Gertz, Morie A.

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<0.001), NYHA Class ≥ III (OR=4.95, p<0.001), dFLC ≥9 mg/dL (OR, 10.18, p=0.023), eGFR <33 mL/min/1.73 m2 (OR=2.7, p=0.026), NT-proBNP >5276 pg/mL (OR=7.69, p <0.001), hs-TnT >70 ng/L (OR=5.88, p<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 >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 <9; 87.5%) and high-risk (score ≥9; 12.5%). The respective cumulative incidence of EM was 6.1% versus 50% (p<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.

Background Multiple myeloma (MM) is a hematological cancer characterized by the proliferation of plasma cells (PC). Progressive disease (PD) criteria are primarily characterized by an increase in (1) serum M-protein (SPEP), (2) urinary M-protein (UPEP), (3) serum free light chains (sFLC), or (4) PC percentage in the bone marrow. An essential aspect of the PD criteria is the requirement for confirmatory results from blood or urine analyses. However, in many cases, patients may be taken off treatment in favor of a new therapy after only one assessment. This can introduce clinical trial endpoint inaccuracies when confirmatory values are missing, resulting in increased censoring and underestimation of the progression rate (if the second assessment is not done). Moreover, in subjects with high tumor burden and rapidly progressing disease, it is often urgent to confirm PD before starting a subsequent line of treatment. This study assessed the necessity of repeating biomarkers to confirm PD if two biomarkers meet the progression criteria. Methods In this retrospective study, between 2002 and 2020, we assessed all consecutive patients with relapsed MM enrolled in any therapeutic clinical trial at Mayo Clinic. We included patients with measurable disease if SPEP and sFLC were available at the time of assessment. Patients required at least two consecutive assessments (by the same method) to be included in our study. PD was based on the IMWG criteria. Relapse characterized by the development of new bone lesions or extramedullary relapse without meeting biochemical progression criteria was an exclusion criterion. Patients starting a new line of treatment after non-confirmed PD were also excluded. Furthermore, patients who did not meet simultaneous progression criteria and had unconfirmed PD (did not meet IMWG criteria at the second assessment) were excluded from the analysis (n=15). The probability of meeting the progression threshold with 1 and 2 consecutive assessments was calculated. We then examined the proportions of patients meeting PD by 2 biomarkers simultaneously at the first assessment. Results We evaluated episodes of treatment among 434 patients enrolled in clinical trials, including 601 episodes: 593 episodes of biochemical confirmed PD and 8 episodes when patients did not progress but who met simultaneous progression criteria at the same time with two different biomarkers. Per measurable disease criteria, MM isotypes were 71.0% IgG, 16.8% IgA, 0.9% IgM, 1.2% IgD, 0.3% biclonal, and 9.8% light chain. According to the standard IMWG response criteria (sequential criteria), 78% and 9% of episodes reached the progression threshold with serum and urine M-components, respectively, with two consecutive assessments. For the FLC, 21% of episodes met the progression criteria. No patients had a second bone marrow examination for confirmation of PD. At the first available assessment, 82%, 19%, and 2% of episodes met progression threshold, respectively, with serum M-protein, urine M-protein, and both (serum + urine M-protein). Additionally, 58%, and 19%, episodes met the progression threshold at the first assessment with FLC and bone marrow examination, respectively. Moreover, 67% of patients with IgA myeloma meet the progression threshold with the total quantitative IgA. With the simultaneous criteria at time of first assessment, 403 episodes meet progression threshold: 45% with SPEP+sFLC (n=269/593), 4% with SPEP+UPEP (n=21/593), 9% with sFLC+UPEP (n=55/593), 11% with BME only (n=66/593), and 0.3% with qIgA +dFLC/UPEP (n=2/593). Thus, among these 413 episodes, which meet progression criteria by 2 simultaneous values at the time of the first assessment, 98% (n=413/(413+8)) of these patients (positive predictive value of the new criteria) subsequently had confirmed progression by sequential value. Conclusions In summary, we showed that the simultaneous criteria allow to identify patients with true progressive disease without overestimating the progression rate of myeloma. Therefore, confirmatory results of progression for relapsed MM patients having two biomarkers meeting criteria of progression at the same time is useless for determining disease progression.

Background: Light chain (AL) amyloidosis is a rare and understudied plasma cell disorder. It is caused by abnormal misfolding of monoclonal immunoglobulin light chains, leading to extracellular deposition of amyloid, ultimately resulting in organ dysfunction and death. Since AL amyloidosis is uncommon, therapies are adapted from the more common plasma cell disorders like multiple myeloma. Daratumumab, a monoclonal antibody targeting CD38, was first tested in several prospective and retrospective studies in AL patients with relapsed refractory disease. The ANDROMEDA study (Kastritis E et al, NEJM 2021) established daratumumab in combination with CyBorD (Cyclophosphamide-Bortezomib-Dexamethasone) followed by daratumumab maintenance as the new standard of care compared to CyBorD alone for newly diagnosed patients. Consequently, daratumumab maintenance has become universally offered to all newly diagnosed AL amyloidosis patients. Notably, there was no second randomization before the initiation of maintenance therapy in ANDROMEDA. Hence, a critical question that remains is whether the superior efficacy observed in the investigational arm of the ANDROMEDA trial is solely a result of the addition of daratumumab during the induction phase or if the maintenance phase contributed to the favorable outcomes in the investigational arm. We hypothesize that a shorter duration of maintenance would prove non-inferior to the standard duration of daratumumab maintenance in patients with AL amyloidosis that have responded to Daratumumab-CyBorD induction. To answer this question we are conducting a pragmatic phase 2 randomized trial assessing the optimal duration of daratumumab maintenance in patients with AL amyloidosis who have responded to Daratumumab-CyBorD induction. Study Design, Patients and Methods: We use broadened eligibility criteria consistent with pragmatic trial design. The estimated total enrollment is up to 96 patients. The main eligibility criteria are patients with biopsy-proven AL Amyloidosis who have completed 6 cycles of Dara-CyBorD-based induction treatment and achieved an adequate response to induction (defined as hematological complete response (CR), hematological very good partial response (VGPR), or hematological partial response (PR) with at least one organ response). Patients in whom bortezomib and/or cyclophosphamide were omitted from induction due to toxicity concerns or adverse effects are allowed. The major exclusion criteria are patients who were concomitantly diagnosed with multiple myeloma based on International Myeloma Working Group (IMWG) criteria. This phase II, open-label, multicenter trial (NCT05898646) randomizes patients who have attained an adequate response to 6 cycles of Dara-CyBorD-based induction in a 1:1 ratio, using a dynamic allocation procedure that balances the marginal distributions of the stratification factors (age, cardiac stage, and t(11;14) status). Randomization is to either single-agent daratumumab maintenance of 6 cycles duration (experimental arm) or 18 cycles of daratumumab maintenance (control arm) (cycle = 28 days). Treatment is allowed to be given at a local facility After completing maintenance treatment, patients will follow up every 3 months for up to 36 months from registration. The primary endpoint of the trial is to evaluate the non-inferiority of a shorter (6 cycles) daratumumab maintenance measured by event-free survival (EFS) compared to the standard maintenance of 18 cycles in newly diagnosed AL amyloidosis who receive 6 cycles of daratumumab-CyBorD based induction. EFS in this study is defined as time from registration to any of the following events: hematological progression, organ progression, subsequent anti-plasma cell therapy in the absence of hematological progression but with persistent organ dysfunction or death, whichever occurs first. Secondary endpoints are depth of hematological and organ response, bone marrow measurable residual disease negativity rate, duration of response, quality of life, and survival. By investigating whether a shorter duration of maintenance is non-inferior to the standard duration, we aim to inform clinical practice and potentially reduce the toxicities associated with prolonged maintenance therapy, including hypogammaglobulinemia, recurrent infections, the need for intravenous gammaglobulin replacement, and financial toxicity.

Introduction: In myeloma, accurate risk stratification remains a challenge due to substantial biological heterogeneity and highly variable survival outcomes. Cross-sectional imaging is commonly obtained at the time of diagnosis, but imaging findings are not currently incorporated into risk stratification efforts in a standardized manner, despite their prognostic significance. Here, we investigate the use of novel image-based prognostic biomarkers obtained by automated image segmentation and radiomics feature extraction using machine learning methods. Methods: We obtained the pre-treatment 18F-FDG PET/CT scans of 443 patients with newly diagnosed myeloma and complete demographic and cytogenetic data (seen at Mayo Clinic between 2005 and 2019). The native DICOM images were pre-processed and subjected to automated image segmentation using nnU-Net (v1.0, inference using a pre-trained hematologic malignancies model). Limitations of this automated segmentation approach include heterogeneity introduced by varying image quality, technical differences related to PET reconstruction, and potential inclusion of non-neoplastic FDG-avid lesions in segmented regions. The quality of the automated image segmentation was evaluated by comparing the radiomics features obtained from ground-truth segmentation (manual lesion segmentation) and model segmentation in a separate cohort of patients with hematologic malignancies (n=72). We selected 42 radiomics features that moderately (r≥0.30, p<0.005, n=23) or strongly (r≥0.50, p<0.001, n=19) correlated between ground-truth (manual) and model (automated) segmentation for further evaluation in myeloma patients. PyRadiomics was used to extract discrete radiomics features for clinical prediction modeling. We evaluated the prognostic significance of tumor size-, shape-, and texture-related radiomics features and compared their predictive power to established prognostic factors (International Staging System [ISS], Revised ISS [R-ISS] stage and high-risk FISH cytogenetics). The outcome of interest was overall survival and the predictive power of competing proportional hazards regression models was assessed using Harrell's C-statistic. For modeling purposes, patients without measurable tumor volume were categorized as having undetectable radiomics features (0 for all features). All radiomics features were median dichotomized for downstream modeling. Forward feature selection and testing for multicollinearity were used to remove redundant features. Select radiomics features were divided into quintiles to generate an additive radiomics risk score and associated risk strata. Results: Median age at diagnosis of the 443 myeloma patients was 63 years (32-91) and 270 patients (62%) were men. After a median follow-up of 2.4 years (95% CI 0.1-7.4), median overall survival was 6.5 years (95% CI 5.5-NR). Most patients had detectable metabolic tumor volume (n=309, 70%) on their pre-treatment 18F-FDG PET/CT scan. Several of the 42 radiomics features were intercorrelated and two features were selected for further investigation based on their independent prognostic significance (forward feature selection). Higher maximum axial tumor diameter (HR 1.90, 95% CI 1.31-2.76, p=0.001) and a lower concentration of low gray-level values in the tumor (HR 1.73, 95% CI 1.20-2.49, p=0.004) were independently associated with overall survival in newly diagnosed myeloma. These associations were independent of age at diagnosis, sex, and R-ISS stage. We devised a simple additive risk score representing the sum of quintiles of the two radiomics features and divided the patients into three risk categories akin to the R-ISS. The predictive power of this radiomics risk score (Harrell's C=0.60) was comparable to the ISS (C=0.59) and the R-ISS (C=0.57). Conclusions: Automated image segmentation and radiomics feature extraction from 18F-FDG PET/CT scans is feasible. This approach yields image-based biomarkers that correlate with results obtained by manual imaging segmentation. Several radiomics features such as tumor size and heterogeneity have independent prognostic significance in newly diagnosed myeloma. These novel biomarkers rival the predictive power of the currently established risk stratification methods and may be used to improve risk stratification in myeloma.

Introduction: Measurable residual disease (MRD) is a well-validated prognostic marker and interim outcomes measure in patients with multiple myeloma (MM). Despite its broad acceptance as a robust prognostic marker, the MRD status is only available down the treatment line, and there is limited information on the markers at diagnosis that can predict achievement of MRD negativity post-transplant. This study explored the relationship between baseline risk factors and post-autologous stem cell transplantation (post-ASCT) MRD status, as well as the combined impact of these baseline factors and post-ASCT MRD status on progression-free survival (PFS) and overall survival (OS). Patients and Methods: We conducted a retrospective, single-center study of patients achieving at least VGPR after ASCT between 01/01/2016 and 12/30/2023, majority (n=814, 98%) received ASCT in the frontline setting. MRD testing was performed between days 60-100 post-transplant using next-generation flow cytometry with a sensitivity of at least 1x10^5 nucleated cells (minimum 2x10^6 cells assessed). Treatment response and disease progression were determined by IMWG criteria. High-risk disease (HRD) was defined as presence of International Staging System ISS stage 3, high lactate dehydrogenase, 1q gain, 17p deletion, or t(4;14) chromosomal abnormalities. We calculated PFS/OS from transplant day 0 to first documented event (progression or death). Categorical variables were compared using chi-square and Fisher's exact tests. Non-parametric tests compared continuous variables, and logistic regression analyses tested associations between clinical/lab variables and MRD status post-ASCT. Time-to-event analyses were performed using Kaplan-Meier and compared using log-rank test. Multivariable analyses were conducted using the Cox regression model. Result: The study cohort included 831 newly diagnosed MM patients. The median follow-up for the cohort was 50 months (95% CI: 48-51). 48% (n=402) achieved MRD negativity (MRD-neg) post-ASCT. Univariate analysis demonstrated that R2-ISS stage, depth of response pre-ASCT, and presence of t(11;14) to be associated with worse MRD-negativity rates. Multivariate analysis revealed that t(11;14) significantly decreased the odds of MRD-negativity (p<0.0001, OR=0.4, 95% CI: 0.3-0.6) and a deeper pre-ASCT response was associated with increase odd of MRD-negativity OR-4.7 (95%CI 3.2-7.4) p<0.0001. Patients with MRD-positive disease post-transplant had an inferior estimated median PFS of 57.6 months (95% CI: 49-69) with a 5-year PFS of 49% (95% CI: 43-56), compared to an estimated median PFS of 83.3 months (95% CI: NA) and a 5-year PFS of 66% in MRD-negative patients (p<0.0001, HR=1.9, 95% CI: 1.5-2.5). Similarly, MRD positivity was associated with an inferior OS [estimated median of 92.6 months (95% CI NA) ,5-year OS 76% (95%CI 72-82) for MRD-pos vs. Median OS NR, 5-year OS 85%(95%CI NA) in MRD-neg; p=0.003, HR=1.69, 95% CI: 1.2-2.38)]. In MRD-neg patients, a baseline bone marrow plasma cells BMPC% >60% was significantly associated with worse PFS (HR=1.9, 95% CI: 1.26-2.99; p<0.01). High-risk disease was not associated with an inferior PFS or OS in patients with MRD-negativity. For MRD-neg patients, estimated median PFS was not reached for those without HRD, 5-year PFS was 66% (95%CI 51-85), compared to 83 months(95%CI 65-NA) for those with HRD, 5-year PFS was 65%(95%CI57-74), p=0.6441. The median OS was not reached in either group (p=0.07). Five-year OS was 94% (95%CI 86-100) in MRD-neg without HRD vs. 81%(95%CI 75-87) with HRD (p=0.07). In MRD-pos patients, median PFS was 81 months (95%CI 58-NA) for those without HRD, 5-year PFS of 59% (95%CI 46-77), compared to PFS of 41 months(95%CI 36-52) for those with HRD ,5-year PFS of 39% (95%CI 31.3-47) , p=0.003. Median OS was not reached in MRD-pos patients without HRD, but it was 59.8 months ( for those with HRD (p=0.0012). Five-year OS was 94% (95%CI 89-99) in MRD-pos without HRD vs. 67%(95%CI 60-74) with HRD (p<0.0001). For every 1 log increase in the residual cell % on MRD testing in MRD-pos patients, the hazard ratio for PFS increased by 42% (p=0.0002, HR=1.42, 95% CI: 1.2-1.7). Conclusion: Patients with t(11;14) have a reduced likelihood of achieving MRD negativity post-ASCT, whereas high-risk cytogenetics did not impact MRD-negativity rates. Achievement of MRD negativity post-ASCT mitigates the impact of high-risk characteristics.

Background: Multiple Myeloma (MM) is predominantly a disease of older adults. However, older patients vary widely in physiological status and treatment tolerance. The simplified frailty index (Facon 2020) incorporates age, ECOG performance status, and comorbidities (Charleston Comorbidity Index [CCI]) to classify patients as frail or non-frail. While frailty is associated with increased toxicity with conventional systemic therapies, its impact on outcomes of older patients treated with bispecific antibodies (BsAbs) has not been established. Thus, we conducted a retrospective study to evaluate the efficacy and toxicity of BsAbs in older patients based on frailty. Methods: This is a single institution study. We included patients with MM ≥65 years who initiated treatment with a BsAb at Mayo Clinic in Rochester, MN from August, 2018 to January, 2024. Patients who received a BsAb on trial or as standard of care were included. For patients who received 2 different BsAbs at different timepoints, we included the first treatment only. We grouped patients into frail and non-frail based on the simplified frailty index (score ≥2 = frail). We evaluated the overall response (ORR) and ≥very good partial response (VGPR) rates, progression-free (PFS) and overall (OS) survival, early mortality (within 90 days) including early non-relapse mortality (NRM), and toxicities including cytokine release syndrome (CRS), immune effector cell associated neurotoxicity syndrome (ICANS) and healthcare utilization. P values were insignificant (>0.05) unless otherwise stated. PFS and OS were calculated from the day of BsAb start. Results: A total of 99 patients age 65-89 years were included. The products used were teclistamab (N=43), talquetamab (N=2), and investigational agents (N=54); 67% were ≥70 and 29% were ≥75 years; 39% were female, 95% were non-Hispanic White and 4% were Black/African American. Seventy patients (71%) were considered frail and 29 (29%) were non-frail. At the time of BsAb start, a higher proportion of frail patients had platelets <75 x 10^9/L (30% vs 8%, P=0.04). Otherwise, there was no significant difference between frail and non-frail patients in age (median: 72 vs 70), hemoglobin <8 g/dL (19% vs 12%), absolute neutrophil count <1 x 10^9/L (6% vs 8%), presence of high-risk FISH (70% vs 60%), ISS stage 3 (32% vs 41%), high LDH (58% vs 61%), presence of extramedullary disease (39% vs 25%), serum creatinine ≥2 mg/dL (15% vs 8%), bone marrow plasma cell% (20% in both), triple- (83% vs 90%) and penta-class refractoriness (63% vs 48%), number of prior lines of therapy (median: 6 in both), prior exposure to BCMA-directed therapy (24% vs 21%, P=0.80) and prior autologous stem cell transplant (73% vs 86%). Step-up dosing was used in 81% vs 48% of patients (P=0.001), and treatment was initiated in the outpatient setting in 46% vs 28% (P=0.12) in frail and non-frail patients, respectively. The median follow-up was 1.9 (95%CI: 1.0-2.3) years. There was no significant difference between frail and non-frail patients in ORR (52% vs 62%), ≥VGPR (46% vs 48%), 1-year PFS (36% vs 48%, P=0.26), or 1-year OS (57% vs 61%, P=0.30), respectively. Age and CCI alone were not associated with PFS or OS, but ECOG >1 was associated with decreased PFS (hazard ratio: 3.1, P=0.001) and OS (hazard ratio: 3.1, P<0.001). There was no significant difference between frail vs non-frail patients in grade 3/4 thrombocytopenia (39% vs 17%, P=0.06), grade 3/4 neutropenia (27% vs 35%), total days of hospitalization (median: 8 vs 5, P=0.35), number of unplanned admissions in 6 months (median: 1 in both), or total hospital days for unplanned admissions (1 vs 2 days). There was no significant difference between frail and non-frail patients in early mortality (23% vs 10%, P=0.17), including early NRM (4% in both), CRS (59% vs 66%), grade 3-4 CRS (3% vs 7%), or CRS recurrence (21% vs 10%). ICANS occurred in 5 (9%) frail patients and 1 non-frail patient (grade 2); among frail patients, grades were: 1 in 3 patients, 3 in 1 patient, and 4 in 1 patient. Similarly, there was no significant difference in CRS/ICANS between the 2 groups when patients with and without step-up dosing were analyzed separately. Conclusion: Frailty, defined using the simplified frailty index, was not significantly associated with inferior efficacy or increased toxicity with BsAb therapy among older patients with MM. Poor performance status predicted inferior PFS and OS, while age and comorbidity scores did not.

Background: A deeper understanding of the cytogenetic features has enabled robust risk stratification for patients with newly diagnosed multiple myeloma (NDMM). However, heterogeneity persists in the currently available prognostic tools and there is further room for personalization. We assess the utility of PC-PRO, a test to measure the proportion of monotypic plasma cells in the synthetic phase (S-phase) of cell cycle, as a prognostic marker for NDMM. Methods: Patients with active MM diagnosed between January 2013 and January 2023 with a flow cytometry-based S-phase assessment at diagnosis were included. Flow cytometric immunophenotyping was performed using the following antibodies: CD19, CD38, CD45, CD138, cytoplasmic kappa and lambda immunoglobulin, and DAPI (4',6-diamidino-2-phenylindole). The percentage of plasma cells in S-phase was determined by measuring the proportion of cells with DNA content of the monotypic plasma cells between the G0/G1 and G2/M peaks. Plasma cell clonality was detected through demonstrating CD38 and CD138 positivity along with immunoglobulin light chain restriction, abnormality of CD19/ CD45 expression and/or ploidy difference by DAPI staining. High-risk cytogenetic abnormalities (HRCA) by FISH were defined as follows: presence of deletion 17p (del17p), t(4;14), t(14;16), t(14;20), 1q gain/amplification, 1p deletion (when available). Additionally, the second iteration of the revised ISS (R2-ISS), incorporating both laboratory and cytogenetic features as well an adaptation of the recently proposed International Myeloma Working Group (IMWG) Classification for high-risk disease, was utilized for risk stratification. All time-to-event analyses were performed using the Kaplan Meier method and compared using the log-rank test. Univariable and multivariable Cox proportional hazards analyses were performed to assess the independent prognostic impact of S-phase. Results: A total of 823 patients were included in the study. The median follow-up was 6 years [95% Confidence interval (CI): 5.5-6.3 years] and estimated median overall survival (OS) was 8.3 years. The median S-phase value for the cohort was 0.8 % (interquartile range: 0.5-1.4%), with 135 (16%) patients harboring an S-phase of ≥2% at diagnosis. Applying the R2-ISS prognostic model to our cohort, 11% (79/706) patients were stratified to the R2-ISS high-risk cohort; 93 patients (out of 788, 12%) had 2 or more HRCA at diagnosis. Patients with a S-phase ≥2% at diagnosis had a median OS of 3.9 years (95% CI: 2.9-5.7) vs. 9.2 years [95% CI: 7.9-not reached (NR)] for patients with a S-phase <2% [Hazard ratio (HR): 2.2 (95% CI: 1.7-2.8), p<0.0001]. The median OS was inferior for cohorts with an increasing S-phase value: S-phase of 0.1-1%: HR: 1 (standard), S-phase 1.1-3%: HR 1.7 (95% CI: 1.3-2.1), S-phase >3%: HR 3.0 (95% CI: 2.2-4.1)]. On a multivariable analysis including S-phase ≥2%, age at diagnosis of MM (>65 years) and R2-ISS high-risk status, S-phase ≥2% was an independent predictor of inferior OS [hazard ratio (HR) 1.9 (95% CI: 1.4-2.6), p<0.0001]. Age >65 years [HR 1.9 (95% CI: 1.5-2.5), p<0.0001] and R2-ISS high-risk status [HR 1.8 (1.3-2.6), p=0.001] were also independent predictors of OS. Within the sub cohort of patients with 2 or more of the listed high-risk cytogenetic features (n=93, 12%), a S-phase ≥2% (n=24) was associated with a worse median OS of 1.6 years (95% CI: 0.7-NR) vs. 6.2 years (95 % CI:3.3-NR) for S-phase <2% (p=0.002). Conclusion: Flow cytometry-based determination of the proportion of monotypic plasma cells in S-phase is an easy-to-study and powerful prognostic tool for NDMM. A S-phase of ≥2% at diagnosis is a predictor of OS independent of age and R2-ISS high-risk stage. An S-phase of ≥2% was able to identify a distinct group with markedly inferior outcomes even within the sub cohort of patients with 2 or more high-risk cytogenetic features.

Background: TP53 mutations (TP53mut) are highly prevalent in therapy-related myeloid neoplasms (t-MN) compared to de novo MN (35-40% vs 7-13%) and are associated with a poor outcome. Understanding the risk factors involved in the pathogenesis of TP53mut t-MN is critical to prevent its development. Methods: We characterized t-MN cases by examining primary cancer type vs autoimmune disease diagnosis vs solid organ transplantation, treatment modality, and latency (interval between primary cancer/disease and t-MN diagnosis) to identify patient and disease-related factors associated with TP53mut t-MN. Allelic loss of TP53mut MN was defined according to International Consensus Classification (ICC) criteria (Arber et al., Blood 2022). Results: Of 587 t-MN patients, 33% (n=194) had acute myeloid leukemia (t-AML) and 67% (n=393) had myelodysplastic syndrome (t-MDS, blasts<20%). Primary diagnosis comprised of 243 (41.6%) solid cancers and 300 (51.4%) hematological malignancies, while 7% (n=41) of t-MN cases had autoimmune disease or underwent solid organ transplant. Overall, 94 (16.1%) patients received prior radiotherapy (RT) alone and 75.6% (n=444) received chemotherapy (CT) with/without RT. 109 patients (18.7%) underwent autologous stem cell transplant (ASCT). The median latency from primary diagnosis to t-MN was 83.2 months (IQR 41.3, 153.2), and there was a trend towards shorter latency in t-AML compared to t-MDS (70.5 vs 85.8 months; P=0.07). Of the t-MN patients, 280 (47.7%) harbored TP53mut, which was associated with significantly poorer survival compared to wild-type (TP53wt) t-MN (9.7 vs 21.9 months; P <0.001). In contrast to TP53wt (59.0% vs 41.0%), the majority of TP53mut t-MN presented with t-MDS vs t-AML (75.7% vs 24.3%; P <0.001). According to ICC criteria, multi-hit MDS (n=131; 47.8%) was the most common entity, followed by AML (n=68; 24.8%), MDS/AML (n=34; 12.4%), and single-hit MDS (n=8, 2.9%). Poor prognostic karyotype changes e.g., del 5q, del 7q, complex karyotype and monosomal karyotype, were more prevalent in TP53mut compared to TP53wt t-MN. Co-mutations in other genes were enriched in TP53wt t-MN. As TP53mut t-MN is associated with a dismal outcome, we assessed the factors associated with its development. There were no significant differences in median age at primary cancer/disease diagnosis (59.0 vs 59.9 years; P=0.4) or gender (females 43.3% vs 39.3%; P=0.3) between TP53mut and TP53wt t-MN. However, TP53mut patients were older at t-MN diagnosis (69 vs 67.4 years; P=0.05). Correlations between gene mutations and prior malignancies revealed a significant association between TP53mut and hematological primary cancers (odds ratio [OR] 1.6; P=0.006), especially multiple myeloma (MM, OR 4.9; P<0.001) and lymphoproliferative disease (LPD, OR 2.0; P=0.013). Among solid cancers, head and neck malignancies were significantly associated with increased risk of developing TP53mut t-MN (OR 7.7; P=0.01). Compared to RT alone, ASCT (OR 2.2; P=0.004) and CT (OR 2.0; P=0.008) were associated with an increased risk of TP53mut t-MN. Recent studies indicate that CT/RT confer a selective advantage to preexisting TP53mut hematopoietic stem and progenitor cells, allowing clonal expansion/evolution and progression to t-MN. We hypothesized that TP53mut t-MN with high-risk disease features is a function of TP53mut clonal expansion/evolution rate and would predict latency between primary cancer and t-MN. Indeed, the latency between primary cancer and t-MN diagnosis was longer in TP53mut (87.8 months, IQR 45.5, 154.1) compared to TP53wt (74.7 months, IQR 37.5, 146.9 months) t-MN (P=0.05). Interestingly, 54% and 29% of TP53mut t-MN had a latency of ≥5 and ≥10 years, respectively. There were no correlations between latency and TP53 variant allele frequency (VAF) (r=0.38 and P=0.7) or between TP53mut t-MDS and t-AML (85.2 vs 109.3 months; P=0.9). Together, latency between primary cancer and t-MN was not associated with TP53mut t-MN phenotype, VAF or other poor-risk disease features. Conclusion: Hematological malignancies, especially MM and LPD treated with high-dose CT, were strongly associated with TP53mut t-MN development, highlighting the importance of careful and ongoing screening in this population. Also, the long latency of TP53mut t-MN provides an opportunity to devise effective surveillance strategies and preventative interventions long before TP53mut t-MN development.

Background and Methods: IEC-HS is a hyperinflammatory state with high morbidity and mortality. Effective interventions to reverse the process early in the clinical course may be critical to improve outcomes. We previously examined cytokine differences between IEC-HS and other secondary hemophagocytic lymphohistiocytosis, and found significant differences in the patterns and outcomes.(1) This study examines cytokine profiles (CP) of patients treated with CAR-T from 9/2019 to 3/2024 who developed CRS, MAS-L and IEC-HS. Demographics and lab results were compared among the three groups and correlated with outcomes. Results: CP was tested in 113 of 366 CAR-T patients: 74 with CRS, 19 with MAS-L, and 20 with IEC-HS. The racial distribution was 93% White/Caucasian, 2% Black or African American, 1% Asian, 1% Native American and 3% other or unavailable. No differences were seen in demographics between groups except a higher percentage of patients with ECOG performance status ≥2 in IEC-HS (p=0.037). Incidence of IEC-HS by disease: 3.6% (7/193) in lymphoma, 5% (8/159) myeloma and 28.5% (4/14) B-acute lymphoblastic leukemia (p=0.0002). Incidence of IEC-HS by CAR-T product: 3% (4/150) in Axi-cel, 23% (6/26) in Brexu-cel, 8% (1/13) in Tisa-cel, 5% each (3/60) in Cilta-cel and Ide-cel, and 0/17 in Liso-cel (p=0.001). Prior to lymphodepletion, labs were already different among the CRS, MAS-L, and IEC-HS groups: hemoglobin (g/dL: 11.1, 9.6, 8.45); platelets (x109/L: 168, 116, 52.5); ferritin (µg/L: 115, 946, 1944). CP was started when patients needed a second dose of tocilizumab or concern for developing MAS-L/IEC-HS, and continued daily until clinical improvement or resolution of inflammatory state. Tocilizumab and dexamethasone use were similar across groups. Other therapies used were vasopressors (3%, 10.5%, 45%; p<0.0001), Methylprednisolone (20%, 31.6%, 50%; p=0.027), Anakinra (12%, 63%, 85%; p<0.0001), Siltuximab (9.5%, 16%, 30%; p=0.06), Basiliximab (30% of IEC-HS), and continuous veno-venous hemofiltration (30% of IEC-HS). Among the first CP, the CRS group had lower levels of cytokines (in pg/mL) compared to MAS-L and IEC-HS groups: TNF (31, 62.9, 47.7), IL-10 (29.3, 97.7, 169), IL-18 (794, 1353, 2011), IFN-gamma (74, 281, 250), MCP-1 (689, 2722, 2485.5), MIP-1 alpha (220, 234, 247.5), IL-6 (>315: 45%, 79%, 70%), soluble IL-2R alpha (>4000: 45%, 84%, 70%). The percentage of patients who received anakinra before CP1 were 4% (CRS), 21% (MAS-L) and 25% (IEC-HS) (p=0.007). IL-1 beta was below threshold among all patients who received anakinra in CRS and MAS-L and 75% in IEC-HS, suggesting rapid and effective IL-1 suppression by anakinra except in IEC-HS. Cytokines trends 24 hours and 48 hours after the first CP differed between MAS-L and IEC-HS. MAS-L had decreased TNF (62.9, 40.4, 18.5) and MCP-1 (2722, 355, 104) while these cytokines remained elevated or increased in IEC-HS (TNF: 47.7, 105.5, 62.6; MCP-1: 2486, 2276, 1585). IL-18 was minimally elevated in MAS-L (1353, 1955, 3068) and significantly increased in IEC-HS (2011, 2420, 4048). Notably, CP2 and CP3 levels of these cytokines in IEC-HS were statistically significantly higher than corresponding CPs among CRS and MAS-L. In addition, patients who died with persistent E. faecium bacteremia had higher IL-18 on CP3. Infections occurred in 43%, 58%, and 85% respectively (p=0.002), including E. faecium bacteremia (3%, 5%, 35%; p=0.0004), CMV viremia (30% of IEC-HS patients vs. 11% of non-IEC-HS; p=0.025), and invasive fungal infections (15% of IEC-HS patients; p=0.0001). Between the IEC-HS and non-IEC-HS groups, day 100 non-relapse mortality was 35% vs. 0 (p<0.0001), day 100 all-cause mortality was 45% vs. 3% (p<0.0001), and E. faecium bacteremia-related deaths were 50% vs. 1% (p<0.0001). Conclusions: CRS, MAS-L andIEC-HS are known complications of CAR-T. Cytokine-directed therapy can modify the cytokine milieu and control the inflammatory process. However, excess immunosuppression may result in life-threatening infections. Further studies are needed to identify optimal biomarker-guided immunosuppressive strategies to control the inflammatory cascade, while avoiding excess immunosuppression. References: 1. Leung, Nelson, et al. “Outcomes of patients who received CAR T cell therapy and developed IEC-HS treated with cytokine directed therapy.” (2024): 7516-7516.

Background In 2014, the IMWG updated the criteria for diagnosing multiple myeloma (MM) and added three additional criteria to the traditional CRAB criteria. The new criteria called the SLiM criteria, include clonal bone marrow plasma cells ≥60%, involved to uninvolved free light chain ratio (rFLC) ≥100 (involved FLC must be ≥ 100 mg/L), and > one focal lesion on MRI studies (each lesion ≥ 5 mm). These criteria were deemed myeloma-defining events (MDE) in the absence of CRAB criteria. Autologous stem cell transplantation (ASCT) has been used for treating MM for over three decades and is safe and efficacious. We report on outcomes of outpatient ASCT in a cohort of patients with MM where therapy was initiated solely based on SLiM criteria. Methods We conducted a retrospective study of all patients diagnosed with MM based on SLiM criteria at Mayo Clinic, Rochester, MN. We compared this cohort to a matched cohort of newly diagnosed MM patients whose MDE was CRAB and who underwent an ASCT. For every patient whose MDE was SLiM, we matched two patients whose MDE was CRAB. The matching was done by age, gender, and melphalan dose. Results Between 2013 and 2022, 30 patients received an ASCT due to SLiM criteria at Mayo Clinic, Rochester (Durie Salmon Stage IA). The median age of our cohort was 63 (range 46-75) years, and 60% had an ISS of 1. Seventeen percent of the cohort was treated with DVRd induction. The median time from diagnosis to ASCT was 6.5 months (IQR 6-7), and all but one received full intensity conditioning with melphalan 200 mg/m2. 53% of patients completed the ASCT without requiring hospitalization, and 47% (n=14) of patients required hospitalization with a median duration of hospital admission of 6 days (IQR 5-14). Bacteremia was confirmed in 7 patients (23%). The matched cohort included 60 patients. Baseline characteristics were similar, with the exception of lower hemoglobin levels in the control group, as expected (13.1 vs 12, P=0.0017). No differences were seen in the number of cells collected (3.4 vs 3.67 X106 cells/kg, P=0.19) or the use of Plerixafor (80% vs 78%, P=0.8). The SLiM cohort had a shorter median time to neutrophil (15 vs 16 days, P=0.049) and platelet (15 vs 17 days, P=0.0004) engraftment. Similar hospitalization and bacteremia rates were seen. The overall response rate was 100%, with a complete response or better (sCR/CR) seen in 30% of patients. The matched cohort had an ORR of 98%, with sCR/CR of 37%. The MRD- rate was the same in both groups. More patients in the SLiM cohort achieved VGPR (50%) than in the CRAB cohort (27%). None of the patients died within 100 days of transplant. The 36-month OS was 100% in the SLiM group and 93.3% in the control group (95% CI 83.1%-97.4%), with a trend towards higher OS in the SLiM cohort (P=0.065). The 36-month PFS was 91.61% in the SLiM cohort (95% CI 69.93-97.87%) and 65.95% in the control group (95% CI 52.31%-76.53%). There was no difference in the PFS between the cohorts (P=0.414). Conclusion ASCT is efficacious and safe in MM patients transplanted only due to SLIM criteria. Improved MRD- and longer PFS were not seen despite lower ISS stage disease in the SLiM group.