy, Honoraria, Research Funding. Komrokji:Acceleron: Honoraria; Incyte: Honoraria; Abbvie: Honoraria; Agios: Speakers Bureau; BMS: Honoraria, Speakers Bureau; Jazz: Honoraria, Speakers Bureau; Geron: Honoraria; Novartis: Honoraria. Maciejewski:Alexion, BMS: Speakers Bureau; Novartis, Roche: Consultancy, Honoraria. Padron:Novartis: Honoraria; BMS: Research Funding; Incyte: Research Funding; Kura: Research Funding. Starczynowski:Captor Therapeutics: Consultancy; Tolero Therapeutics: Research Funding; Kurome Therapeutics: Consultancy, Current equity holder in private company, Research Funding. Sekeres:BMS: Consultancy; Takeda/Millenium: Consultancy; Pfizer: Consultancy.