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e20030 Background: Recent studies suggested associations between higher serum Magnesium (Mg) level and better survival outcome in patients receiving immunotherapy, especially in small cell lung cancer (SCLC). However, the prognostic significance of Mg in extensive-stage (ES) SCLC treated with first-line chemoimmunotherapy remains unclear. We evaluated the association between baseline serum Mg and survival outcomes in ES-SCLC receiving platinum–etoposide plus PD-(L)1 blockade. Methods: We conducted a retrospective cohort study of adults with ES-SCLC treated with first-line platinum–etoposide plus atezolizumab or durvalumab at Mayo Clinic via Mayo Clinic Platform in 2018–2025. Baseline average serum Mg level was defined as the mean of all Mg labs from day −30 to day 0 relative to chemoimmunotherapy initiation and categorized as low ( < 1.7 mg/dL), normal (1.7-2.0 mg/dL), or high ( > 2.0 mg/dL) using clinical cutoff. Low and normal groups were combined a priori due to small low-Mg counts. The primary endpoint was overall survival (OS), estimated by KM and compared by log-rank test. OS was measured from chemoimmunotherapy initiation to death and censored at last follow-up. Multivariable Cox proportional hazards models adjusted for age, gender, ECOG, liver/brain metastases status, and smoking status. Results: The cohort included 214 patients, 124 (58%) were female; median age was 68 years; 49% had liver metastases and 30% had brain metastases. Median OS was 10.4 months (95% CI 7.6-15.9) among 99 patients with high serum Mg level, compared with 7.5 months (95% CI 6.7-10.7) in 115 patients with low or normal serum Mg level (Log-rank p = 0.126). High Mg was associated with a trend toward longer OS in unadjusted analyses (Hazard ratio [HR] 0.80, 95% CI 0.59-1.07, p = 0.129); however, the association was not statistically significant after multivariable adjustment (aHR 0.81, 95% CI 0.60-1.10, p = 0.180). Conclusions: Among patients with ES-SCLC treated with first-line platinum–etoposide plus PD-(L)1 blockade, higher baseline serum Mg was associated with numerically longer OS but was not independently associated with survival after multivariable adjustment. These findings suggest baseline serum Mg level may be associated with prognosis and warrant validation in larger cohorts. Baseline characteristics by baseline serum magnesium category in ES-SCLC treated with first-line chemoimmunotherapy. Variable Overall (N=214) High Mg >2.0 (n=99) Low/Normal Mg ≤2.0 (n=115) p value* Age, median (IQR) 68 (62, 74) 68 (61, 74) 69 (62, 75) 0.201 Female, n (%) 124 (58%) 57 (58%) 67 (58%) >0.999 ECOG ≥2, n (%) 58 (27.1%) 28 (28%) 30 (26%) 0.719 Liver metastases, n (%) 105 (49%) 49 (49%) 56 (49%) 0.648 Brain metastases, n (%) 65 (30%) 33 (33%) 32 (28%) 0.469 Ever smoker, n (%) 197 (92.1%) 90 (90.9%) 107 (93.0%) 0.974 *p values: Wilcoxon (age); χ²/Fisher (categorical).

e20000 Background: Multimodal machine-learning (ML) models that fuse imaging, pathology, omics, and clinical data may improve overall-survival (OS) prediction in non–small-cell lung cancer (NSCLC) beyond staging-based tools. We systematically reviewed the design, performance, and methodological quality of these models. Methods: Following PRISMA 2020, we searched Ovid (MEDLINE/Embase/CENTRAL/CDSR), Scopus, IEEE Xplore, and arXiv (January 2017–July 2025). Eligible studies developed or validated ML models integrating ≥2 modalities to predict OS in adults with NSCLC and reported either time-to-event or fixed-horizon binary outcomes. Two reviewers independently screened, extracted, and assessed risk of bias using PROBAST with PROBAST-AI items. Due to heterogeneity, results were synthesized narratively. Results: We included 18 studies (2021–2025) with per-study sample sizes ranging from 115 to 2,898. Outcome framing: time-to-event OS only (n=11), fixed-horizon binary OS only (n=4), and both (n=3). Modalities most often used were clinical structured data (15/18), CT (12/18), PET (6/18), molecular omics (7/18), pathology whole-slide images (4/18), and EHR text (1/18). Fusion strategies clustered as early/concatenation (10/18), interaction-based (attention/bilinear/graph; 5/18), and late/score-level (3/18). For time-to-event OS, internal C-indices ranged 0.658–0.893, with the highest internal value 0.893 (CT+clinical). One study reported external C-index (0.678, pathology+genes). An additional study reported external time-dependent AUC 0.845 at 1-year for a PET/CT-genomics survival model (n=32). For binary OS, internal AUROCs were 0.802–0.888 (2–5-year horizons), and internal accuracies ranged 0.68–0.93 (1–5 years). External binary performance included accuracy 0.72 at 1-year in an immunotherapy cohort. Across studies, multimodal models typically outperformed the best single-modality comparator by ~+0.06 C-index or AUROC, though absolute gains varied. Risk of bias was frequently high in the analysis domain (internal-only validation, optimistic tuning, sparse calibration reporting); code/weights were publicly available in 5/18 studies. Conclusions: Multimodal ML models for NSCLC show consistent, modest improvements in OS discrimination versus single-modality approaches, with CT+clinical the most translationally pairing. However, independent validation, calibration, and transparency remain limited, constraining clinical adoption. Future work should prioritize multi-center datasets, standardized reporting, and open workflows.

e19564 Background: Risk stratification in multiple myeloma (MM) relies on baseline staging systems and cytogenetic abnormalities, yet early relapse occurs in a subset of patients despite favorable risk features. Prior studies showed that clonal plasma cell S-phase assessed by flow cytometry using the plasma cell proliferation (PCPRO) assay at diagnosis and at autologous stem cell transplantation (ASCT) identifies biologically high-risk disease. The prognostic significance of clonal plasma cell S-phase following ASCT has not been well defined. Methods: We retrospectively analyzed MM patients who underwent ASCT within one year of diagnosis between January 1, 2013, and August 31, 2024. Patients without available post-ASCT clonal plasma cell S-phase assessment were excluded, yielding 150 evaluable patients. The proportion of clonal plasma cells in S-phase was determined by DNA content between G0/G1 and G2/M peaks and reported as a percentage. S-phase was assessed at the first post-ASCT marrow evaluation at day +60 (D45–75) and/or day +100 (D76–130), using the earlier assessment when both were available. Patients were classified as low (<2%) or high (≥2%) post-ASCT S-phase. Landmark progression-free survival (PFS) analyses were performed from the post-transplant assessment. Multivariable Cox models adjusted for cytogenetic risk, maintenance therapy, disease response at transplantation, International Staging System (ISS), and age. Results: Among 150 evaluable patients, 36 (24%) had high post-ASCT S-phase (≥2%) and 114 (76%) had low post-ASCT S-phase (<2%). Median age at ASCT was higher in the high S-phase group (64.5 vs 61.0 years; p=0.063), and advanced ISS stage (II/III) was more frequent (78% vs 57%; p=0.02). Cytogenetic risk, induction regimen, depth of response at transplantation, and maintenance therapy were similar between groups. Patients with high post-ASCT S-phase had significantly inferior PFS compared with those with low S-phase (median 17.0 vs 39.7 months; p=0.0003). On multivariable analysis, post-ASCT S-phase ≥2% remained independently associated with inferior PFS (HR 1.76, 95% CI 1.00–3.09; p=0.049). In an exploratory analysis among patients with paired S-phase assessments at the time of ASCT and post-ASCT, dynamic S-phase trajectories further stratified outcomes. Median PFS was longest in patients with persistently low S-phase (low→low; 39.7 months), intermediate in those converting from high to low S-phase (high→low; 27.2 months), and shortest in patients with newly emergent or persistently high post-ASCT S-phase (low→high: 15.0 months; high→high: 11.0 months) p=0.0019. Conclusions: Elevated proliferative activity of residual clonal plasma cells following ASCT identifies a biologically high-risk subset of MM patients with early relapse. Dynamic changes in post-ASCT S-phase further refine post-transplant risk stratification.

e19562 Background: Multiple myeloma is a chronic blood cancer in which patients often live for many years, yet the risk of death remains ongoing. While survival has improved over time, population-level studies that combine traditional survival analysis, advanced modeling techniques, and future burden projections are limited. Methods: We performed a population-based retrospective study using the Surveillance, Epidemiology, and End Results (SEER) database. Overall survival was evaluated using Kaplan–Meier analysis and Cox proportional hazards regression. Parametric survival modeling was conducted using Weibull regression to better characterize long-term mortality patterns. Machine-learning survival analysis was performed using random survival forests to assess the relative importance of clinical and demographic factors. Annual case counts were analyzed and projected through 2035 using time-series forecasting methods. Results: The study included 8,627 patients with multiple myeloma. Overall survival declined gradually over long-term follow-up, with approximately one-quarter to one-third of patients surviving at extended time points. Female patients experienced better survival than males. Significant survival differences were observed across racial groups, with Asian or Pacific Islander patients demonstrating the most favorable outcomes and American Indian or Alaska Native patients the poorest. In multivariable analyses, age, sex, race, and year of diagnosis were independently associated with survival. Parametric modeling closely mirrored non-parametric survival estimates and supported a time-dependent pattern of mortality. Machine-learning analysis identified year of diagnosis as the strongest predictor of survival, followed by age and race. Forecasting suggested that the burden of multiple myeloma will remain substantial through 2035. Conclusions: Multiple myeloma is associated with long-term survival but persistent mortality risk and ongoing demographic disparities. Combining traditional survival analysis with parametric and machine-learning approaches provides a more complete understanding of outcomes and highlights the sustained future burden of this disease, with important implications for clinical care and healthcare planning.

e19559 Background: Timely initiation of systemic therapy is critical in multiple myeloma (MM), yet real-world variation in time to treatment initiation (TTI) and its association with clinical outcomes, treatment-related toxicities, and supportive care utilization remain incompletely characterized. Methods: We conducted a retrospective cohort study using the Epic Cosmos database (2015–2025). Adults with MM were identified using ICD-10-CM code C90. TTI was defined as days from MM diagnosis to first exposure to systemic anti-myeloma therapy, including proteasome inhibitors, immunomodulatory drugs, or anti-CD38 monoclonal antibodies. Patients were stratified into TTI < 30 days (n = 90015), 30–60(n = 81190), and > 60 days(119,245). Primary outcomes included mortality, infection (sepsis or pneumonia), AKI within 30 days, DVT/PE, and bone marrow transplant (BMT). Secondary outcomes included hemodialysis initiation, febrile neutropenia, thrombocytopenia, herpes zoster reactivation, and use of bone-protective therapy (zoledronic acid, pamidronate, or denosumab) and antiviral prophylaxis (acyclovir/valacyclovir). Outcomes are presented as unadjusted percentages with 95% confidence intervals. Results: Mortality demonstrated a U-shaped association with TTI, occurring in 22.99%, 21.32%, and 21.32% of patients in the < 30-day, 30–60-day, and > 60-day cohorts, respectively. Infection rates were 16.42%, 17.11%, and 17.30%, while AKI < 30 occurred in 16.01%, 16.38%, and 16.49%. BMT utilization was highest in the 30–60-day cohort (19.14%) compared with < 30 days (18.28%) and > 60 days (18.21%). VTE rates increased modestly with delayed treatment (9.39%, 9.82%, and 10.10%). HD occurred in 3.15%, 3.08%, and 3.07% of patients. Febrile neutropenia occurred in 17.15%, 18.03%, and 17.55%, thrombocytopenia in 13.34%, 13.93%, and 13.86%, and herpes zoster reactivation in 1.21%, 1.29%, and 1.42%. Antiviral prophylaxis use was highest in the 30–60-day cohort (91.25%) compared with < 30 days (88.48%) and > 60 days (88.23%). Bone-protective therapy use was also highest in the 30–60-day cohort (31.68%) versus < 30 days (28.90%) and > 60 days (23.79%). Conclusions: In this large real-world analysis, initiation of systemic therapy within 30–60 days of MM diagnosis was associated with lower mortality, higher transplant utilization, and greater use of guideline-recommended supportive care compared with both earlier and delayed treatment initiation. Patients treated within 30 days appeared to represent a higher-acuity phenotype, while delays beyond 60 days were associated with lower supportive care uptake and higher thrombotic risk. These findings suggest that time to treatment initiation may reflect both disease severity and care delivery quality, and identify a potentially actionable window to optimize treatment pathways and supportive care in multiple myeloma.

e19543 Background: Multiple myeloma (MM) is a plasma cell malignancy characterized by immune dysfunction and end-organ damage. Emerging preclinical evidence suggests vitamin D is implicated in MM biology through effects on plasma cell differentiation and immune regulation. Vitamin D deficiency is common among patients with MM, yet its prognostic significance remains unclear. Clarifying its role may inform risk stratification and supportive management in MM. Methods: We conducted a retrospective cohort study using the multicenter TriNetX research network. Adults aged ≥20 years diagnosed with MM between 2011 and 2024 were included. Vitamin D status was defined using serum 25-hydroxyvitamin D levels, with deficiency defined as ≤30 ng/mL and normal levels defined as 31–80 ng/mL. Patients were stratified into two groups based on vitamin D status at the time of MM diagnosis. Propensity score matching (1:1) was performed to balance age, sex, race, baseline laboratory values, and clinically relevant comorbidities between groups. Kaplan–Meier survival analyses and Cox proportional hazards models were performed for outcome analyses. Results: A total of 36,273 patients with MM were included, of whom 42% (n = 15,262) had vitamin D deficiency. After propensity score matching, 14,023 vitamin D–deficient patients were well balanced with 14,006 non-deficient patients across baseline characteristics. In the matched cohort, the mean age was 64 years, 49% were female, and 64% were White. At five years, vitamin D deficiency was associated with a significantly higher risk of mortality (hazard ratio [HR] 1.63, 95% CI 1.54–1.72), with lower five-year overall survival (OS) compared with non-deficient patients (71.1% vs 80.8%, p<0.05). Vitamin D deficiency was also associated with increased risks of pneumonia (risk ratio [RR] 1.11), bacteremia (RR 1.22), and critical care admission (RR 1.30) (all p<0.05). Additionally, deficient patients had higher risks of acute kidney injury (AKI) (RR 1.19) and venous thromboembolism (RR 1.18) (both p<0.05). Notably, the risk of MM relapse was modestly increased among vitamin D-deficient patients (RR 1.07, 95% CI 1.01–1.13). No significant associations were observed between vitamin D deficiency and amyloidosis or pathologic fractures. In multivariable Cox regression, vitamin D deficiency remained independently associated with worse five-year OS (adjusted HR 1.60, 95% CI 1.52–1.67). Conclusions: This study highlights the negative impact of vitamin D deficiency in patients with MM. It identifies a high-risk subgroup of patients characterized by worse five-year OS, higher rates of serious infections, AKI, critical care utilization, and an increased risk of MM relapse. These findings suggest vitamin D deficiency as a clinically relevant prognostic marker in MM. Prospective studies are warranted to determine whether vitamin D level optimization can improve MM outcomes.

e19537 Background: Chimeric antigen receptor (CAR) T cell therapy is a paradigm shifting modality for relapsed/refractory multiple myeloma (MM). Yet national scale delineation of immune effector toxicities, cardiopulmonary and renal sequelae, and economic burden across demographic and payer strata has not been adequately characterized. Methods: The National Inpatient Sample (2018–2022) was queried to identify adult MM hospitalizations receiving CAR T through ICD-10-PCS codes. Cytokine release syndrome (CRS) [all grades - 2021–2022], immune effector cell–associated neurotoxicity syndrome (ICANS) [all grades – 2022], cardiac events and infections were identified through ICD-10 codes. Age was stratified into 21-40, 41-60, 61-80, >81 years. Payer groups were Medicare, Medicaid, Private and Uninsured. Races were White, African American, Hispanic and others [Pacific Islanders, Native Indians, Asians]. Chi-square analysis was performed and multivariate regression adjusted for demographics, comorbidities and hospital characteristics. Results: Across >7,000 weighted hospitalizations, mortality, any grade CRS and ICANS were statistically similar across age, race, and payer (p>0.05). However, CRS was numerically higher in Hispanic patients (78.6%) than in White (63.2%), African American (68.1%), and other minor races (60.0%) (p=0.339). ICANS grade 4 was numerically higher in Hispanic (5.3%) versus White (0.8%) (p=0.278). Mortality was numerically highest in other minor races (9.5%) versus White (3.6%), Hispanic (2.8%), and African American (0.0%) (p=0.179). Age-stratified analyses showed significant heterogeneity in arrhythmias (22.2% [21–40 years] to 28.6% [≥81 years]; p=0.021), attenuating after adjustment. By race, arrhythmias ranged from 8.3% (Hispanic) to 25.0% (White) (p=0.113). Other cardiac events including myocardial infarction, stroke and cardiogenic shock were similar across groups. Payer stratified pneumonia varied (p=0.010) with uninsured 23.8% versus Private 5.1%, Medicare 7.3%, and Medicaid 6.4%, without persistence in adjusted models. Sepsis and septic shock rates showed no differences. Hispanic patients had higher adjusted costs versus White (Odds ratio [OR] 1.3, 1.04–1.7; p=0.023). Age-stratified costs differed (p=0.032), with elevated cost in ≥81 years (USD 394,617) versus 21–40 (USD 229,862), 41–60 (USD 214,974), and 61–80 (USD 269,844) but it was not significant in adjusted analysis. Conclusions: In this national cohort, CRS, ICANS and mortality were broadly stable across strata, while cardiac events displayed select divergences with elevated rates of arrhythmias among the elderly population suggesting robust cardiac surveillance in these patients. Cost differentials were evident with higher costs among Hispanic and elderly patients warranting validation in larger, prospectively harmonized datasets.

e19536 Background: Chronic kidney disease (CKD) may impair physiologic resilience during chimeric antigen receptor (CAR) T-cell therapy for multiple myeloma (MM). While cytokine response syndrome (CRS) and immune cell-associated neurotoxicity syndromes (ICANS) have been described in MM CAR-T recipients with CKD, the broader cardiopulmonary, infectious, renal, and economic implications of CKD remain insufficiently defined. We examined the national impact of CKD on mortality, immune cell effector toxicities, organ dysfunction, infections and resource utilization. Methods: Adult MM hospitalizations receiving CAR T-cell therapy were identified from the National Inpatient Sample (2018–2022) using ICD-10-PCS codes. Patients with ESRD were excluded. CKD was categorized as CKD3a+ (eGFR <60 mL/min) versus no CKD/CKD1–2. Outcomes included in-hospital mortality, CRS (2021–2022), ICANS (2022), cardiac arrhythmias, acute kidney injury (AKI), renal replacement therapy, respiratory failure, infections and total hospitalization cost (calculated using TOTCHG variable and adjusted cost to charge ratio). Comparative analysis was done using chi-square testing. Multivariate analysis adjusted for demographics, comorbidities, and hospital characteristics. Results: Among 2,045 weighted MM CAR-T hospitalizations, 7.6% had CKD3a+. Overall CRS rates were similar (66.7% vs 64.9%; p=0.839) between CKD3a+ vs no/CKD1-2. Overall ICANS rates were also comparable (16.7% vs 17.3%; p=0.941). Differences in CRS/ICANS grades were not significant. CKD3a+ patients experienced sharply higher AKI (58.1% vs 13.0%; p<0.001; adjusted odds ratio [OR] 9.2, p<0.001). Renal replacement therapy was more frequent in CKD3a+ but non-significant (3.2% vs 0.8%; p=0.196). Acute respiratory failure was more frequent (9.7% vs 2.9%; p=0.045) in patients with CKD. Cardiac arrhythmias were numerically higher but non-significant (25.8% vs 20.6%; p=0.527; adjusted OR 1.3, 95% CI 0.4–4.9; p=0.673). Infections were amplified, including gram-negative bacteremia (3.2% vs 0.3%; p=0.026), sepsis (9.7% vs 2.6%; p=0.040), and septic shock (3.2% vs 0.3%; p=0.027) in patients with CKD. Inpatient mortality was numerically higher (6.5% vs 1.9%; p=0.101), though nonsignificant after adjustment (OR 6.9; p=0.319). Hospital costs were substantially higher in CKD3a+ (USD 346,769 vs 239,175; p=0.006), though not significant in adjusted models (OR 1.3; p=0.120). Conclusions: CKD3a+ is associated with markedly increased AKI, higher respiratory failure and infections, with a trend towards higher hospitalization costs. Inpatient mortality, CRS and ICANS rates were similar. CKD3a+ represents a significant vulnerability that amplifies downstream complications in MM CAR-T recipients, warranting enhanced pre-treatment risk stratification, infection surveillance and renal-preserving strategies.

e19504 Background: Initiation of bsAbs requires SUD with close monitoring, typically in IP settings, to mitigate early toxicities. As bsAb use expands, it is crucial to understand the financial viability for administering bsAbs, particularly non–PPS-exempt hospitals paid via a capitated, DRG-based method where costs may exceed payout. We compared net costs and payments for Medicare pts initiating bsAbs in the IP setting at non-PPS-exempt hospitals and explored cost variations for hospital characteristics and adverse events (AEs). Methods: Using Medicare FFS Parts A/B claims (10/25/21–10/20/24), pts ≥65 years with MM, IP bsAb initiation, and 12 mos continuous pre-index coverage were identified. Pts receiving other MM therapies <30 days post-index or treated in PPS-exempt hospitals were excluded. Hospital costs were estimated by applying revenue center–specific Medicare cost–charge ratios from CMS Hospital Cost Reports to IP facility charges. Outpatient (OP) bsAb costs were estimated using ASP/unit administered/wasted at the time of the claim. Costs for other OP services were estimated using revenue center–specific cost–charge ratios. Medicare payments were defined as total allowed amounts on IP and OP claims, and net cost as payments minus estimated costs. IP resource use and net cost recovery by academic vs nonacademic hospital, length of stay (LOS), and AEs were analyzed. Results: Of 3074 pts with a bsAb claim, 1129 met inclusion criteria. Mean IP LOS was 9 days (range 1–68). Hospital mean estimated IP cost/day for index hospitalization was $3963. Mean estimated costs for index hospitalization were $36964 per pt for IP SUD and $28366 for mean Medicare payments with a mean loss of $8598 per pt (median −$5616). Payments exceeded estimated costs on average by $2764–8149 for 1–4-day hospitalizations and roughly equal costs for hospitalizations at 5 days. For pts with LOS of 6–9 days and ≥10 days, payments were lower than costs by $6735 and $16659, respectively, suggesting a loss. For pts with subsequent OP administrations (74%) observable in this sample, cumulative payments and costs were assessed following the index hospitalization, mean cumulative longitudinal payments were ≥ cumulative costs within 2–3 mos. IP stay net losses were higher among pts with infection (−$6406 vs no infection), neutropenia (−$7006), and febrile neutropenia (−$10018). Payment patterns and estimated costs were similar across hospital types. Conclusions: Results suggest a large financial burden on non-PPS-exempt hospitals for IP-administered bsAb SUD. While shorter LOS for IP SUD generally did not result in financial losses, longer LOS was associated with disproportionately higher costs relative to payments. Care models (e.g. OP SUD) are key to manage initiation costs and ensure delivery of care for bsAbs remains financially sustainable.

e19503 Background: The anti-B-cell maturation antigen (BCMA) antibody-drug conjugate (ADC) belantamab mafodotin is approved in the USA and EU for relapsed/refractory multiple myeloma (RRMM). Understanding treatment options and patient outcomes following ADC failure is clinically important. This study describes post-ADC treatment patterns and clinical outcomes in real-world patients with RRMM. Methods: Adult patients with MM who received an ADC and initiated ≥1 subsequent line of therapy (LOT) were included. The index date was the start of the first post-ADC LOT. Data were obtained from chart reviews at International Myeloma Foundation International Myeloma Working Group (IMF IMWG) academic sites, and US electronic health records from largely community sites (COTA and Guardian Research Network [GRN]). Patient characteristics and index regimens were summarized descriptively. Time to next treatment (TTNT) and overall survival (OS) were estimated with the Kaplan-Meier estimator. Results: The IMF IMWG cohort (n=40) had a mean age of 70.8 years, median of 7 prior LOTs and 82.5% were triple-class refractory (TCR). Overall, 85% received ADC monotherapy (70% belantamab mafodotin) and 15% combination therapy. Pre-ADC and not considering corticosteroids, patients were commonly exposed to lenalidomide (R; 100%), bortezomib (V; 92.5%), daratumumab (D) and pomalidomide (P; 90% each). Over a median follow-up of 26 months after index date, 29 unique index post-ADC regimens were reported, frequently selinexor (27.5%) and bispecific antibodies (15%). CAR T-cell therapy was administered to 5%, with 60% re-treated with a pre-ADC drug class (PI/IMiD/anti-CD38) after ADC. Median (95% CI) TTNT and OS were 10.8 (7.0–20.6) and 19.0 (13.4–25.1) months, respectively. The COTA-GRN cohort (n=39) had a mean age of 67.5 years, median of 8 prior LOTs, and 51.3% were TCR. Overall, 56% received ADC monotherapy (belantamab mafodotin) and 44% combination therapy. Pre-ADC and not considering corticosteroids, patients were commonly exposed to D and R (97.4% each), and carfilzomib, V and P (94.9% each). Over a median follow-up of 9.2 months, 32 unique index post-ADC regimens were reported, frequently selinexor (23.1%) and venetoclax (17.9%) based; 0% received CAR Ts and 54% were re-treated with a pre-ADC drug class (PI/IMiD/anti-CD38) after ADC. Median (95% CI) TTNT and OS were 4.9 (2.8–non-estimable [NE]) and 12.0 (4.9–NE) months, respectively. Conclusions: Findings highlight that most patients with heavily pretreated BCMA-ADC exposed MM were re-treated with similar classes. Academic centers used novel therapies (ie, CAR T, bispecific antibodies) more often and their patients had longer survival than those treated at community sites. However, clinical outcomes remained sub-optimal, emphasizing the unmet need for effective, accessible post-ADC treatments.