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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 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.

Introduction: Light chain multiple myeloma (LCMM) is a distinct subtype of multiple myeloma (MM) characterized by the exclusive production of immunoglobulin light chains, unlike the common form of MM that produces the complete immunoglobulin. There is a paucity of literature on the specific tumor cell alterations leading to light chain-only disease as opposed to the typical presentation in MM. Additionally, data on treatment response and outcomes in this subgroup of patients is sparse. This study explores the differences in baseline characteristics, including cytogenetic abnormalities and treatment response between LCMM and multiple myeloma with heavy chain involvement. Materials and Methods: We reviewed patient charts to obtain clinical and laboratory information for individuals diagnosed with LCMM and those with heavy chain MM (comparison cohort) from 2004 to 2022. Patients were matched for age, sex, and year of diagnosis. Data collected included treatment assessment, overall survival, and progression-free survival (PFS). Associations between outcomes and categorical variables were analyzed using the chi-square test, while the Mann-Whitney U test was employed to compare medians. Progression-free survival following initiation of initial therapy and overall survival were assessed using Kaplan-Meier analysis. The Mayo Clinic Institutional Review Board (IRB) approved the study. Results: We identified 848 patients, representing 17.1% of newly diagnosed MM cases. The median age of the LCMM cohort was 63 years (range 16-92), with a female-to-male ratio of 1:5. The LCMM cohort had higher levels of lactate dehydrogenase (LDH), beta-2 microglobulin (p<0.0001), higher baseline creatinine (p<0.0001) and calcium (p<0.0001). The two cohorts had no significant difference in the International Staging System (ISS) or revised ISS (R2-ISS). Additionally, hemoglobin (Hb) and white blood cell count at presentation were higher in the LCMM cohort. Chromosome 1 abnormalities were lower in the LCMM cohort: 1q gain (OR-0.7; 95% CI: 0.6-0.9) and 1p deletion (OR-0.7; 95% CI: 0.6-0.9, p=0.02). Likewise, the frequencies of trisomies and hyperdiploidy were lower in the LCMM cohort, with odds ratios of 0.32 (p=0.012) and 0.37 (p<0.001), respectively. The frequencies of translocations t(4;14) (OR-0.35, p<0.001) and t(14;16) (OR-0.6, p=0.03) were lower in LCMM compared to heavy chain MM. In contrast, the frequencies of t(11;14) (OR-3.4) and t(6;14) (OR-4.9) and deletion of 13q(OR-1.3) was higher in the LCMM cohort. There was no significant difference in the occurrence of del(17p)/TP53 abnormalities. The median PFS after the first regimen was shorter in the LCMM cohort (23 months vs. 27 months, p=0.03), and this difference remained significant after adjusting for baseline adverse prognostic indices and treatment regimen. Median PFS in LCMM patients with monoclonal antibody (Mab) as part of their treatment was 37 months vs. 23 months (Proteasome Inhibitor or immunomodulator-based regimen without Mab), though this difference is not statistically significant p=0.87. No significant difference was found in overall survival between the two groups. Conclusion: This study highlights unique features of light chain multiple myeloma, including increased frequencies of specific cytogenetic abnormalities. Further evaluation of observed differences in cytogenetic abnormalities may enhance our understanding of LCMM and potentially guide baseline treatment choices to improve outcome.

Background: Despite effective front-line therapies, DLBCL & MM have high relapse rates. Novel therapies like CAR-T & bispecific antibodies (BsAb) offer deep & durable remission compared to salvage therapies, but have a unique toxicity profile (TP) that requires monitoring. With no head-to-head trials, the rationale for therapy selection may vary. This study explores provider choices, sequencing preferences, & access barriers. Methods: Two anonymous surveys (MM and DLBCL) of US-based Hematologists were conducted from 2/2024 to 6/2024, on practice settings, CAR-T & BsAb availability, treatment preferences & barriers. Responses were analyzed to assess preferences across clinical scenarios. Results: Surveys were completed by 37 MM & 45 DLBCL providers. Most were at centers offering both CAR-T & BsAb. Most gave CAR-T inpatient, & BsAb outpatient. CAR-T was given by 73% MM providers & 66% DLBCL (92% used Cilta-cel, 96% used Ide-cel; 100% used Axi-cel, 90% used Liso-cel & 73% Tisa-cel). In MM, 78% used Teclistamab, 60% Talquetamab & 24% Elranatamab. In DLBCL, 62% used Epcoritamab & 40% Glofitamab. Providers preferred CAR-T over BsAb in MM after 4+ prior lines of therapy (LOT) (89%), & in DLBCL after 2+ prior LOT (93%). CAR-T was favored more among academic providers & those at CAR-T centers. Practice volume did not impact selection. Among providers at centers with BsAb-only, CAR-T was preferred by 60% (MM) and 50% (DLBCL). Providers at centers without both favored CAR-T (MM: 75%, DLBCL: 86%). CAR-T was chosen for better outcomes, short treatment, center choice, & prior experience. Other factors that influenced decisions were lower incidence of cytopenia/infection & “BsAb effective post-CAR-T, less so vice versa” (MM), & “curative potential of CAR-T” (DLBCL). Logistical barriers & institutional constraints influenced BsAb selection: CAR-T unavailability, access to specialized centers, referral complexity, insurance delay, manufacturing delay & hospitalization needs. In MM, 78% providers preferred Cilta-cel over Ide-cel, especially academic providers & those with CAR-T experience. CAR-T volume did not impact selection. Cilta-cel was preferred due to perceived better response rate (RR), more experience, “progression-free survival (PFS) benefit”, center choice, & logistical issues with Ide-cel. Ide-cel was selected due to center choice, favorable TP & insurance preference. Teclistamab was preferred by 78% due to more experience, better RR, TP & center choice, Elranatamab by 11% (better TP, RR, & “PFS”), & Talquetamab by 11% due to having a non-BCMA target. Academic providers preferred Teclistamab (89% vs 50%), & nonacademic providers preferred Talquetamab (38% vs 4%) and Elranatamab (13% vs 8%). In DLBCL after 2+ LOT, 69% favored Axi-cel due to prior experience, RR, center choice, & logistical issues with other products. Liso-cel & Tisa-cel were chosen by 27% & 2%, respectively, due to favorable TP. Axi-cel was also preferred 2nd line by 73% for similar reasons, while 24% favored Liso-cel for its favorable TP. Epcoritamab was preferred by 56% (subcutaneous injection, more experience & center choice) & Glofitamab by 42% (shorter treatment duration, easy administration, more experience, & center choice). Practice setting & volume did not impact selection between products in DLBCL. InBCMA-naïve MM pts, majority (97%) chose an anti-BCMA agent over GPRC5D due to better RR, TP, prior experience, & center choice. InBCMA-exposed pts, most (92%) favored an anti-GPRC5D agent. In contrast in DLBCL, 80% chose CD19 CAR-T after prior CD19-directed therapy, & 18% chose CD20 BsAb. Therefore, antigen escape was less of a concern in DLBCL vs MM. For relapse after 2nd line CAR-T in DLBCL, 78% preferred BsAb over other salvage options due to better RR, TP, & more experience. Providers prioritized RR, survival, & TP in decision making. Treatment logistics, duration, frequency, & cost were less crucial. MM providers also prioritized quality of life, which was less so in DLBCL. There were no differences in priority based on practice setting & experience with CAR-T. Conclusion: The study highlights factors influencing therapy choices in MM & DLBCL. Despite CAR-T's potential for better outcomes, significant access barriers exist. Efforts to streamline referral pathways, logistics, & expanding availability are crucial to improve outcomes. Understanding these preferences & barriers can guide future management strategies.

Introduction: Tissue biopsies are needed to establish a diagnosis of systemic AL amyloidosis. Biopsy can be obtained from an involved organ with suspected amyloid deposition (target biopsy) or from sites in which amyloid commonly deposits (surrogate biopsy). The choice of biopsy site depends on institutional and physician preference. Two commonly used sites for surrogate biopsies are abdominal fat pad and bone marrow. The present systematic review and meta-analysis aims to evaluate the diagnostic test accuracy of fat pad and bone marrow biopsies as surrogate biopsy sites in the diagnosis of AL amyloidosis. Methods: As part of the ASH AL Amyloidosis Diagnostic Guideline, we performed systematic reviews for seven prioritized PICO questions related to the screening, diagnosis and organ involvement evaluation of AL amyloidosis. We conducted electronic searches on PubMed, Embase, and the Cochrane Central Register of Controlled Trials from inception until January 2024. Two reviewers independently and in duplicate performed title and abstract screening and full text article screening on LASER AI, with conflicts resolved by a third reviewer. Studies were eligible if they included patients that had a fat pad sample or bone marrow biopsy and a target organ biopsy for suspicion of AL amyloidosis allowing for the calculation of diagnostic test accuracy measures. Diagnostic test accuracy measures of interest were sensitivity, specificity, positive and negative predictive value. Statistical analysis was performed on OpenMeta[Analyst]. Grading of Recommendations Assessment, Development and Evaluation (GRADE) was used to assess the certainty of evidence. Results: After deduplication, we retrieved 29,237 studies.. 20 studies with 2955 patients reporting on bone marrow biopsy, 25 with 4702 patients on fat pad sampling were included. The pooled sensitivity for bone marrow biopsy was 55.1% (95% CI 45.8-64.0, I2 = 94%) (Certainty of evidence: Low ⨁⨁◯◯), For fat pad sampling sensitivity was 76.6% (95% CI 72.1-80.8, I2 = 84.2%) (Certainty of evidence: Moderate ⨁⨁⨁◯). Among the included studies, 1 evaluated the sensitivity of fat pad sampling and bone marrow biopsy combined and found it to be 89%. No included studies evaluated specificity for bone marrow biopsy or fat pad sample. Conclusion: Combination of fat pad and bone marrow biopsy together significantly improve sensitivity for amyloid detection compared to either fat pad sampling or bone marrow biopsy alone.

Abstract Patient-reported outcomes (PROs) are associated with treatment outcomes in multiple myeloma (MM) in the clinical trial setting. However, most PRO tools are time consuming, which hinders use in routine practice. Our institution incorporated a “Hematology Patient-Reported Symptom Screen” (HPRSS), a 3-item questionnaire for fatigue, pain, and quality of life (QOL). The main objective of this study was to evaluate the impact of these symptoms on progression-free survival (PFS) and overall survival (OS) in a real-world cohort of patients with newly diagnosed MM. This retrospective study included patients with MM diagnosed between April 2011 and December 2017, seen at Mayo Clinic (Rochester, MN), who completed the HPRSS. Patients rated their symptoms on a scale from 0 to 10. Clinically relevant symptoms were defined as scores ≥5 for pain and fatigue, and ≤5 for QOL. At diagnosis, 735 patients had scores for all domains. The median follow-up was 8.1 years. Age was associated with increased odds of fatigue and decreased QOL. Female sex and comorbidities were associated with fatigue and pain. Higher disease stage, anemia, lytic lesions, and increased plasma cell burden were associated with fatigue, pain, and decreased QOL. Clinically relevant fatigue, pain, and decreased QOL were associated with decreased PFS and OS. On multivariate analysis including age, International Staging System III, high-risk cytogenetics, and postinduction transplantation, fatigue and decreased QOL were independently associated with decreased OS. A composite HPRSS score stratified patients into 3 groups with distinct OS. Patient-reported symptoms are prognostic in patients with newly diagnosed MM. The prognostic values of fatigue and decreased QOL are independent of age, disease stage, and transplant status.

The term monoclonal gammopathy of clinical significance (MGCS) refers to a group of symptomatic monoclonal gammopathies that do not meet the diagnostic criteria for malignant plasma cell disorders, such as multiple myeloma or Waldenström macroglobulinemia. These symptoms are attributable to the paraneoplastic effects of monoclonal immunoglobulins that occur through diverse mechanisms. The presence of symptoms distinguishes MGCS from monoclonal gammopathy of undetermined significance, which lacks significant symptomatic presentation. The presentations of MGCS are manifold, adding to the diagnostic challenge. Clinical suspicion is key for accurate and timely diagnosis. Radiologic imaging can provide pivotal information to guide the diagnosis. In this review, we discuss MGCS from a radiology perspective and highlight pertinent imaging features associated with the disorders.

7558 Background: Survival in patients with multiple myeloma (MM) continues to improve with the newer therapies, but there is no clear evidence of a cure and patients continue to relapse. However, most patients have the most extended period without progression with their first-line therapy, and subsequent therapies often provide a shorter duration of response due to the use of drugs with overlapping mechanisms of action and, more importantly, a shorter first remission, pointing toward more aggressive disease biology. With newer immunotherapies being used at 1st relapse, this may change. We designed this study to explore the natural history of MM after the 1st relapse and define the predictors of outcome after the initial relapse. Methods: We identified all patients in the Mayo Clinic database diagnosed between Jan 2004-June 2019 who had had initial disease progression. The study cohort included 2005 patients. We explored the overall survival (OS) from the time of documented disease progression or the start of second-line treatment in patients who had not met IMWG criteria before second-line therapy. Front-line therapy was grouped into those with either an IMiD or PI, both IMiD and PI, daratumumab with IMiD and PI, and none of these agents. The IMiD and PI were always used with dexamethasone with or without an alkylator. Results: The median age was 63 (range 24-95) years and 60% were male. The median estimated follow-up from diagnosis for all patients was 86 mos. (95% CI; 82, 88) and the median time to progression from the start of therapy was 25 mos. (95% CI; 24, 26). The median OS from the first progression was 45 mos. (95% CI; 42, 50), 36 mos. for those diagnosed before 2009, and 52-53 mos. for those diagnosed later. On univariate analysis, age <70 at 1st relapse, RISS I, novel agents in initial therapy, CR in the first line, diagnosis after 2009, initial remission >18 mos, and initiation of therapy before IMWG progression were all associated with improved OS after 1st relapse (Table). On multivariate analysis, age <70, RISS I, initial remission >18 mos, and initiation of therapy before IMWG progression were all associated with improved OS after 1st relapse. Conclusions: The study provides an estimate of the outcomes and significant predictors of outcomes after 1st relapse in patients with MM. These factors should be taken into consideration when designing clinical trials in this patient population. In particular, these factors identify a high-risk group of patients not always identified by baseline characteristics and should be the focus of future trials. [Table: see text]