Bazarbachi, Abdul Hamid

ABSTRACT Systemic AL amyloidosis is a clonal plasma cell dyscrasia, where toxic free light chains (FLCs) lead to vital organ damage, with risk of early mortality despite effective therapies. Notably, there is a paucity of data on the incidence and predictors of early mortality in the daratumumab (Dara) era. We conducted a multi‐center retrospective cohort study to develop and validate a risk‐prediction model for early mortality (all‐cause death within 6 months) in patients treated with Dara‐based frontline regimens. We used univariate analysis to identify covariates for a logistic regression model predictive of 6‐month mortality and generated a clinical risk score. Among 339 patients across eight centers, 36 (10.6%) experienced early mortality. Multivariate analysis identified four independent predictors: NT‐proBN P > 5300 pg/mL (odds ratio [OR] 3.83, p = 0.006), A ge > 75 years (OR 2.96, p = 0.073), absence of t(11;14) on C ytogenetics (OR 3.0, p = 0.022), and E COG performance status (OR 1.72 per unit increase, p = 0.044). The resulting PACE score stratified patients into three risk groups with a 6‐month mortality of 1.2% (low‐risk), 11.7% (intermediate‐risk), and 50.0% (high‐risk). The PACE score demonstrated superior discrimination (C‐index 0.78) for early mortality compared to Mayo 2004 (0.69) and Mayo 2012 (0.55) staging systems. External validation confirmed robust discrimination (C‐index 0.73) with corresponding 6‐month mortality rates of 4.2%, 15.25%, and 37.04% across respective risk groups. The PACE score provides a clinically applicable tool for early mortality risk stratification in AL amyloidosis patients receiving Dara‐based therapy, and will enable improved patient counseling, clinical trial design, and identification of ultra‐high‐risk patients requiring intensive monitoring and novel therapies.

Abstract Rapid and profound reduction of free light chains (FLCs) improves outcomes in AL amyloidosis; however, early FLC kinetics with daratumumab‐based frontline therapy remain undefined. We retrospectively analyzed 315 patients treated with daratumumab–bortezomib–cyclophosphamide–dexamethasone (Dara–VCd) or Dara–Vd at eight centers. Involved FLC (iFLC), the difference between iFLC and uninvolved FLC (dFLC), and hematologic response (≥very good partial response [VGPR]) were assessed at baseline and at 1, 3, and 6 months, and correlated with light chain isotype, disease burden (bone‐marrow plasma‐cell percentage [%BMPC], baseline dFLC), and cytogenetics. Hematological ≥VGPR increased from 49.8% at 1 month to 66.0% at 3 months. The kappa isotype showed slower responses, with higher iFLC/dFLC and lower ≥VGPR at each time point compared to lambda. Higher %BMPC or baseline dFLC predicted persistently elevated iFLC/dFLC and reduced ≥VGPR. The t(11;14) translocation was associated with lower baseline FLC but similar subsequent kinetics. BMPC < 10% and dFLC < 18 mg/dL independently predicted early ≥VGPR (in ≤1 month). Early ≥VGPR conferred superior hematologic event‐free survival (heme‐EFS) and overall survival (OS) versus later responders (P < 0.001). At a 3‐month landmark, achieving dFLC < 1 mg/dL further stratified prognosis, conferring longer heme‐EFS and OS (P < 0.01). Frontline Dara‐based therapy elicits rapid, deep responses in AL amyloidosis; early ≥VGPR (within 1 month) and dFLC < 1 mg/dL by 3 months predict durable EFS and OS, whereas higher baseline disease burden delays hematologic response.

Background: Despite substantial improvements in early mortality (EM) for patients with systemic light chain amyloidosis (AL), rates remained high in the bortezomib-era, at approximately 25% (Muchtar et al. Blood. 2017). However, the therapeutic landscape in AL amyloidosis has changed with the ANDROMEDA trial, which led to the approval of daratumumab in combination with bortezomib, cyclophosphamide, and dexamethasone (Dara-VCd) in the frontline setting. The incidence and predictors of EM in the context of daratumumab-based frontline therapy have not been studied. Methods: We performed an international multicenter retrospective cohort study of all consecutive patients with newly diagnosed AL treated with frontline Dara-VCd or Dara-Vd, and followed until 12/31/2023. EM was defined as death from any cause within 6 months of treatment initiation. Our primary objective was to identify the rate and significant predictors of EM. Univariate logistic regression was used to identify significant predictors of EM, which were then included in a multivariate logistic regression model. The receiver operator characteristic (ROC) analysis was used to determine the best threshold values that discriminated EM rates for the following continuous variables: age, dFLC (involved-uninvolved), eGFR, NT-proBNP, albumin, and high-sensitivity Troponin-T (hs-TnT). Other variables tested in univariate analysis were the following: ECOG performance status, NYHA functional class, sex, race, light chain isotype, percent bone marrow plasma cells, status of the following cytogenetic abnormalities-t(11;14), +1q, hyperdiploidy, del(13q), high-risk translocations, and del(17p), and the number of organs involved (2 vs 1). To build the clinical prediction score, each variable was weighted according to the β coefficient (natural logarithm of odds ratio) obtained from the multivariable regression. The β coefficients were rounded to the nearest 0.5 and multiplied by 2 to obtain an even number. Results The study cohort included 335 AL patients treated with daratumumab-based frontline therapy (92.2% Dara-VCd, 7.8% Dara-Vd), with all surviving patients having at least 6 months of follow-up. The median age at diagnosis was 66.5 years (range, 59.4 - 71.3), and 6.7% (n = 22) were Non-Hispanic blacks. Median dFLC at diagnosis was 22.91 mg/dL (range, 0.2-1093.4), and median NT-proBNP was 2415 pg/mL (range, 13-70,000). Mayo 2004 stages IIIA/IIIB represented 44% of the total cohort, with 17% having ECOG ≥ 2 and 25.4% having NYHA Class III/IV symptoms. The cumulative incidence of EM was 10.7%, with the incidence in patients with Mayo 2004 stage I, II, IIIA, and IIIB being 0%, 8%, 12.5%, and 25% respectively. On univariate analysis with unadjusted odds ratio (OR), the following variables significantly predicted EM: Age ≥ 75 (OR=2.8, p=0.013) ECOG ≥ 2, (OR 4.9, p&lt;0.001), NYHA Class ≥ III (OR=4.95, p&lt;0.001), dFLC ≥9 mg/dL (OR, 10.18, p=0.023), eGFR &lt;33 mL/min/1.73 m2 (OR=2.7, p=0.026), NT-proBNP &gt;5276 pg/mL (OR=7.69, p &lt;0.001), hs-TnT &gt;70 ng/L (OR=5.88, p&lt;0.001), and absence of t(11; 14) (OR=2.33, p=0.041). These variables were entered into multivariate regression, except for ECOG and NYHA, which were combined to create a single variable (values ranging from 0-8), and hs-TnT was dropped due to substantial missing data as centers used different troponin assays. NT-proBNP was rounded to 5300 pg/ml for ease of clinical application. Based on the multivariate analysis, the following scores were assigned to each variable: Age ≥75 (2.0), ECOG+NYHA (1.0 x combined score), NT-proBNP &gt;5,300 pg/ml (2.0), and absence of t(11;14) (3.0). This led to a score ranging from 1-15, and two risk-groups: low-risk (score &lt;9; 87.5%) and high-risk (score ≥9; 12.5%). The respective cumulative incidence of EM was 6.1% versus 50% (p&lt;0.001). The c-index of the model was 0.725 (95% CI, 0.676-0.774). Conclusion: Using variables that are readily available in the clinic, we have developed a two-tiered risk-prediction model for EM in AL amyloidosis in the context of daratumumab-based frontline therapy. The model needs to be externally validated in an independent dataset.

Abstract Isocitrate dehydrogenase (IDH) 1 and 2 mutations occur in 20% of acute myeloid leukemia (AML). Patients with AML carrying IDH1-2 mutations have a similar prognosis compared to patients without these mutations (DiNardo et al, AM J H, 2015). However, the impact of IDH1-2 mutations on patients with AML undergoing allogeneic hematopoietic stem cell transplantation (allo-HCT) is not well known. In this study, we investigate the prognostic impact of IDH1-2 mutational status on AML patients undergoing alloHCT in complete remission (CR). In this retrospective registry-based analysis, we identified 710 consecutive adult patients (46.2% female; median age: 58.5 years [range, 18-78]) with AML undergoing allo-HCT in CR between 2015 and 2019 at 85 EBMT participating centers. Cord blood, ex-vivo graft manipulated transplants, and patients with favorable cytogenetics were excluded. Median follow-up was 15 months [95% CI 13.4-16.6]. Patients were categorized based on IDH1-2 mutational status, with 300 (42%) mutated and 410 (58%) wild type. Six hundred and fifty-two (92%) and 58 (8%) patients had de novo and secondary AML, respectively, and 141 (20%) patients had poor-risk cytogenetics. IDH1-2 mutation was positively correlated with NPM1 mutation (40% in IDH1-2 mutated vs 27% in wild type, p=0.0001) and more frequently encountered in middle-aged patients (p=0.01). No correlation was noted between IDH1-2 and FLT3 mutation or other patient characteristics. Minimal residual disease (MRD) data was available for 344 patients, 53% of which were MRD-negative at transplant in both groups. Six hundred and twenty-three (88%) and 87 (12%) patients were in first and second CR at time of transplant, respectively. Patients received grafts from a matched sibling (24%), unrelated (62%), or haploidentical (14%) donor, and myeloablative conditioning (MAC) was used in 42%. Ninety-three percent of the patients received peripheral blood as the stem cell source. At day 180, the cumulative incidence of grade II-IV acute graft-versus-host disease (aGVHD) was significantly lower in IDH1-2 mutated compared to wild-type patients (22% vs 33%, p=0.002). No differences in chronic GVHD rates were noted between the 2 groups (39% vs 40%, p=0.87). The 2-year cumulative relapse incidence (RI) was significantly lower and the GVHD-free, relapse-free survival (GRFS) was also improved in IDH1-2 mutated compared to wild-type patients (14.4% vs 27%, p=0.001 and 47% vs 39%, p=0.006, respectively). This led to an improved leukemia-free survival (LFS) in IDH1-2 patients (69% vs 59%, p=0.01), however, it did not translate into an overall survival (OS) difference. No significant difference was noted in non-relapse mortality (NRM) between the 2 groups (17% vs 14.2%, p=0.26). These findings were confirmed in multivariate analysis. In fact, IDH1-2 mutation was associated with significant improvement in RI (hazard ratio [HR]=0.4 [95%CI 0.25-0.64], p=0.0001), LFS (HR=0.7 [95%CI 0.51-0.95], p=0.022), aGVHD II-IV (HR=0.63 [95%CI 0.45-0.87], p=0.005) and GRFS (HR=0.69 [95%CI 0.54-0.89], p=0.004). Conversely, the presence of adverse cytogenetics and undergoing allo-SCT in second CR increased the RI (HR=2.29 [95%CI 1.46-3.61], p=0.0003 and HR=2.84 [95%CI 1.64-4.91], p=0.0002, respectively) and were associated with a shorter LFS (HR=1.67 [95%CI 1.18-2.36], p=0.004 and HR=1.61 [95%CI 1.06-2.44], p=0.025) while reduced intensity (RIC) conditioning had a worse impact on OS compared to MAC (HR=1.56 [95%CI 1.07-2.29], p=0.022). Additionally, in the subgroup of patients with available MRD data, MRD positivity at transplant significantly increased RI (HR=2.15 [95%CI 1.09-4.23], p=0.027) with no impact on survival. In conclusion, our data suggest that the presence of IDH1-2 mutations acts as an independent prognostic factor and is associated with improved outcome in patients with AML in CR undergoing allo-HCT. Indeed, patients with IDH1-2 mutations had significantly lower rates of RI and aGVHD, which translated into improved LFS and GRFS. Nevertheless, patients with MRD positivity at time of transplant had significantly increased RI. Further studies investigating allo-HCT outcomes in IDH1-2 mutated patients with AML in the era of IDH inhibitors (both in the pre- and post-transplant setting) would help to further define the impact of these mutations in this setting and thus optimize an individualized treatment approach. Disclosures Labopin: Jazz Pharmaceuticals: Honoraria. Esteve: Abbvie: Consultancy; Pfizer: Consultancy; Astellas: Consultancy; Novartis: Research Funding; Novartis: Consultancy, Research Funding; Bristol Myers Squibb/Celgene: Consultancy; Jazz: Consultancy. Kröger: Novartis: Research Funding; Riemser: Honoraria, Research Funding; Sanofi: Honoraria; Neovii: Honoraria, Research Funding; Jazz: Honoraria, Research Funding; Gilead/Kite: Honoraria; Celgene: Honoraria, Research Funding; AOP Pharma: Honoraria. Blaise: Jazz Pharmaceuticals: Honoraria. Socie: Alexion: Research Funding. Ganser: Jazz Pharmaceuticals: Honoraria; Novartis: Honoraria; Celgene: Honoraria. Yakoub-Agha: Jazz Pharmaceuticals: Honoraria. Bazarbachi: Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Roche: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Amgen: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Abbvie: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Hikma: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Pfizer: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Astra Zeneca: Membership on an entity's Board of Directors or advisory committees.