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AbstractBackgroundPopulation dementia prevalence is traditionally estimated using cohort studies, surveys, routinely‐collected administrative data, and registries. Hospital Electronic Health Records (EHRs) are comprised of rich structured and unstructured (text) clinical data that are underutilised for this purpose.We aimed to develop a suite of algorithms using routinely‐collected EHR data to reliably identify cases of dementia, as a key step towards incorporating such data in prevalence estimation. Towards this, we developed a novel predictive framework integrating data‐science and biostatistical methods.MethodTraining data were sourced via the National Centre for Healthy Ageing (NCHA) Data Platform, a linked, curated, EHR‐derived data warehouse. Individuals within the platform catchment aged >60 years with confirmed dementia were identified through hospital specialist dementia clinics. A comparison group of individuals aged >60years with EHR records without dementia was recruited from the community.A panel of clinical experts (Neurology, Geriatric Medicine) informed variable and concept selection and guided data cleaning efforts within both streams. Algorithms were developed via two work‐streams; a traditional biostatistical approach to fit logistic regression models using structured data elements, and a data science stream used Natural Language Processing (NLP) to fit models to the unstructured (text) parts of the EHR, for the same individuals.ResultOf 568 individuals (362 with dementia), 434 had clinical notes available. In the data science stream using unstructured data, among a range of NLP derived models, the Random Forest classifier performed best in assigning dementia status, with Area Under the Curve (AUC) 0.95, specificity 90.2% and sensitivity 88.4%. In the biostatistics stream, 15 structured variables were included in the final model, covering demographics, health service attendance, medications, and ICD‐10 Codes, with AUC 0.94, specificity 85.9% and sensitivity 85.6%.ConclusionArtificial intelligence techniques applied to unstructured electronic health data and guided by human clinical expertise may be powerful tools in capturing the presence of dementia, at least comparable to traditional techniques using structured data, and conferring practical and scientific advantages for dementia prevalence estimation. Future validation is required in less crisply delineated real‐world settings.

Abstract Several tools have been proposed for assessing frailty in multiple myeloma (MM), but most are based on clinical trial data sets. There are also limited data on the association between frailty and patient-reported outcomes and on the prognostic value of social determinants of health. This study evaluates the prognostic impact of frailty, based on the cumulative deficit frailty index (FI), and relationship and socioeconomic status (SES) in patients with newly diagnosed MM. This retrospective study included 515 patients with MM seen at Mayo Clinic (Rochester, MN) at diagnosis between 2005 and 2018. The FI was calculated using patient-reported data on activities of daily living and comorbidity data, with items scored as 0, 0.5, or 1, in which 1 indicated a deficit. The FI was calculated by dividing the total score by the number of nonmissing items. Frailty was defined as FI ≥0.15; 61% were nonfrail, and 39% were frail. Frailty and nonmarried/relationship status were associated with higher disease stage, decreased the 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. Approximately a quarter of patients had a deterioration in frailty status at 3 to 12 months, and <10% had improvement. In conclusion, a cumulative deficit FI was associated with higher symptom burden and decreased survival in a real-world cohort of patients with newly diagnosed MM. Frailty status is dynamic and should be reassessed during treatment. Social support has prognostic value and should be evaluated in clinical practice.

Abstract Aims Causes of death remain largely unexplored in the atrial fibrillation (AF) population. We aimed to (i) thoroughly assess causes of death in patients with AF, especially those associated with sudden cardiac death (SCD) and (ii) evaluate the potential association between AF and SCD. Methods and results Linked primary and secondary care United Kingdom Clinical Practice Research Datalink dataset comprising 6 529 382 individuals aged ≥18. We identified 214 222 patients with newly diagnosed AF, and an equivalent number of non-AF patients matched for age, sex and primary care practice. The underlying primary cause of death for each patient was assessed in the form of International Classification of Diseases Tenth Revision (ICD-10) codes and also as part of broader disease categories (i.e. ICD-10 chapters). Findings Over a median follow-up of 2.7 (interquartile range: 0.7–6.0) years, 124 781 (58.25%) patients with AF died. Sudden cardiac death occurred in 13 923 patients with AF [6.50% patients with AF vs. 2.01% non-AF patients; odds ratio (OR) = 3.38, 95% confidence interval (CI): 3.27–3.50, P < 0.0001], contributing to 11.05% of all AF mortality. Diseases of the circulatory system, neoplasms and respiratory diseases explained 45% of AF mortality. Sudden cardiac death occurred more frequently in males (OR = 1.87, 95% CI: 1.80–1.93, P < 0.0001), and females with AF died more often of diseases of the circulatory, respiratory, digestive, and genitourinary system and less often of neoplastic disorders. Interpretation Conditions of the circulatory system are the main driver of mortality in the AF population. Females with AF experience higher cardiovascular and respiratory mortality but die less frequently of neoplasms. The risk of SCD is higher in the AF population, occurring more frequently in males.

Abstract Problem In the United States, physician bias is exhibited early in medical training and contributes to systemic inequities within the field of medicine. A lack of diversity, equity, inclusion, and antiracism (DEI-AR) content within medical curricula drives critical gaps in knowledge and deficiencies when preparing medical students to serve patients of diverse backgrounds. At the Mayo Clinic Alix School of Medicine (MCASOM), student-led curricular reviews between 2017 to 2018 and 2020 to 2021 revealed opportunities to improve DEI-AR content within preclinical courses. Course directors expressed concern of limited expertise and time to enact effective changes. Approach The MCASOM DEI-AR teaching assistant (TA) program aims to curate a collaborative partnership between course directors and compensated student TAs to facilitate course enhancements responsive to the prior preclinical course review while centering standardized DEI-AR best practices. Outcomes As of January 2024, the program has engaged 14 TAs and partnered with 24 preclinical courses. Postcourse student evaluation responses were collected from 8 courses for 2021 to 2022 (before enhancements) and 2022 to 2023 (after enhancements). Student satisfaction with DEI-AR content is tracked through postcourse evaluations, with preliminary data demonstrating improvement after DEI-AR curricular integration (improvement of mean preenhancement and postenhancement scores of 3.81 to 4.05; t12 = 1.79, P = .21). Qualitative student comments were sorted into general categories of positive, negative, or neutral, showing a 6.25% median increase in positive perception of DEI. Next Steps Plans for the MCASOM DEI-AR TA program include application of quality improvement strategies to improve program processes and outcomes. Development of a centralized dashboard that integrates course enhancement progress and ongoing feedback from evaluations is anticipated to facilitate this effort. The program additionally aims to develop partnerships with clinical clerkships, which would allow for a more comprehensive enhancement of the overall medical education experience related to DEI-AR.

Introduction: Light-chain amyloidosis (ALA) is a rare plasma cell disorder characterized by multiorgan involvement. Patients often present with non-specific symptoms, which can lead to a delay in diagnosis. This is associated with progressive organ involvement and shorter survival. Reducing the time from symptom onset to diagnosis is a critical step in improving outcomes. This study was designed to evaluate the clinical prodrome and challenges associated with the diagnosis of ALA from the patient perspective. Methods: This retrospective study surveyed patients with ALA through the online HealthTree® Cure Hub platform, which helps patients navigate their disease in a holistic way. The survey consisted of 32 questions, including 23 multiple-choice, 7 date-entry, and two free-response questions. Data on diagnosis and demographics were extracted from the electronic health record and self-reported data linked to HealthTree® Cure Hub. Results were reported as numbers and percentages, and comparisons were made by age (≥70 vs. <70 years) and sex. The following statistical methods were used: Fisher's exact test for categorical data, two-sample t-test and F-test for normally distributed continuous data, Wilcoxon rank-sum test for skewed data and Spearman correlation coefficient. Results: We surveyed 248 patients. Of those, a total of 87 patients with a self-reported diagnosis of ALA completed the questionnaire between March 12, 2023, and May 8, 2024. The median age was 66 years; 55% were female, and 91% were white. The most common initial symptoms prompting patients to seek medical evaluation were fatigue/weakness (47%), swelling (38%), shortness of breath (28%), chest pain (23%), and foamy urine (22%). Pain in hands/feet, carpal tunnel syndrome, loss of appetite, hoarseness, macroglossia, diarrhea, periorbital puffiness, nail changes, and erectile dysfunction each accounted for <10% of cases. Signs and symptoms were first detected by patients themselves in 58% of cases, by a physician in 33% and by a family member or friend for the rest. The median number of symptoms per individual was 2; 31% reported only one symptom, 37% 2-3, 18% 4-6, and 14% >6; with chest pain being the most common (39%), followed by swelling (22%), shortness of breath (13%), and foamy urine (13%); one patient reported erectile dysfunction and another reported arrhythmias as their only symptom. There was a correlation between hoarseness and nail changes (ρ=0.71), and carpal tunnel syndrome and orthostatic hypotension (ρ=0.63). Only 16% were aware of ALA as a condition prior to symptom onset. Thirty six percent presented to a general practitioner for initial evaluation; about 50% sought a specialist, including a myeloma/amyloid specialist (21%), and 14% were first evaluated in the emergency department. While most patients (45%) were diagnosed by a hematologist/oncologist, patients reported seeing a median of 3 physicians (range: 1-10) before the diagnosis was established. Among responders, 61% reported having myeloma at the time of testing. After diagnosis, about 50% were referred to a center specialized in ALA, and 72% met with a stem cell transplant specialist. Most patients reported receiving multidisciplinary care, with a median of 3 additional specialists participating in ALA care (range: 0-16). More than half of patients (59%) felt the diagnosis was delayed; among those, 42%, 24%, 24%, and 11% reported a delay of 1-6, 7-12, 13-24, and >24 months, respectively. The proportion of patients reporting >12-month delay was higher among older patients (54% vs. 27%, P=0.02). A quarter of responders felt their treatment was delayed. Half of patients felt the diagnostic delay contributed to a decrease in treatment efficacy and 48% did not feel that all medical professionals were knowledgeable about ALA. Only 38% felt the diagnostic process was simple and easy within their healthcare system. Conclusion: Most patients with AL amyloidosis initially present with non-specific symptoms, with fatigue/weakness being the most common. Over a third were evaluated first by a general practitioner, and about a third reported a diagnostic delay of >12 months. The diagnostic process is associated with high healthcare utilization, even among patients with concurrent multiple myeloma. Increasing disease awareness among patients and medical providers may shorten the time to diagnosis and contribute to improved outcomes.

Background: Venetoclax (Ven), a BCL2 inhibitor, has shown promising responses in multiple myeloma (MM) patients with t(11;14) and/or BCL2 expression. However, consistent benefit in clinical trials remain elusive. This report evaluates the efficacy and safety of Ven combination therapies, including in the non-t(11;14) subgroup, and examines the impact of secondary cytogenetic abnormalities (SGA) on outcomes. Methods: This retrospective study included multiple myeloma (MM) patients without concurrent AL amyloidosis treated with Ven-based combinations at Mayo Clinic sites from January 2015 to December 2023. FISH data was collected at diagnosis and before venetoclax initiation to assess SGAs. Refractoriness was defined by progression on or within 60 days of stopping treatment. Patients refractory to at least one proteasome inhibitor (PI), immunomodulatory drug (ImiD), and anti-CD38 antibody were considered triple-class refractory (TCR). Ven combinations were grouped as: Daratumumab/CD38 antibody (Dara)-Ven based if received Dara ± other drugs, PI-Ven-based without Dara, Ven-dexamethasone (Ven-d), and other combinations (Ven-Misc). BCL2 expression in patients without t(11;14) was determined by immunohistochemistry (IHC). Progression-free survival (PFS) was calculated from treatment initiation to disease progression or last follow-up. Results: We included 232 patients in this study. The median age at diagnosis of MM was 62 years (range 32-87), and the median age at initiation was 68 years (range 35-89). The median time from diagnosis of MM to initiation of Ven was 55 months (95% CI 28, 89 months), and the median follow-up from initiation of Ven-based treatment was 17.2 months (95% CI: 14, 22). Patients had received a median of 3 lines (IQR 4-6); 65% (n=152) of patients were TCR, 71% (n=163) had received autologous stem cell transplant and 7% (n=16) patients had received prior immune effector therapy prior to initiation of Ven-based therapy. The majority (83%, n=190) of the patients harbored a t(11;14); in the patients without t(11;14), a BCL2 expression by IHC was tested in 18 patients and positive in 17 patients. The most common Ven-based combinations included: Dara-Ven-d (19%, n=44), PI-Ven-d (30.2%, n=70), Ven-d (48.3%, n=112), Ven-misc (2.6%, n=6). The overall response rate for the entire cohort was 57% [64% for t(11;14) and 26% for non t(11;14), p<0.0001]. The median PFS for the entire cohort was 9.5 months (95% CI 8.5,13), and the duration of response was 18 months (95% CI 15.2-23.3). The median PFS was 11.8 months (95% CI 9.5-16.7) for patients harboring a t(11;14) compared to 2.9 months (95% CI 1.8, 8.4) for patients without a t(11;14), p<0.0001. Among the non-t(11;14) cohort with BCL2 expression, the median PFS was 1.8 months (95% CI: 1.2-4.2). Among the 190 patients with t(11;14), 18% (34/190) harbored deletion 17p and 32% (60/193) harbored a 1q gain/amplification (referred hereforth as 1q21+) at initiation of Ven-based therapy. In the cohort of patients with t(11;14), the presence of either del17p or 1q21+ (n=85/190) was associated with a significantly inferior PFS [median PFS 8.2 months (95% CI: 5.5,13)] vs. 15.1 months (95% CI: 11.6, 22), p=0.03. At the last follow-up,42 patients had ongoing treatment with ven-based combination. Most common reasons for discontinuation were progression (77% N=140), adverse effect (12%, n=22), patient/provider preference(9%, n=17); 2% (n=4) patients died without progression (3 infection, 1 unclear). The most commonly utilized maximum dose of venetoclax was 400 mg (42%); 15% (n=35) of patients required a dose reduction, and 23% (n=54) received a ramp-up. Tumor lysis syndrome was not noted in any patient. Infectious complications were noted in 23% (n=52). The estimated median OS from initiation of ven-based Rx was 34 months (95%CI 25-47). The estimated median OS for patients without a t(11;14) was 6.2 months (95% CI: 3.3-11.3) compared to 46 months (31.4-54.1), p<0.0001. In the t(11;14) subgroup, the 18-month OS rate was 79% for patients without 1q21+/del17p vs. 50% for patients with a 1q21+/del17p (p=0.002). Conclusion: Venetoclax-based regimens represent an important treatment option for patients harboring a t(11;14). The PFS in patients with BCL2 expression without t(11;14) was poor suggesting lack of efficacy of venetoclax-based regimens for that subgroup. Presence of concurrent del17p and/or 1q21+ with t(11;14) portends an inferior PFS.

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.

Introduction: Frailty is known to be an important risk factor for adverse outcomes in multiple myeloma (MM) and is often under-represented in clinical trials. Frail patients are known to have increased toxicity, high rates of treatment discontinuation rates and decreased efficacy including worse overall survival in MM. Teclistamab (TEC) is a bispecific BCMA-CD3 directed T-cell antibody (BsAb) that was approved based upon the pivotal MajesTEC-1 study showing high overall response rates in patients with R/R MM. In MajesTEC-1, the median age was 63, and patients with ECOG ≥ 2 were excluded, suggesting that the vast majority of patients in the trial were fit. There is a paucity of data both in clinical trials as well as in the real-world regarding the outcomes of patients, particularly frail patients, with BsAb. This data is needed to both understand current outcomes of frail patients as well as devise strategies for future optimization with BsAb treatment. We performed a retrospective analysis utilizing the International Myeloma Foundation (IMF) immunotherapy database with the objective of understanding the outcomes of older adults (age ≥ 70) including frail patients treated in the real-world with teclistamab. Methods: Data was collected from 7 individual academic sites for patients aged ≥ 70 years treated with teclistamab in the real-world. Data collected include patient demographics, disease characteristics, as well as efficacy and toxicity associated with teclistamab. Frailty score was retrospectively calculated using the simplified/IFM frailty index which includes chronological age, ECOG PS and Charlson Comorbidity Index categorizing the patients into fit (score 0-1) or frail (≥ score 2). Fisher's exact tests were performed to evaluate differences in outcomes between fit and frail patients. Results: A total of 81 pts were included in our total cohort. The median age was 76 year (range 70-91). Among them, 44 (54%) were > age 75 and 23 (28%) > age 80. Twenty-eight (35%) patients had an ECOG performance status of ≥2. Using the simplified/IFM frailty index, 22 (27%) were classified as fit and 59 (73%) were frail. In the frail subgroup, a high proportion of patients (42%) would be classified as ultra frail (frailty score of ≥3). Selected baseline patient and disease characteristics are as follows: high risk cytogenetics including 1q gain/amp (fit 67% vs frail 43%), median prior lines (fit 7 vs frail 5), triple class refractory (fit 81% vs frail 88%), CrCl <30 (fit 5% vs frail 15%). For patients hospitalized for step-up dosing, median number of hospital days was 8 both in the fit and frail group. All grade CRS was noted in 12 (55%) fit and 28 (47%) frail patients. Among the fit patients, only 1 of the 12 patients (8%) had grade 2 CRS, whereas 8 of 28 (29%) frail patients had grade 2 (p-value=0.23). ICANS was reported in 2 (9%) fit patients and 8 (14%) frail patients (p=0.72). The majority of ICANS was grade 1 in both groups, but among the frail group, there was one grade 3 and two grade 4 ICANS cases reported. Infections were reported in 10 (45%) fit patients and 35 (59%) frail patients (p=0.32), with 2 (9%) and 14 (23%) being grade≥3 (p-value=0.21). IVIG was administered in most patients (fit 50% vs frail 58%, p=0.62). Grade 3/4 neutropenia was reported in 10 (45%) fit patients and 19 (32%) frail patients (p=0.30). The overall dosing interval was changed in 32% of fit patient and 34% of frail patients (p=1.00). The overall response rate was 50% for fit patients versus 66% for frail patient (p=0.61). The type of responses noted in the fit patient were as follows: sCR/CR 18%, VGPR 27%, PR/MR 5%, SD 18%, PD/NE 32% and for frail patients : sCR/CR 18%, VGPR 43%, PR/MR 9%, SD 5%, PD/NE 25%. The median follow-up time was 13.1 months. 12-month PFS for fit pts was 47.6% (95% CI 25.7% - 66.7%) and for frail pts 42.4% (29.0% - 55.3%). 12-months OS for fit pts was 64.9% (95% CI 39.9% - 81.6%) and for frail 61.5% (47.0% -73.1%). Conclusions: This is the first real-world study to evaluate the outcomes of teclistamab in frail older adults. With regards to toxicity, frail older adults showed a trend towards higher rates of ≥ grade 2 CRS, ≥ grade 2 ICANS as well as ≥3 grade infections. Efficacy was maintained in both fit and frail older adults similar to the MajesTEC-1 study. Our study highlights that BCMA BsAb can be safely utilized in older adults including frail older adults; however, additional proactive supportive care may be required to further optimize outcomes.

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.