Citations

Abstract Background Liver surgery carries a high risk of complications due to the complex interplay of patient-related factors, disease characteristics, and liver function. Expertise is essential for healthcare professionals managing hepatobiliary patients. This European consensus provides evidence-based guidance on selected aspects of peri- and postoperative care. Methods A modified Delphi process was used to achieve consensus, with a 70% agreement threshold. The expert panel comprised hepatobiliary surgeons, anaesthetists, hepatologists, a specialist nurse, and a physiotherapist. A systematic literature search was conducted in PubMed/MEDLINE, Embase, Web of Science, and Cochrane databases. Six topics were addressed: thromboprophylaxis; perioperative antibiotics; prehabilitation/nutrition/mobilization; bile leak including bilioenteric anastomosis leaks; post-hepatectomy haemorrhage; and post-hepatectomy liver failure (PHLF). Evidence appraisal and statement development followed Scottish Intercollegiate Guidelines Network methodology. A patient representative reviewed the guideline. Results Searching the literature yielded 204 included publications from an initial 6514. Thirty-two statements were formulated with a median evidence level of 2. Evidence strength varied by topic with noticeably lower evidence levels in complex surgery settings and less prevalent conditions. In some topics, study heterogeneity and specific inclusion criteria resulted in conditional recommendations, despite high-level evidence. Notably, the weakest evidence was found for perioperative thromboprophylaxis and PHLF management. Strong recommendations were formulated for prehabilitation, early postoperative mobilization, and avoidance of routine drain use. Several evidence gaps warranting multicentre studies were identified. Conclusion Optimizing peri- and postoperative care after liver resection remains challenging. Standardizing key practices and addressing evidence gaps through collaborative research are vital to improve outcomes.

Abstract Background The Joint Propagation Model (JPM)‐based CenTauR scale was recently introduced to harmonize tau‐PET quantification across different radiotracers. This study examined how CenTauR harmonization enhances the comparability of tau‐PET quantification across matched cohorts using different tracers. The evaluation focused on three key aspects: (1) comparing tau‐PET positivity rates as defined by CenTauR, (2) evaluating its diagnostic accuracy for symptomatic AD, and (3) analyzing longitudinal changes in tau‐PET rates over time. Method The JPM, developed by the CPAD‐led Tau PET Harmonization Working Group (Leuzy et al., Alzheimers Dement. 2024; Figure 1A), models relationships between anchor point subjects and head‐to‐head tau‐PET SUVR data onto the CenTauR scale, providing conversion equations for multiple tracers. JPM equations were applied to [¹⁸F]flortaucipir SUVR (Meta‐temporal ROI) data from 561 cognitively impaired participants in the ADNI and OASIS‐3 studies. Using ROC analysis, we determined the CenTauR cut‐off for positivity (T+) that maximized the Youden index for discriminating between FDA‐approved positive/negative visual reads. Three separate cohorts, scanned using [¹⁸F]flortaucipir (ADNI), [¹⁸F]MK‐6240 (CPAS), and [¹⁸F]RO‐948 (BioFINDER‐2), were matched 1:1 by age, MMSE, amyloid‐β, and clinical diagnosis. CenTauR‐based metrics were compared across these cohorts. Result A cut‐off of 18 CenTauRs was found to optimally classify [ 18 F]flortaucipir PET visual reads (Figure 1B). The matching procedure identified 1089 participants (363 per cohort). The frequency of T+ using the 18 CenTauRs cut‐off for the Meta‐Temporal ROI was highly comparable across tracers across groups, except for the Aβ‐positive cognitively unimpaired group, where variability was more pronounced due to a smaller sample size (Figure 2A). Similarly, tau‐PET discriminative accuracy for symptomatic AD vs controls remained similar across [ 18 F]flortaucipir and [ 18 F]MK‐6240 (Figure 2B). In a separate sample of 212 matched participants from ADNI ([¹⁸F]flortaucipir) and AIBL ([¹⁸F]MK‐6240) with baseline and 1‐year follow‐up tau‐PET scans, 1‐year change in CenTauRs was comparable (Figure 2C). An exploratory voxelwise transformation, utilizing the Meta‐Temporal conversion equation in a representative case scanned with both [¹⁸F]flortaucipir and [¹⁸F]MK‐6240, demonstrates the potential for voxelwise CenTauR harmonization (Figure 3). Conclusion These analyses suggest that CenTauR harmonization increases the comparability of tau‐PET data acquired with different tracers. Additional validation analyses with larger cohorts including other radiotracers ([¹⁸F]PI‐2620) are underway.

Abstract Objectives Patient education is increasingly acknowledged as an important aspect of the management of systemic lupus erythematosus (SLE). The aim of the study was to develop the SLE Knowledge Assessment score (SLAKE), a digital multilingual self-assessment tool designed to quantify essential SLE knowledge. Methods International healthcare professionals (HCPs) and patient representatives engaged in a multi-step process to: identify essential SLE knowledge domains, select key domains via rating, and generate an item bank of 394 questions across 11 domains, which was then adapted into 19 languages. For validation, participants completed 44 questions (including 33 randomly selected), with scores calculated for total knowledge and the 11 specific domains. Statistical analyses examined associations between scores and demographic, clinical, and educational variables. Results SLAKE was used by 1182 SLE participants (1120 [94.8%] women, median age: 45 years [IQR: 35–54 years]), with a median SLE duration of 10 years (IQR: 4–20 years). The median SLAKE score was 37 (IQR: 34–40) of a maximum of 44 points while the median score across the 11 SLAKE domains ranged between 3 and 4 over a maximum of 4 points. There was a significant positive association between SLAKE score and SLE duration (p= 0.006), previous participation to a patient education course or a patient training for lupus (p< 0.0001) and the education level (p< 0.0001) but not with age (p= 0.48) or gender (p= 0.39). Conclusion SLAKE is a valid, multilingual, digital self-assessment tool that effectively measures essential SLE knowledge. Its randomized question bank and domain-specific scoring enable targeted education, ultimately supporting better disease management.

Abstract Introduction: The prognosis of patients (pts) with histological transformation (HT) of Waldenström macroglobulinemia (WM) remains dismal with standard chemoimmunotherapy. CD19-targeted chimeric antigen receptor T-cell therapies (CAR-T) can lead to durable responses in relapsed/refractory (R/R) large B-cell lymphoma (LBCL) and are approved in the second or third line settings. Pts with HT-WM were largely excluded from CAR-T trials. We previously reported high response rates in a series of 23 pts. The aim of the present study was to evaluate a larger cohort of pts with R/R HT-WM treated with CAR-T with a longer follow-up. Methods: We performed a multicenter retrospective study of pts with biopsy-proven transformed WM/lymphoplasmacytic lymphoma treated with CAR-T in the French DESCAR-T registry (NCT04328298), 4 centers from ECWM and 4 US centers. This study includes updated data from previously published cases (Durot et al, Blood, 2024). Responses were assessed according to the Lugano 2014 criteria. Cytokine release syndrome (CRS) and immune effector cell-associated neurotoxicity syndrome (ICANS) were graded according to the ASTCT 2019 consensus criteria. Hematological toxicity and infections were graded according to the NCI CTCAE (version 5.0). Progression-free survival (PFS) and overall survival (OS) were calculated from the date of CAR-T infusion and estimated using the Kaplan-Meier method. Results: 50 pts were included (39 from DESCAR-T centers, 7 from US centers and 4 from ECWM centers). Median age was 60 (range: 32-72) and 68 (range: 42-82) years at WM diagnosis and CAR-T infusion, respectively. MYD88L265P and CXCR4 mutations were present in 79% (23/29) and 15% (2/13) of patients with available data, respectively. The median time from WM to HT diagnosis was 5.3 years (range: 0-32). Median prior lines of therapy was 1 (range: 0-9) for WM and 2 for HT (range: 0-4). Twenty (40%) pts previously received a BTK inhibitor for WM or HT, 12 (24%) underwent prior autologous SCT and 1 pt allogeneic SCT. 40% of pts presented primary refractory disease and 44% were refractory to last treatment before CAR-T. 40 pts (80%) received bridging therapy, of whom 17 (44%) responded (7 complete responses (CR)). 35 (70%), 10 (20%), and 5 (10%) pts received axicabtagene ciloleucel (axi-cel), tisagenlecleucel (tisa-cel), and lisocabtagene maraleucel (liso-cel), respectively. The best overall response rate (ORR) was 94%, with 44 (88%) pts reaching CR. With a median follow-up of 25.7 months (range: 1-69) from CAR-T infusion, the median PFS was 1.2 years (95% CI: 0.5-4.5) and median OS was 4.2 years (95% CI: 1.2-not reached). Median duration of response was 1.5 years (95% CI: 0.4-4.4), with a median of 4 years (95% CI: 1.5-NR) for pts still in CR at 6 months after CAR-T. 22 pts experienced relapse/progression after CAR-T, 19 related to LBCL and 3 to WM. Median survival after relapse was 7.9 months (95% CI: 3.8-25.3). At LBCL relapse after CAR-T, salvage therapy consisted of CD20xCD3 bispecific antibodies for 9 pts, lenalidomide +/- anti-CD20 or anti-CD19 antibody for 6 pts, and BTKi for 3 pts. Among 19 pts who died, 14 (74%) were due to progressive disease and 5 (26%) from infections. 37 (76%) pts experienced CRS, including 2 (4%) grade 3 events, and 22 (45%) had ICANS, with 2 (4%) ≥ grade 3 events. 17 (35%) pts presented infections, including 12 ≥ grade 3. 21 (43%) pts developed ≥ grade 3 prolonged cytopenias (ie, not resolved within 30 days post infusion). CNS involvement due to LBCL was present in 11 pts (22%) at the time of CAR-T. 6 of them had ICANS, with 1 grade 4. The best ORR was 91% (best CR 91%). Only 1 patient did not obtain a response, with stable disease at 1 month and progression at 3 months. The median PFS was 1.2 year (95% CI: 0.2-NR) and median OS was NR (95% CI: 0.5-NR). On univariate analysis, only elevated LDH was correlated with worse PFS (HR 2.5, p=0.04) and OS (HR 3.3, p=0.04). Other variables, including number of prior lines of therapy, MYD88 mutation status, primary refractory disease, refractory to last treatment, CNS involvement before CAR-T, response after bridging therapy and type of CAR-T received, were not associated with inferior PFS or OS. Conclusion: This cohort represents the largest series of pts with transformed WM treated with anti-CD19 CAR-T. We confirm the high efficacy previously reported with an acceptable safety profile, including for pts with CNS involvement due to LBCL at CAR-T infusion.

Abstract Background: The recently published BLAST clinical and BLAST molecular (BLAST-Mol) risk models for chronic myelomonocytic leukemia (CMML) incorporate clinical and molecular variables, respectively, for prediction of overall survival (OS), while BLAST-BT (blast transformation) risk model was predictive of BT free survival (BTFS) [Blood 2025;doi:]. In the current study, the Mayo Clinic (USA) CMML cohort used in the aformentioned study was expanded from 457 to 600 patients and merged with an external cohort of 501 patients from the Humanitas Research Hospital (HRH; Italy) in order to validate the BLAST, BLAST-Mol and BLAST-BT risk models. Methods: CMML diagnosis and sub-categorization were according to the International Consensus Classification, which included CMML-1 (BM/PB blasts <10%/<5%) vs. CMML-2 (BM/PB blasts ≥10%/≥5%) and CMML-MP (leukocytes ≥13 x 10⁹/L) vs. CMML-MD (leukocytes <13 x 10⁹/L) [Blood 2022;140:1200]. The BLAST score is based on clinical risk factors including PB blasts ≥2%, leukocytes ≥13 x 109/L, and severe or moderate anemia resulting in BLAST low, intermediate, and high risk groups. BLAST-Mol also accounts for mutations and karyotype and identifies PHF6 and TET2 as “favorable” and DNMT3A, U2AF1, BCOR, SETBP1, ASXL1, NRAS, PTPN11, RUNX1, TP53, as “unfavorable” mutations with adverse karyotype also considered unfavorable. BLAST-BT variables include absence of PHF6MUT, BM blasts ≥10%, presence of DNMT3AMUT, PB blasts ≥2%, leukocyte count ≥13 x 109 /L, and ASXL1MUT. OS analyses were censored for allogeneic stem cell transplant (ASCT). Conventional statistical methods were employed, using JMP Pro 18.0.0 software SAS Institute, Cary, NC, USA. Results: A total of 1,101 patients (median age 73 years; 67% males) with newly-diagnosed CMML were considered: Mayo cohort 600 and HRH cohort 501. Compared to the HRH cohort, the Mayo cohort was more likely to include CMML-MP (44% vs. 28%; p<0.01), CMML-1 (87% vs. 81%; p<0.01), ASXL1MUT (48% vs. 35%; p<0.01), SRSF2MUT (43% vs. 33%; p<0.01), NRASMUT (15% vs 9%; p<0.01), PHF6MUT (7% vs. 4%; p<0.01), and less likely to harbor TET2MUT (50% vs. 58%; p<0.01), and SF3B1MUT (4% vs. 10%; p<0.01) [Table 1]. At a median follow-up of 55 months (range 0-202), 686 (62%) deaths, 218 (20%) BTs, and 142 (13%) ASCTs were documented. CPSS-mol risk categories at diagnosis included low (N=190; median OS 67 months), intermediate-1(N=271; median 38 months), intermediate-2 (N=407; median 26 months), and high (N=231; median 16 months; p<0.01) [AUC at 5 years 0.75]. BLAST clinical risk distribution was low (N=356; median OS 65 months), intermediate (N=393; median 30 months), and high (N= 352; median 16 months; p<0.01) [Figure 1; AUC at 5 years 0.79]. The corresponding AUCs calculated for the Mayo and HRH cohorts, separately, were 0.81 and 0.76, respectively. BLAST-Mol risk assignments included low (N=357; median OS 66 months), intermediate (N=512; median 27 months) and high (N=232; median 15 months; p<0.01) [Figure 2; AUC at 5 years 0.79]. The corresponding AUCs for the Mayo and HRH cohorts were 0.81 and 0.77, respectively. The 3-year cumulative incidence of BT (accounting for death from another cause) stratified by BLAST-BT risk model included 8% for very low risk (N=54), 11% for low risk (N=332), 20% for intermediate-risk (N=281), 27% for high risk (N=250), and 34% for very high risk (N=176) [p<0.01; Figure 3]. Multivariable analysis of the combined Mayo-Humanitas cohort (N=1,101) identified age >65 years (HR 1.7, 95% CI 1.3-2.1), CMML-2 subtype (HR 2.0; 95% CI 1.6-2.5), and a number of other mutations or co-mutations with BLAST-Mol-independent and CPSS-mol-independent prognostic contribution (to be elaborated further at the time of meeting presentation). Conclusions: The current study validates the predictive performance of the BLAST, BLAST-Mol and BLAST-BT risk models in a large two-center international cohort of patients with CMML. The possibility of further enhancement of the BLAST-Mol model is suggested by the demonstration of independent prognostic relevance from additional mutations and co-mutations.

Abstract Background: Multiple myeloma (MM) is always preceded by monoclonal gammopathy of undetermined significance (MGUS) and smoldering multiple myeloma (SMM). While these precursor conditions are asymptomatic, they are not entirely benign and carry a lifelong risk of progression to MM. Unlike other cancers defined by pathology, malignant transformation from MGUS or SMM to MM has so far relied on demonstration of clinical end-organ damage or high tumor cell burden (i.e. SLiM criteria, SV Rajkumar Lancet Onc 2014), as morphology and cytogenetics cannot reliably distinguish them. Methods: To identify genomic features underlying clinical behavior in MGUS and SMM, a total of 374 patients with SMM (n= 290) or MGUS (n=84) with available whole exome (whole exome sequencing, WES, n=190) or whole genome sequencing (whole genome sequencing WGS, n=184) were included in the study. Overall, none of the patients had evidence of SLiM or CRAB criteria at the time of the biopsy. Based on the center of origin and availability of WES and WGS, 227 and 97 patients were used to form our study training and validation set. The study was designed in two parts: 1) defining a new classification for MM precursor conditions; 2) integrating genomics to existing prognostic score to improve accuracy in identifying patients at imminent risk of progression. Overall, 68 patients in the training set were either lost to follow-up or enrolled in a clinical trial and they were only included in the classification part of the study. Results: By leveraging the distribution of established MM-defining genomic events (Maura et al. JCO 2024) in the training set, we developed a workflow that differentiates MGUS and SMM into two genomically distinct entities: one with evidence of neoplastic transformation (i.e., genomic MM) and one without (i.e., genomic MGUS). Overall, 39% of MGUS and 91% of SMM cases had genomic evidence of neoplastic transformation in the training set (i.e., genomic MM). When we applied the same workflow and classification to the validation set, 46% and 83% of MGUS and SMM had evidence of neoplastic transformation, respectively. Importantly, none of the patients classified as genomic-MGUS progressed to MM in either the training or validation cohorts, with a median follow-up of 40 and 61 months, respectively. Moreover, all patients with IMWG 2/20/20 high risk SMM were classified as genomic MM in both the training and validation set. Interestingly, 5 out of 62 (8%) patients enrolled in early intervention trials for high risk SMM were genomically classified as genomic-MGUS. Overall, these data demonstrated that the MM genomic background and neoplastic transformation can be acquired very early in time, even before the SMM phase, in line with what observed in solid tumors. To avoid overestimating the prognostic impact of myeloma-defining genomic events—which are, by definition, enriched in the genomic-MM group compared to genomic-MGUS—we restricted our prognostic analysis to patients in whom transformation has already occurred (genomic-MM). In fact, distinct genomic drivers may predict malignant transformation but not necessarily the risk of imminent progression to MM once transformation has occurred. After running 5-fold cross validations corrected for IMWG 2/20/20, only presence of RAS mutations, genomic events involving MYC, presence of neoplastic copy number variant (CNV) signatures and APOBEC mutagenesis were predictive of early progression in the training set. Adding the presence of high-risk myeloma-defining genomic events to the IMWG 2/20/20 model (i.e., genomic-IMWG) significantly improves the accuracy of predicting MM progression in both the training (c-index 0.69 vs. 0.74) and validation sets (c-index 0.74 vs. 0.79), compared to the IMWG 2/20/20 alone. Conclusion: By leveraging comprehensive genomic profiling integrated with the clinical IMWG 2/20/20 risk score, we propose a novel classification and prognostication system for MM precursor conditions, which will better define patients who may benefit from early therapeutic intervention versus watch-and-wait monitoring.

Abstract Introduction AL amyloidosis is a rare disorder caused by amyloid fibrils produced by clonal plasma cells, leading to serious organ dysfunction. Cardiac involvement is a major risk factor for poor survival. CD38-binding Daratumumab (D) targets plasma cells and, with bortezomib, cyclophosphamide and dexamethasone (VCd) is the only approved regimen for newly diagnosed AL amyloidosis. The ANDROMEDA phase 3 study showed significant improvements in hematologic responses, major organ deterioration progression free survival and overall survival, compared with VCd alone. The AQUARIUS study (NCT05250973) evaluated cardiac safety of different D-VCd schedules and potential cardiac toxicity mitigation strategies. Methods This multicenter, open-label, phase 2 study enrolled 151 newly diagnosed AL amyloidosis patients at 37 sites in 10 countries. Patients enrolled in either Cohort 1 (n=120, cardiac involvement [Mayo 2004 stage II/IIIA], randomized 2:1 to receive D + immediate VCd or D + deferred VCd) or Cohort 2 (n=31, racial or ethnic minorities with ≥1 any organ involvement, treated with D + immediate VCd). Immediate VCd began on Cycle 1, deferred VCd on Cycle 4. The primary safety endpoint was the incidence of cardiac treatment emergent adverse events (TEAEs). Cardiac assessments included HS TroponinT, NT-proBNP, echocardiogram (ECHO), ECG, NYHA, and the 6-minute walk test (6MWT). Clinical cardiac signs and symptoms (S&S) were assessed at baseline and monthly. Selected, clinically relevant grade ≥3 and/or serious cardiac TEAEs were defined as Major Cardiac TEAE and were assessed by an independent adjudication committee for causality. Patients were followed for 12 treatment cycles or 12 months from first dose (if treatment discontinued prior to 12 cycles). Results 142 patients from both cohorts had cardiac involvement and received at least one dose of D + immediate VCd (n=103) or D + deferred VCd (n=39). Baseline characteristics were balanced between the two groups, including Mayo 2004 stage (IIIa: immediate VCd, 35.0%; deferred VCd, 35.9%; II: immediate VCd, 62.1%; deferred VCd, 53.8%). Treatment duration (median: 10.4 months) and proportion completing ≥10 cycles (79% vs 85%) were similar. Serious cardiac TEAEs occurred at similar rates across groups (immediate VCd, 7.8%; deferred VCd, 7.7%). The most common serious cardiac TEAE (MedDRA term) was cardiac failure (immediate VCd, 5.8%; deferred VCd, 2.6%). Two deaths occurred within 60 days of first study treatment, both were in the immediate VCd group, cardiac-related and unrelated to treatment. The immediate VCd group had fewer cardiac TEAEs overall (48.5% vs 61.5%) but experienced them more frequently during Cycles 1-3 than deferred VCd (35.9% vs 28.2%). This trend reversed for Cycles 4-6 (immediate VCd, 17.7%; deferred VCd, 28.9%). Cardiac TEAEs were low for both groups for Cycles 7-9 (immediate VCd, 9.3%; deferred VCd, 12.1%) and Cycles 10-12 (immediate VCd, 7.4%; deferred VCd, 12.1%). Levels of NT-proBNP, HS troponin T, the 6MWT, and overall cardiac S&S improved similarly for both treatment groups. Rate of cardiac TEAEs of any grade was similar for Mayo stage III patients in the two groups (immediate VCd, 73.0%; deferred VCd, 68.8%) whereas for Mayo stage II patients the incidence was higher in the deferred group (35.9% vs 57.1%). Twenty patients (Immediate VCd, 13; deferred VCd, 7) experienced 30 Major Cardiac TEAEs (selected grade ≥3 and/or serious). Adjudicators attributed 28 events primarily to amyloid cardiomyopathy and 2 events primarily to treatment. These 20 patients had higher baseline Mayo stage (IIIa: 70% vs 29.5%) than the remaining patients (n=122), higher baseline median NT-proBNP (4862 ng/L vs 1723 ng/L) and overall S&S score (7.5 vs 4.0). Several ECHO measures were worse at baseline in these 20 patients (notably, median GLS: -8.8% vs -13.7% and E prime lateral: 4.4 cm/s vs 6.1 cm/s) as was 6MWT (median distance: 319 m vs 363 m). Complete Response (CR) rates were similar in both groups: immediate VCd, 62.1%; deferred VCd, 59.0%. Median time to CR was 64 days for the immediate VCd group and 113 days for the deferred VCd group. Conclusion The D-VCd regimen (immediate or deferred) had a manageable safety profile consistent with previous studies. Cardiac TEAEs were similar between regimens, and their emergence correlated with the start of VCd. Major cardiac events were associated with underlying disease and baseline risk factors that are quantifiable and monitorable.

Abstract Introduction: HMA monotherapy (HMAm) continues to be the standard of care for HR-MDS. While the addition of VEN to azacitidine (AZA) improved overall survival (OS) and complete remission (CR) rates among older pts with acute myeloid leukemia (AML) over AZA monotherapy, the recently completed phase III VERONA trial of AZA+/-VEN in HR-MDS failed to show an OS benefit for AZA/VEN over AZA monotherapy. Using the icMDS VALIDATE database, we compared outcomes of pts with HR-MDS treated with HMA or HMA/VEN as frontline therapy. Methods: The icMDS VALIDATE database includes over 4000 adult MDS pts who received HMA-based therapy from 32 international centers in 9 countries. For this analysis, we included pts with HR-MDS defined by International Prognostic Scoring System [IPSS] ≥1.5 or IPSS-revised [IPSS-R] ≥4 (at diagnosis or HMA initiation) and treated with HMAm or HMA/VEN as frontline therapy for HR-MDS. We assessed responses based on 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 from any cause. Pts lost to follow-up were censored at the date they were last known to be alive. We used Kaplan-Meier methods to calculate OS and compared OS between different groups using the log-rank test. We used Cox and logistic regression models to adjust for baseline prognostic variables as appropriate. The study was funded by an independent grant from Abbvie. Results: A total of 1907 pts met eligibility and were included (1552 AZA, 221 decitabine, 134 HMA+VEN). 479 pts subsequently underwent allogeneic stem cell transplant (allo-SCT; 430 after HMAm [32.6%]; 49 after HMA/VEN [37.1%]). Our cohort was enriched for pts with adverse disease characteristics including complex karyotype (33.6%) and TP53 mutations (28.7%). Compared to pts treated with HMA/VEN, pts treated with HMAm were more likely to be male (p=0.012), have lower baseline platelet counts (p=0.037), peripheral blood (PB) blasts (p=0.004), or bone marrow blasts (p<0.001), and were less likely to have very high risk IPSS-M (p<0.001), TP53 mutations (p<0.001), or complex karyotype (p=0.020). In unadjusted analyses, the rate of cCR was significantly lower in HMAm treated pts compared to HMA/VEN treated pts (27.7% vs. 48.8%, p<0.001). However, CR rate was not significantly different (11.7% vs. 17.1% for HMAm and HMA/VEN, respectively, p=0.22). After adjusting for age, sex, and IPSS-M, pts treated with HMA/VEN were more likely to achieve cCR compared to HMAm with an odds ratio (OR) of 2.49 (95% CI: 1.56-3.96, p<0.001). When separated by TP53 mutation status, the OR for cCR for HMA/VEN vs HMAm was 4.17 (95%CI: 2.14-8.31; p<0.001) and 1.27 (95%CI: 0.54-2.86; p=0.57) for TP53 wild-type and TP53-mutant pts, respectively. In unadjusted analyses, median OS was 17.4 months for HMAm and 19.6 months for HMA+VEN, and OS did not differ significantly by treatment type (p=0.33). For HMAm treated pts, the OS rates at year 1, 2, 3 were 0.65 (95%CI: 0.63-0.67), 0.38 (95%CI: 0.36-0.40), and 0.27 (95%CI: 0.25-0.29), respectively. For HMA/VEN treated pts, the OS rates at year 1, 2, 3 were 0.64 (95%CI: 0.56-0.73), 0.45 (95%CI: 0.36-0.56), and 0.37 (95%CI: 0.27-0.51), respectively. In a multivariate analysis adjusting for age, sex, PB blast, IPSS-M and allo-SCT as a time-varying covariate, treatment with HMA/VEN vs HMAm did not significantly influence OS (hazard ratio (HR) of OS for HMA/VEN vs HMAm: 0.89, 95%CI: 0.69-1.13, p=0.33). When stratified by TP53 mutation status, HR of HMA/VEN vs. HMAm was favorable for TP53 wild-type (HR: 0.47; 95%CI: 0.29-0.74) but not TP53-mutant pts (HR=0.96; 95%CI: 0.66-1.41). Adjusting for other variables in the model, HR for pts who underwent vs. those who did not undergo allo-SCT were 0.65 (95% CI: 0.49-0.85) and 0.36 (95%CI: 0.24-0.53) in TP53 wild-type and mutant patients, respectively. Conclusion: In this large, international retrospective analysis from the icMDS VALIDATE database, HMA/VEN was associated with higher cCR rates—but not CR rates—compared to HMAm among pts with HR-MDS, though we observed no significant differences in OS. In our analysis, clinical benefit from the addition of VEN was most clear in TP53 wild-type pts, and allo-SCT was associated with improved OS regardless of baseline TP53 status. Our analysis was limited by the relatively small number of HMA/VEN-treated pts and heterogeneous real-world treatment patterns.

Abstract Background: Systemic AL amyloidosis is an incurable disorder caused by misfolded light chain fibrils. Survival is determined by the extent of cardiac involvement and response to therapy. Mayo 2012 (stage I-IV) and European modified Mayo 2004 (stage I-IIIB) prognostic scores were developed in a historic treatment era, prior to widespread bortezomib and daratumumab use. These no longer discriminate those with the poorest outcomes. We presented a new model sub-stratifying IIIB into a high risk, ‘IIIC’ group, incorporating longitudinal strain (LS) to the European modified score (IIIC: LS >-9% + NT-proBNP >8500ng/L + high-sensitivity troponin T [hs-TnT] >50ng/L) in the bortezomib-era (2015-2019) last year (Khwaja et al, ASH 2024). Here, we present an independent external validation of the IIIC model in the modern treatment era. Methods: The ‘IIIC model’ was derived from a large real-world cohort of adults from the UK National Amyloidosis Centre (2015-2019). Performance was externally validated across Europe (Greece, Italy, Netherlands, Switzerland), USA (2015-2024) and UK (2020-2024). Survival estimates were generated from diagnosis to death or last follow-up using the Kaplan-Meier method and groups compared using Cox regression (using Stata v18). Stage IIIB and IIIC were defined as follows IIIB: LS <-9%, NT-proBNP >8500ng/L, hs-TnT >50ng/L and IIIC: LS >-9%, NT-proBNP >8500ng/L, hs-TnT >50ng/L, respectively. Stage I, II and IIIa were defined as previously described in the European modification of Mayo 2004 staging system. Results: 2493 patients were analysed from 2015-2024 (derivation, n=573; validation: Europe, n=374, USA n=458, UK, n=1088). In the derivation cohort, LS ≥-9% and standard cardiac biomarkers (NT-proBNP 332ng/L and 8500ng/L and hs-TnT>50ng/L) were selected as independent prognostic factors in a multivariable model. In the European and UK validation cohort (n=1462), median age at diagnosis was 67 years (range 35-95) with 1014 (69%) cardiac and 869 (60%) renal involvement. Median difference in involved and uninvolved free light chain (dFLC) was 181 mg/L (range 0-24933), NT-proBNP 1911ng/L (range 42-70000), hs-TnT 45ng/L (range 3-1221) and LS -14.7% (range -3- -28). In the US cohort median NT-proBNP was 1764 (range 13-71000) and hs-TnT 44 (6-687). Applying the new model staging, the patient stages were across Europe and UK were stage I: 224 (15%), II: 627 (43%), IIIA: 396 (27%), IIIB: 139 (10%) and IIIC: 76 (5%), respectively. 592 (41%) were treated with first-line daratumumab-based regimens. In the US dataset stage I: 103 (22%), II: 176 (38%), IIIA: 131 (29%), IIIB: 48 (10%) and IIIC: 16 (3%), respectively. 234 (51%) were treated with first-line daratumumab-based regimens. At a median follow-up of 30 months (95% CI 28-32) in the European and UK validation cohort, estimated median overall survival (OS) was not reached and 2-year OS was 74% (95% CI 72-77). Median survival for stages I-II, IIIA, IIIB and IIIC were not reached (NR), 67, 31 and 10 months, respectively (p<0.001). Hazard ratios for stage II, IIIA, IIIB, IIIC were 2.01 (95% CI 1.32-3.07), 3.51 (95% CI 2.31-5.35), 5.67 (95% CI 3.60-8.91) and 11.12 (95% CI 6.93-17.87), respectively (p<0.001). This was confirmed in the US cohort with a median survival for respective stages were NR, NR, NR, 8 and 2 months (p<0.001). External validation in the European and UK cohorts exhibited good predictive performance: 12-month calibration slope was 1.00 (95% CI 0.81-1.20, p=0.98), Harrel's C was 0.90 (95% CI 0.76-1.00), Royston's D 1.07, R2D 0.21 (95% CI 0.15-0.28). In 1462 patients with dataset available, stage IIIC discriminated the poorest outcome despite a greater proportion treated with first-line daratumumab v IIIB in the validation cohort (59% v 40%, p=0.008). 12-month OS for IIIC v IIIB was 44% (95% CI 32-55) v 69% (95% CI 60-76), specificity for 12-month OS 97% v 92% and diagnostic odds ratio 6.62 v 2.36. Conclusions: This study validates the new staging system from stage I-IIIC with robust identification of an ultra-poor prognostic group (Stage IIIC) in a contemporarily treated patient cohort. Despite novel therapies, the OS remains <12 month in the IIIC group and also poor in stage IIIB with median OS 31 months compared to a median of >5 years for all other stages. This staging system can be considered as a new standard of care for risk stratification of AL amyloidosis. Novel approaches are required for patients with advanced risk.