Abdallah, Nadine

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.

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.

Older patients with multiple myeloma (MM) exhibit wide heterogeneity in their baseline physiologic and functional status, which demands an individualized treatment approach based on biological rather than chronological age. Various frailty scores have been developed for older patients with MM, but they are underutilized in clinical trials and in practice. Older patients with MM are underrepresented in therapeutic clinical trials, and treatment recommendations are currently derived from clinical trials of transplant-ineligible patients. This article provides a summary of phase II and III clinical trials in transplant-ineligible patients with newly diagnosed MM, highlighting outcomes in patients aged ≥75 years and frailty-based outcomes. The data available thus far show that triplet regimens are more efficacious than doublets in older patients but may be associated with higher toxicity. DRd (daratumumab/lenalidomide/dexamethasone) and VRd (bortezomib/lenalidomide/dexamethasone) are good options in patients who are nonfrail, whereas dose-adjusted DRd and VRd-lite should be offered to frail patients. Frailty should be assessed regularly to guide treatment intensification and/or deescalation. It is important that frailty measures are incorporated in clinical trials evaluating novel treatments to inform how older and frail patients will benefit from these treatments.

7520 Background: There are 2 CAR-T products and 3 bispecific antibodies (BsAbs) that are FDA-approved for patients (pts) with relapsed, refractory multiple myeloma (MM). Clinical trials experience to date suggests that clinical response of BsAb is less impacted after CAR-T therapy. We examined the outcome of pts who received BsAb in standard-of-care (SOC) practice at Mayo Clinic Rochester. Methods: Retrospective analysis of MM patients who received FDA-approved BsAb at Mayo Clinic, Rochester between 12/2022- 1/2024. IMWG criteria was used for clinical response. Results: Sixty-two patients received BsAbs: 77% (48/62) received teclistamab, and 23% (14/62) received talquetamab. Median age was 62 years (range: 33-81), 60% (37/62) were males, and 45% (28/62) received prior CAR-T. Patients who had prior CAR-T therapy had more prior lines of therapy compared to those who did not. Overall, ORR to teclistamab was 61%, which is comparable to previous studies and other real-world reports. ORR and ≥CR rates were comparable between patients with and without prior CAR-T (Table). Of the 28 pts who received CAR-T before BsAbs, 61% (17/28) received idecabtagene vicleucel, 10% (3/28) were ciltacabtagene autoleucel, and 29% (8/28) on clinical trial. We then compared outcome of BsAb between pts who had relapsed from CAR-T within 1 year (n=21, median PFS: 8.84 months (range, 1.12, 10.84)) or after 1 year (n=7, median PFS: 16.62 months (range, 13.30, 36.20)). At the time of BsAb infusion, pts with who relapsed < 1 year vs ≥1 year post CAR-T had comparable blood counts, ALC, M-protein and involved FLC levels, CRP, ferritin and LDH. BsAb CR/sCR rate was significantly higher in pts with disease relapse ≥1 year compared to <1 year post CAR-T (57% vs 14%, p=0.02). Conclusions: Irrespective of prior CAR-T exposure, BsAb have clinical activity in SOC practice in pts with MM. Our preliminary data suggest that responses to BsAbs are better in pts with late compared to early relapse post CAR-T. Longer follow-up is needed to understand the duration of response. Larger, multi-center studies with longer follow-up will help identify factors that impact BsAb response post CAR-T.[Table: see text]

AbstractSeveral tools exist for assessing frailty in multiple myeloma (MM), but most are based on clinical trial datasets. In this study, we evaluate the prognostic impact of frailty based on the cumulative deficit frailty index (FI), and the prognostic impact of relationship and socioeconomic status (SES) in newly diagnosed MM patients. This is a retrospective study including 515 patients with MM seen at Mayo Clinic (Rochester, MN) at diagnosis between 2005–2018. The FI was calculated using patient-reported data on activities of daily living and comorbidity data. Items were scored as 0/0.5/1, with 1 indicating deficit. The FI was calculated by adding individual scores and dividing that by the number of non-missing items. Frailty was defined as FI ≥ 0.15; 61% were non-frail and 39% were frail. Frailty and non-married/relationship status were associated with higher disease stage, decreased likelihood of early transplantation, and independently associated with decreased survival. SES was not independently associated with survival. Frail patients reported worse scores for fatigue, pain, and quality of life. In conclusion, a cumulative deficit FI was associated with higher symptom burden and decreased survival in a real-world cohort of newly diagnosed MM patients. Social support has prognostic value and should be assessed in clinical practice.

CONCLUSION The most widely used multiple myeloma (MM) staging system, the Revised International Staging System (R-ISS), is based on lactate dehydrogenase (LDH), albumin, high-risk genetic markers by FISH, and beta-2 microglobulin (B2M). However, it does not account for additional risk impacted by multiple genetic abnormalities, or the risk imparted by presence of gain of chromosome 1q, and most patients are staged as R-ISS Stage 2. Two new staging systems, the Mayo Additive Staging System (MASS), and the Second Revision of the International Staging System (R2-ISS) have been recently proposed. A comparison of the performance of these two systems has not previously been done. We aimed to externally demonstrate the application of these staging systems and compare their performances in a large, contemporary cohort of patients in the United States. We conducted a retrospective cohort study using the nationwide Flatiron Health electronic health record (EHR)-derived de-identified database, comprising de-identified patient-level structured and unstructured data, curated via technology-enabled abstraction and originating from approximately 280 US cancer clinics (~800 sites of care). The study included newly diagnosed MM patients initiating treatment between January 1, 2016 and October 1, 2022. We used the Kaplan-Meier method to evaluate real-world overall survival (rwOS) and patients were followed from first-line treatment initiation (index date) until the first of death, end of the study period or last recorded activity. The log-rank test to compare survival curves across derived stages. Multivariable analysis was conducted using stratified Cox models to account for non-proportional hazards by age with covariate adjustment for race/ethnicity, sex, practice type (academic or community) and diagnosis year (2016-2019 vs 2020-2022). Discrimination and calibration were evaluated in crude models using Harrell's c-index and the Hosmer-Lemeshow goodness-of-fit test, respectively. There were 497 patients with MM included. Patient characteristics are listed in Panel A. The distribution of patients across R-ISS stages were as follows, 24%, 63% and 13% for Stage 1, 2 and 3 respectively. rwOS differed across R-ISS stage (log-rank p = 0.0006) and the median OS (OS) was not reached (NR), 63, and 37 months for R-ISS stage 1, 2, and 3, respectively. 34%, 35% and 31% for MASS 1, 2, and 3, respectively. The corresponding survival curves were significantly different (p &lt; 0.0001), with associated mOS of 77, 61 and 45 months for MASS stages 1, 2, and 3, respectively. R2-ISS includes four risk categories (stages I-IV) and in our cohort, 20% (n = 100) were stage I (low), 126 (25%) were stage II (low-intermediate), 229 (46%) were stage III (intermediate), and 42 (9%) were stage IV (high). Survival across stages were significantly different (p&lt;0.0001), though the survival curves for low and low-intermediate, and intermediate-high and high, were clustered, suggesting comparable outcomes in stages I-II and stages III-IV. mOS for R2-ISS stages I, II, III, and IV was NR, 69, 50 and 51 months respectively (Panel B). In fully adjusted analyses, as compared to MASS I, the hazards of death were 2.0 (95% CI 1.3-3.2) for MASS II and 2.7 (1.7-4.2) for MASS III. The hazards of death were similar for R2-ISS low and low-int (HR for low-int vs low: 1.2 [0.7, 2.3]). As compared to R2-ISS low, the hazards of death were similarly higher for int-high and high (HRs: 2.4 [1.4, 4.1] and 2.6 [1.3, 5.2], respectively). Discrimination and calibration were similar across all staging systems (c = 0.6, and Hosmer-Lemeshow p&gt;0.05 for all three staging systems). Application of contemporary MM staging systems in a large cohort of US patients shows that they are prognostic for OS in MM. MASS demonstrated a greater separation for OS across stages, whereas R2-ISS intermediate-high and high were largely overlapping. Although our results demonstrate similar accuracy and reliability of MASS and R2-ISS, the discrimination of patients across different stages seen with the newer staging systems, as opposed to R-ISS, calls for greater use of these newer staging systems in routine clinical practice.

Background: Frailty is a state of decreased reserve affecting multiple organ systems, thereby increasing vulnerability to stressors. Several tools have been proposed to measure frailty in multiple myeloma (MM), such as the IMWG frailty index, and the Revised Myeloma Comorbidity Index. However, these are based on clinical trial datasets, and include chronological age as one of the indicators of frailty. A frailty index based on the principle of accumulation of health deficits (Rockwood doi:10.1093/gerona/62.7.738), provides a measure of physiologic age. This index can be readily calculated using various combinations of health deficits and has been shown to predict outcomes in several populations. Social support has been associated with improved outcomes in various populations, however its impact on survival in patients with MM has not been well studied. The objective of this study was to assess the impact of frailty measured by a deficit accumulation frailty index and the impact of relationship status on outcomes in patients with newly diagnosed MM. Methods: This is a retrospective study including patients diagnosed with MM between January 6 th, 2005, and September 19 th, 2018. We calculated a deficit accumulation frailty index using previously published methods (McNallan et. al doi.org/10.1016/j.ahj.2013.07.008, Searle et al. doi.org/10.1186/1471-2318-8-24). We used the electronic medical record system at Mayo Clinic in Rochester, MN, to extract data on activities of daily living (14 items) provided by patient-completed questionnaires, and data on comorbidities as recorded by treating providers (16 items), within 6 months prior to diagnosis. Each item was scored as 0, 0.5, or 1, with 1 indicating the presence of deficit (Table 1). The frailty index was defined as the sum of individual scores divided that by the total number of non-missing items. Patients who had N &gt;2 missing items were excluded. Patients with a frailty index ≥0.15 were considered frail. We also extracted data on self-reported relationship status within 6 months prior to diagnosis. Variables were compared between groups using Fisher's exact test and Wilcoxon signed-rank test for categorical and continuous variables, respectively. Univariate and multivariate analysis were performed using Cox proportional hazard models. Overall survival (OS) was estimated using the Kaplan-Meier method and compared between groups using the Log-rank test. P values &lt;0.05 were considered statistically significant. Results: We included 578 patients. Median age was 67 (interquartile range: 59-74) years, and 40% were female. Among all patients, 226 (39%) were frail. Compared to fit patients, patients who were frail were older (median age: 70 vs. 65 years, P&lt;0.001) and more likely to have International Staging System (ISS) III (vs. I/II) disease (47% vs. 27%, P&lt;0.001) and ECOG performance status ≥2 (vs. 0 or 1) (45% vs. 17%, P&lt;0.001). There was no difference in R-ISS III disease or presence of high-risk cytogenetic abnormalities between fit and frail patients. Median OS was 7.6 and 4.1 years in fit and frail patient, respectively (P&lt;0.001). Physician assessed ECOG performance status was available for 268 patients. Among patients with ECOG performance status 0 or 1 (193 patients), 136 (70%) were fit, and 57 (30%) were frail. The OS was 8.3 and 4.6 years in the 2 groups, respectively (P=0.006) (table 2). On multivariate analysis including age, frailty status, and R-ISS stage (III vs. I/II), all were associated with OS with frailty's hazard ratio (HR): 1.4 (95%CI [1.1-1.8]), P=0.004; the HR was 1.4 (95%CI [1.1-1.9]), P=0.02, when analysis was restricted to patients ≥60 years. Among all patients, those who were married or in a committed relationship (474 patients) had improved survival (median OS: 7.0 vs. 3.7 years, respectively, P&lt;0.001) compared to patients who were divorced/separated, widowed, or single (96 patients). On multivariate analysis, which included age, R-ISS III, frailty status, and relationship status, all were associated with OS. The HR for relationship status was 1.4 (95%CI [1.0-1.8]), P=0.0465. Conclusion: Frailty, defined by the deficit accumulation frailty index, is independently associated with decreased survival in patients with newly diagnosed MM. Being married or in a committed relationship is associated with improved survival independent of age, disease stage, and frailty.

Abstract The approach to patients with high-risk smoldering multiple myeloma (SMM) varies among clinicians; while some advocate early intervention, others reserve treatment at progression to multiple myeloma (MM). We aimed to describe the myeloma-defining events (MDEs) and clinical presentations leading to MM diagnosis among SMM patients seen at our institution. We included 406 patients diagnosed with SMM between 2013-2022, seen at Mayo Clinic, Rochester, MN. The 2018 Mayo 20/2/20 criteria were used for risk stratification. Median follow-up was 3.9 years. Among high-risk patients who did not receive treatment in the SMM phase (n=71), 51 progressed by last follow-up; the MDEs included: bone lesions(37%), anemia(35%), hypercalcemia(8%), and renal failure(6%); 24% met MM criteria based on marrow plasmacytosis (≥60%) and/or free light chain ratio (>100); 45% had clinically significant MDEs (hypercalcemia, renal insufficiency, and/or bone lesions). MM diagnosis was made based on surveillance labs/imaging(45%), testing obtained due to provider suspicion for progression(14%), bone pain(20%), and hospitalization/ED presentations due to MM complications/symptoms(4%). The presentation was undocumented in 14%. A high proportion (45%) of patients with high-risk SMM on active surveillance develop end-organ damage at progression. About a quarter of patients who progress to MM are not diagnosed based on routine interval surveillance testing.