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Introduction: Ven is a BCL2 inhibitor that has shown clinical efficacy in RRMM patients (pts) particularly those that harbor t(11;14). Ven has been evaluated in clinical trials as a single agent, in combination with dexamethasone (dex), immunomodulatory drugs (IMiD), proteasome inhibitors (PI), and anti-CD38 monoclonal antibodies (MAb) yet its place in the therapeutic landscape remains in question. In this retrospective analysis, we aim to evaluate the real-world efficacy of Ven-based regimens in RRMM pts treated outside of a clinical trial across the 3-site MCCC. Methods: We retrospectively analyzed the medical records of pts with RRMM treated with Ven-based regimens between January 2015 and October 2023 at the MCCC. Refractoriness was defined by progression on or within 60 days of stopping treatment. Categorical variables were compared with Chi-square tests and continuous variables were compared with t-tests. Outcomes were estimated using the Kaplan-Meier method and curves were compared between the groups using log-rank tests. Results: 83 pts were included in the analysis. The median age was 71 (39-93), 63% were male, 93% were white, 27% had ISS III, 18% had high risk cytogenetics (HRCyto), 76% had t(11;14), the median prior lines of therapy (LOT) was 4 (1-15), 68% received ≥ 4 prior LOT, 87% received prior autologous transplant, 58% were triple-class refractory (TCR), 64%/23% were penta-drug exposed/refractory (PDE/R), 8% received prior BCMA-directed therapies (BDT), 58% received Ven+dex, 25% received Ven+PI +/-dex, 6 % received Ven+anti-CD38 MAb+/-dex and 11% received Ven+other. The median follow-up time from start of a Ven-based regimen was 29 months (mo). The median Ven dose was 800mg (20-1600) with 25% of pts receiving Ven ramp-up dosing. The overall response rate (ORR) to a Ven-based regimen was 58% and was 64% for pts with t(11;14) and 40% for pts without t(11;14); p=0.06. Ven-treated pts with HRCyto had inferior PFS (3mo) and OS (8mo) compared to patients who did not have HRCyto who had a PFS of 9mo (p=0.020) and OS of 80mo (p<0.001). The ORR for TCR and PDR pts were 52% and 42%, respectively. No significant ORR differences were noted across the different Ven-based regimens (p=0.32). The median PFS for pts with t(11;14) was 10mo compared to 2mo for pts w/o t(11;14); p=<0.001. The median OS for pts with t(11;14) was 80mo compared to 10mo for pts without t(11;14); p=0.001. Ven-treated pts who received 1-3 prior LOT has superior ORR, median PFS, and median OS; 89%, 25mo, and 99mo, respectively, compared to pts who received ≥4 prior LOT who achieved an ORR of 43% (p<0.001), median PFS of 5mo (p<0.001) and median OS of 25mo (p<0.001). Ven-treated pts that were TCR had inferior PFS (5mo) and OS (26mo) compared to pts who were not TCR who achieved a PFS of 12mo (p<0.001) and a median OS of 80mo (p=0.02).Ven-treated pts that were PDR had inferior PFS (4mo) and OS (22mo) compared to pts who were not PDR who achieved a PFS of 9mo (p<0.001) and a median OS of 80mo (p=0.02).Ven-treated pts who received prior BDT (n=7) achieved an ORR of 29% and had a median PFS and OS of 2mo and 6mo, respectively on a Ven-based therapy. 59 pts received additional therapy in the post Ven-progression setting. The ORR to post-Ven progression therapies was 53% (n=31/59), the median PFS was 9mo and median OS was 35mo. The most common post-Ven progression regimens used were PI-based (n=16; ORR=56%), anti-CD38 MAb-based (n=14; ORR=50%), BDT (n=12; ORR=83%), selinexor-based (n=3; ORR=0%) with BDT resulting in highest ORR (p=0.048) and PFS (p=0.005). Conclusions: Ven-based regimens are effective in heavily pre-treated pts with RRMM however they are more effective when used within 1-3 prior LOT, in pts with t(11;14), and in pts without HRCyto, TCR or PDR MM. BDT appear to be the most efficacious therapies in the post-Ven progression setting.

Introduction: Uniform assessment of response to treatment is crucial to managing myeloma and developing new therapies. Measurement of the monoclonal protein (s) secreted by the myeloma cells forms the cornerstone of disease assessment in MM and has primarily been performed by electrophoretic methods in the serum and urine, as well as assessment of free light chains in the serum. According to international myeloma working group (IMWG) guidelines, serial serum-free light chain (sFLC) is included in MM response assessment to define stringent complete response and for evaluating partial response (PR) or progressive disease (PD) in non/oligo-secretory MM. This study aims to determine the added value of serial sFLC measurements in monitoring response and progression in MM with measurable disease by comparing the kinetics of FLC with M spike measured by electrophoresis in serum or urine. Methods: This retrospective observational study included newly diagnosed MM patients evaluated at Mayo Clinic in Rochester between 2011-2021. All patients had measurable sFLC (involved FLC level ≥ 10mg/dL, with abnormal sFLC ratio) along with measurable M-protein by serum or urine protein electrophoresis at diagnosis. Serial measurements of sFLC and M-protein by electrophoresis (sPEP/uPEP) were prospectively collected from the electronic medical records at different time points. FLC-response and FLC-PD were evaluated based on IMWG criteria. Results: The study cohort included 839 patients, 52% with measurable M protein by electrophoresis in serum, 27% in both serum and urine, and 21% in urine-only. A significant association was observed between sFLC and electrophoretic response during the induction and at the time of best response (p <.001). Serum FLC showed a comparable response rate of 98% (≥ PR) at the time of best electrophoretic response (p <.001). Ninety-nine percent of early FLC responders eventually achieved an overall response by sPEP/uPEP (p <.001). In the urine-only group, 99% achieved at least a PR by uPEP, and all showed at least a PR based on sFLC. We observed comparable median percentage changes in serial dFLC and urine M-protein, with parallel trends (p <0.001). The correlation coefficients between the change of sFLC and urine M-protein showed a moderate/strong correlation with coefficients (r) of 0.791, 0.597, 0598, 0.545, after cycles 1, 2, 3, 4, respectively, (p < .001). The response for all cohorts was detected earlier by dFLC (median time 1.1 months, 95% CI: 1.06-1.17), in comparison with serum M-protein (1.5 months, 95% CI: 1.40-1.62) and urine M-protein (2.8 months, 95% CI: 2.42-3.10) with p < .001. In the urine-only group, earlier detection of response by dFLC (1.1 months, 95% CI: 1.00-1.2) was observed, compared to urine M-protein (2.4 months, 95% CI: 2.00-2.7) (p <.001). After a median follow-up of 52 (IQR 27.6, 72.3) months, 56% had PD: 62% by s-FLC, 56% by serum M-protein, and 24% by urine M-protein. Among patients with PD by uPEP, all except one patient met sFLC-PD. Within patients with PD, sFLC was the only detectable tumor marker in 12% of cases at the time of the second line of treatment. After four cycles of induction, there was no difference in PFS between VGPR response determined by sFLC, sPEP, and uPEP (p =0.538). The median second-PFS for patients with onlysFLC-PD was similar to those with urine M-protein PD with or without sFLC-PD (HR 1.28, 95% CI =0.77-2.13. p 0.334). However, the median overall survival (OS) from the first relapse was significantly better for patients with onlysFLC-PD than those with urine M-protein PD (HR 1.87, 95% CI =1.07-3.27. p 0.026). Conclusions: In this study, achieving sFLC-VGPR has a similar impact on PFS as electrophoretic-VGPR after induction, indicating that serial sFLC can potentially replace the requirement for urine M-protein response (< 100mg in 24-hours urine) as part of the electrophoretic-VGPR criteria, as required by IMWG. A similar response rate between sFLC and urine paraprotein confirms the current cutoffs (90% for urine and 50% for dFLC for VGPR) used for response categories for s-FLC. We also observed that in 12% of patients with PD, sFLC was the only marker of progression, highlighting the value of serial s-FLC in monitoring relapse. In conclusion, our study supports the integration of serial sFLC measurements for monitoring response and progression in MM, even with electrophoretic measurable disease.

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 and significance: Light chain (AL) amyloidosis is a plasma cell malignancy characterized by the production of amyloidgenic clonal light chains that deposit in various tissues. The addition of daratumumab to bortezomib, cyclophosphamide and dexamethasone (Dara-VCD) has improved the depth of hematologic and organ responses and is an approved induction therapy in newly diagnosed AL amyloid patients (DOI: 10.1056/NEJMoa2028631). However, this approach has not yet demonstrated an overall survival (OS) benefit and follow up remains short. With strict adherence to eligibility criteria, in particular severity of cardiac involvement, autologous stem cell transplantation (ASCT) as consolidative therapy is safe with transplant related mortality on par with multiple myeloma. This approach generates deep and sustained responses, but it is unclear if it offers an additional survival benefit following Dara-VCD induction. The only randomized trial evaluating the role of ASCT in AL amyloid is outdated (DOI: 10.1056/NEJMoa070484) and no randomized data exist to inform the optimal use of ASCT in the era of Dara-VCD induction. Furthermore, multi-organ involvement in AL amyloid drives morbidity and mortality thus the impact of any consolidative therapy on cardiac and renal involvement in addition to overall survival but must be defined. Finally, the approval of Dara-VCD therapy was based on complete hematologic response rates but there is increasing data demonstrating that achieving minimal residual disease (MRD) negativity by either bone marrow next generation flow cytometry (DOI: 10.1002/ajh.26562) or peripheral blood mass spectrometry (DOI: 10.1038/s41408-020-0291-8) generates improved organ response, hematologic progression free survival, and possibly OS. Methods: This randomized phase 3 SWOG led intergroup trial (S2213; NCT06022939) is being conducted within the United States and will accrue a total of 143 participants per arm. The primary endpoint will compare MOD-PFS (major organ deterioration progression free survival: defined as time from randomization to death, cardiac/renal progression, or hematologic progression) between participants receiving an ASCT with those receiving 3 cycles of Dara-VCD consolidation following 3 cycles of uniform Dara-VCD induction. Following the assigned consolidation, all patients will receive 18 months of daratumumab maintenance therapy. A median MOD-PFS of 31 months is anticipated in the non-ASCT arm. This study has 90% power and a two-sided significance level of 0.05 to detect a hazard ratio of 0.62 corresponding to a MOD-PFS of 50 months in the ASCT arm. Important additional endpoints include OS, hematologic PFS, cardiac and renal responses, MRD negativity both by peripheral blood mass spectrometry and bone marrow next generation flow cytometry, delayed utilization of ASCT, and quality of life. Key inclusion criteria include non-severe cardiac AL amyloid (NT-proBNP <5000; TnT < 0.06; NYHA I or II, EF ≥ 40%), CrCl ≥30 mL/min, serum dFLC > 2 mg/dL, and supine systolic BP ≥ 90 mmHg. Importantly, patients are permitted to have up to one full cycle or 28 days of any plasma cell directed therapy prior to enrollment. This trial was activated on 12/1/2023 with the first patient enrolled 07/01/2024. Funding: NIH/NCI/NCTN grants U10CA180888, U10CA180819; and in part by Janssen Pharmaceuticals Inc. of Johnson & Johnson (now J&J Innovative Medicine).

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.