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Introduction: Acute kidney injury (AKI) due to cast nephropathy is a medical emergency that leads to a diagnosis of myeloma in less than 3% of cases, but up to 30% of patients develop kidney impairment during the course of their disease. Currently, studies aiming to identify parameters that correlate with kidney function recovery and response to myeloma are limited due to small sample size or single center reports. We have therefore initiated an international collaboration and collected a large number patients (pts) from 16 participating centers. Objectives: To assess the impact of pts and disease characteristics and treatment-specific factors on renal outcome and overall survival and to validate the IMWG criteria for renal response in pts with cast nephropathy and newly diagnosed MM. Patients and Methods: Three-hundred forty-three pts (median age: 65.5 range 35-93 yrs) with newly diagnosed MM and an eGFR <40ml/min/1.73m2 have been selected from 704 pts that had been enrolled in the database hosted by RedCap. Eligibility criteria were a diagnosis of AKI due to cast nephropathy diagnosed either by kidney biopsy (n=119) or on clinical criteria (AKI in the setting of involved free light chain concentration of ≥500 mg/L), newly diagnosed multiple myeloma, >2 cycles of therapy, time and type of therapy, best eGFR and best myeloma response available. Results: Median follow up was 36.9 months. Myeloma therapy resulted in renal CR, and PR as defined by the IMWG criteria in 131 (38.2%) and 57 (16.6%) pts, respectively, 54 (15.7%) and 82 (23.9%) pts had minor response or no response, respectively. Nineteen (5.5%) pts were not classifiable by the IMWG response criteria (pts with eGFR 15-<30, with increase to eGFR to ≥30-<40). An eGFR of >60, ≥30-<60, ≥15-<30, and <15ml/min was achieved by 131 (38.2%), 112 (32.7%), 67 (19.5%), and 33 (9.6%) pts respectively. Myeloma response (≥VGPR) correlated significantly with renal response (≥PRrenal) (OR 1.64, CI 1.05-2.56, p=0.03) and with OS compared to no myeloma response (median 89.7 vs. 39.7 months, HR 2.12, CI 1.55-2.89, p<0.0001). A >50% reduction in FLCs from baseline to treatment cycle 2 (OR 5.92, CI 2.15-19.23, p=0.001) and cycle 3 (OR 5.25, CI 2.15-19.25, p=0.006) were strongly associated with renal response Median OS was 69.6 months (CI 55.4-89.7). Forty-three pts died within the first 12 months of treatment and additional 146 during further FU. Pts with a best GFR of >15ml/min had a significantly longer OS compared to those with GFR <15ml/min (median: 77.9 vs 31.9 months, HR 1.85, CI 1.16-2.94, p=0.01). The comparison of survival of pts with different renal response groups and with the best eGFR showed no statistically significant difference (log rank p=0.1, long rank p=0.057, respectively). Other factors that correlated with longer OS were bortezomib-based therapy (77.9 vs. 44.0 months, HR 1.59, CI 1.05-2.38, p=0.03), M-protein isotype with κ as compared to l light chain type (84.9 vs. 51.4 months, HR 1.47, CI 1.09-2.00, p=0.013), and higher hemoglobin (HR 1.16, CI 1.06-1.26, p=0.001). In contrast, hypercalcemia which was noted in 101 (29.4%) pts (HR 1.10, CI 1.03-1.18, p=0.005), ISS stage III vs. I-II (57.8 vs. 126.2 months, HR 2.26, CI 1.22-4.17, p=0.009), and ECOG status 3+4 vs. 2 vs. 0+1 (24.4 vs. 44.6 vs. 103 months, HR 2.83, CI 2.15-3.74, p<0.0001) were associated with shorter OS. Hypercalcemia, correlated with renal response (OR 1.27, CI 1.12-1.44, p=0.0002), and best eGFR ≥46.4 ml/min (median dichotomized) (OR 1.28, CI 1.14-1.46, p<0.0001). 119 (34.7%) pts required initial dialysis, OS was significantly longer in those who achieved best eGFR levels of >15ml/min. (77.6 vs 31.9 months, HR 0.54, CI 0.34-0.86, p=0.01); 64 (53%) pts discontinued dialysis. Conclusion: Myeloma response correlated with renal response as defined by IMWG criteria. A >50% reduction in FLCs from baseline to treatment cycle ≥2 was strongly associated with renal response. OS was longer in pts with renal response, in pts receiving bortezomib-based therapy, and in pts with kappa light chain M-proteins. Hypercalcemia was frequent (29.4%), and associated with higher renal response rate and best eGFR, but shorter OS. Pts on dialysis who achieved eGFR >15ml/min had better survival. Fast diagnostic work up, rapid treatment initiation and achieving significant myeloma response (≥VGPR) is essential to prevent irreversible kidney damage. Including novel immunotherapies may further improve outcome.

Introduction Genomic alterations are common in multiple myeloma precursor stages, monoclonal gammopathy of undetermined significance (MGUS) and smoldering multiple myeloma (SMM). However, commonly used stratification systems do not include somatic alterations that play a role in the disease. To address this clinical need, we generated a comprehensive genomic map of MM and precursors by harmonizing and analyzing mostly WGS data from 1,030 patients. We used these data to define a simple MM-like score, that is able to discriminate which premalignant patients are at risk to progress. Methods We collected, enriched, and performed WGS of tumor plasma cells and matched normals from 138 participants with MGUS or SMM, including those in low, intermediate, and high-risk groups. We combined our precursor dataset with genomic profiles from MM (n=20) and external sources of 872 individuals with MGUS (n=18), SMM (n=62), and MM (n=792) for a cohort of 1,030 individuals with MM or a precursor condition. In 16 patients, we could perform WGS serially from the bone marrow or circulating tumor cells (n=39) and reassess the presence of mutations. Results To develop a simple score that reflects the similarity of precursor genomes to full-blown multiple myeloma disease, we searched among the 107 common driver events (occurring in >1% of patients) and initiating translocations for ones that are differently altered in precursor conditions versus MM. We found 26 differentially altered events: only MAF and MAFB translocations were enriched in MGUS/SMM whereas 24 events were enriched in MM, including known drivers MYC, KRAS, FAM46C, del(1p) and gain(1q). We then defined a simple “MM-like” score for each tumor as the number of MM-enriched drivers minus the number of MGUS-enriched drivers. As expected, the MM-like score in our cohort increased throughout MM development (MM-like score median of 1 in MGUS, 2 in SMM, and 3 in MM). Even among SMM patients, we found a gradual increase of the MM-like score from low- (median=1), to intermediate (median=2), to high-risk (median=3) groups that match the overall medians in MGUS, SMM and MM (p=2e-5). We tested whether the MM-like score can be used to estimate risk of progression. Among untreated SMM patients characterized with WGS, an MM-like score greater than 2 was associated with a higher likelihood of progression (HR=5.3, P=0.03). Using an independent dataset of 87 patients with SMM, we were able to validate that a MM-like score greater than 2 was indeed associated with a higher risk of progression (HR=3.3, P=5x10-5). 11 patients who did not progress and for whom we performed longitudinal WGS, has stable MM-like scores over time, while three patients clinically progressed and their MM-like score increased at the time of progression (due to newly detected mutations in KRAS and NRAS). For the two remaining patients, their MM-like score increased, and we observed growth of the subclone that acquired the additional MM-like driver. In the first patient with MGUS/low-risk SMM, a novel hyperdiploid clone was detected in addition to a TP53 bi-allelic hit and t(11;14) translocation and was shown to increase in clonal fraction with tumor burden (light chains +104% within three years). In the second non-progressor with an increasing MM-like score, a novel del(1p) was detected, and other subclones in the phylogenetic tree either shrank or were stable over three years. Finally, because the MM-like score can place tumors on a gradual axis of evolution towards a more genomically-mature tumor, we tested whether the MM-like score was also predictive of survival in patients treated with a newly diagnosed MM. To do so, we calculated the MM-like score in patients from the publicly available CoMMpass database. We found that an increased score significantly correlated with shorter progression-free survival (median PFS1: 3 years in high score, versus 5 years in low/intermediate score; p=1e-3) and overall survival (median OS: 4.5 years in high score, versus not reached in low/intermediate score; p=1e-5). Conclusion Overall, we demonstrate that it is possible to stratify precursor stages of MM by discovering drivers, detecting those that are associated with the stage of the disease, and defining a genomically-based score that can be used to assess risk of progression and is easy to implement in the clinic.

Introduction: Scant data exist on prognostic factors, survival and treatment (Tx)-related outcomes in SCNSL. We conducted a multicenter international analysis to identify prognostic factors and outcomes in SCNSL at diagnosis (de novo), or after frontline Tx (1L) either with (concomitant) or without (isolated) systemic (syst) relapse. Methods: This study collected data from patients (pts) treated between 2001-2023 at 35 centers. Overall (OS) and progression-free survival (PFS) were calculated from SCNSL diagnosis to first event (death for OS, relapse/death for PFS) or last follow-up. Uni- (UVA) and multivariable (MVA) Cox analyses were performed to assess prognostic factors; Kaplan-Meier method was used to estimate survival. Results: 1173 (US: 863, UK: 273, Canada: 37) pts with SCNSL were included. Baseline characteristics were median age: 62 years (interquartile range 52.5-69), male sex: 58.7%, elevated LDH: 71.1%, stage III/IV: 88.6%, HIV: 3%, transformed LBCL (tLBCL): 13.8%, non-germinal center B-cell like (non-GCB) subtype: 52.3%, double expressor (DE): 40%, MYC rearrangement (MYC-R): 28.3%, MYC/BCL2 double hit: 16.6%, MYC/BCL2/BCL6 triple hit (TH): 6.1%. Among 522 pts with de novo SCNSL, 84.2% had involvement of a single CNS compartment (44.7% brain parenchyma; 40.4% leptomeningeal [lepto]). 1L regimens included 36.2% R-CHOP with high-dose methotrexate (HD-MTX), 12.5% MARIETTA-type, and 9.8% R-CODOX-M/IVAC; 54.6% received intrathecal chemotherapy. Consolidation Thiotepa-based autologous stem cell transplant (TT-ASCT) occurred in 15.3%. The majority of pts who underwent TT-ASCT had previously achieved CR or PR in syst (92.5%) and CNS (72.5%) compartments. At median follow-up 25.7 months (mos), subsequent relapse was observed in 27.5% TT-ASCT recipients: 36.3% had isolated CNS, 27.4% syst, and 36.3% concomitant. 588 pts presented with SCNS after 1L (66.2% isolated, 33.8% concomitant). Brain parenchyma involvement was observed in 56.8%, lepto in 22.6%. Tx included 31.6% HD-MTX combination (eg, R-MPV, MTR); 18.4% HD-MTX +/- rituximab; 16.2% MARIETTA-type; and 9.4% platinum-based regimen. Consolidation TT-ASCT occurred in 22.4% (n=132), and 13.8% (n=81) received CAR-T cell therapy (excluding subsequent relapses in de novo group). Syst (65.1%) & CNS (69.1%) responses (CR/PR) were higher before TT-ASCT compared to CAR-T cell (49.5% & 54.5%, respectively). After TT-ASCT, 52 pts (39.3%) relapsed, mainly in the CNS (n=30, 57.7%), with only 4 (7.7%) concomitant. After CAR-T, 48 pts (59.3%) relapsed: 15 (31.2%) isolated in CNS and 15 (31.2%) concomitant. 12-month cumulative incidence of relapse (with death as competing risk) was 21.1% after TT-ASCT and 55.8% after CAR-T. In 63 pts (5.4%), the first CNS event occurred >2 lines of Tx. With median follow-up of the entire cohort of 24.6 mos, median PFS and OS were 11 and 21 mos, respectively. mPFS and mOS were significantly better in pts with de novo SCNSL (13.4 & 47.4 mos) compared to SCNSL after 1L (10.4 & 14.2 mos) and >2 lines of Tx (6.5 & 9.7 mos); P<0.0001. Factors associated with significantly shorter OS in UVA across all presentations were age >60, male sex, GCB subtype, MYC-R, tLBCL, DE, TH, elevated LDH, ECOG PS ≥2, SCNSL after 1L (vs. de novo), and failure to achieve syst/CNS response to 1L. Of these, age >60, male sex, MYC-R, ECOG PS ≥2, and failure to achieve response to 1L remained significant in MVA. In de novo cases, age >60, DE, ECOG PS≥2, and failure to achieve syst/CNS response to 1L were associated with poorer OS; for pts with SCNSL after 1L, age >60, GCB subtype, and ECOG PS ≥2 were significant. Pts treated with HD-MTX-based regimens after 1L experienced longer OS than those treated with platinum regimens or high-dose cytarabine. In de novo cases, TT-ASCT was significantly associated with longer OS (HR=0.58; P=0.025) in MVA after adjusting for significant factors, 1L type, and response. For SCNSL at relapse, TT-ASCT (HR=0.34; P<.0001) and isolated SCNSL presentation (vs. concomitant HR=0.70, P=0.007) were associated with longer OS, adjusting for significant factors, type of second-line Tx, & site of CNS relapse. Conclusions: This study represents the largest analysis of SCNSL inclusive of all modes of presentation. Concomitant SCNSL at relapse was associated with poor outcomes, while TT-ASCT consolidation was associated with improved OS in de novo & relapsed disease. Despite advances in LBCL SCNSL remains an unmet therapeutic need.

Background: Although advanced stage cHL typically has excellent disease outcomes, 20-30% of patients (pts) experience treatment failure. In addition, decision-making is challenging given varying treatment options and incomplete prognostic data across the disease course. Pre-treatment factors, such as those incorporated into the Advanced Stage Hodgkin Lymphoma International Prognostication Index (A-HIPI), predict 5 year (y) overall survival (OS) and progression-free survival (PFS) (Rodday JCO 2023). Other than interim PET (iPET) results, it is unknown what factors influence cHL disease states mid-therapy. Using multistate modeling (MSM) and individual pt data from the HoLISTIC Consortium, we refined prognostication across the cHL disease course, specifically assessing the relationships between A-HIPI, iPET and end of treatment (EOT) response, and whether the A-HIPI and iPET provide independent prognostic information. Methods: We analyzed 1240 pts aged 18-65y with newly diagnosed Stage IIB, III or IV cHL treated on 2 advanced stage PET-adapted trials (RATHL, SWOG0816). All pts first received 2 cycles of ABVD; those with a negative iPET (Deauville score (DS) ≤3) received ABVD or AVD, and those with a positive iPET (DS >3) received BEACOPP. In contrast to other methods, MSMs incorporate multiple disease states into one model, account for censoring and competing risks, and estimate transitions between disease states using different covariates. Our MSM had 6 states: diagnosis, negative iPET, positive iPET, EOT non-progression (e.g., DS ≤ 3), treatment failure, and death. Treatment failure included progression or relapse. All pts start at the diagnosis state and can transition to other states without return to prior states. Transition states with <5 events were excluded. The MSM was estimated using a multivariable Cox model with censoring at 5y. Covariates were the 5y PFS A-HIPI (comprised of stage and continuous age, lymphocyte count and albumin), which was included for all transitions, and iPET, which was included for transitions from EOT non-progression and from treatment failure. Higher scores on the 5y PFS A-HIPI indicate lower risk of progression or death; the A-HIPI was modeled for a 1 standard deviation (SD) increase. We calculated probabilities of 5y treatment failure for 4 sample pts based on low (70) and high (85) A-HIPI scores, positive and negative iPET, and EOT non-progression. Results: Median age was 33y (Q1=25, Q3=45), 56% were male, 23% were stage IIB, 40% III and 37% IV, and mean A-HIPI was 77 (SD=7). Median follow-up was 75 months (Q1=53, Q3=92). At iPET, 80% (95% CI 78%, 83%) were negative and 16% (95% CI 14%, 18%) were positive. At EOT, 90% (95% CI 89%, 92%) were in the non-progression state. At 5y, 75% (95% CI 73%, 78%) were in the non-progression state, 16% (95% CI 14%, 19%) had experienced treatment failure, and 9% (7%, 11%) had died. Better A-HIPI scores (per SD) were associated with lower rates of transitioning from diagnosis to positive iPET (HR=0.80, p<0.01) and from positive iPET to treatment failure (HR=0.58, p=0.04). Better A-HIPI scores (per SD) were also associated with lower rates of transitioning from EOT non-progression to treatment failure (HR=0.78, p<0.01) and from treatment failure to death (HR=0.64, p<0.01), adjusting for iPET. Positive iPET was associated with an increased rate of transitioning from EOT non-progression to treatment failure (HR=1.90, p<0.01), adjusting for A-HIPI. The probability of 5y treatment failure for 4 sample pts was: 25% for low A-HIPI and positive iPET; 20% for high A-HIPI and positive iPET; 13% for low A-HIPI and negative iPET; and 12% for high A-HIPI and negative iPET. Conclusions: We created a novel MSM that refines prognostication across the cHL disease course by incorporating pre- and post-treatment factors (e.g., iPET) to estimate transitions to future disease states. Although the A-HIPI was developed using pre-treatment factors to predict 5y OS and PFS, we found that it was also associated with transitions to interim disease states, including iPET and EOT response. The A-HIPI and iPET each provided independent prognostic information, supporting the use of both in estimating cHL outcomes. Future analyses will develop clinical prediction models using MSMs that also incorporate varying frontline and salvage treatments and treatment-specific late effects, with the goal of providing individualized information across the disease course.

AbstractClinical recognition of primary mitochondrial disorders (PMD) is difficult due to the clinical and genetic heterogeneity. Whereas lactate has low sensitivity and specificity, in structured clinical studies growth differentiation factor 15 (GDF15) has shown promise with elevations in mitochondrial DNA (mtDNA)‐related PMD, but its specificity has been questioned. In a tertiary care hospital‐wide study, medical records were retrospectively reviewed from 418 cases where GDF15 levels were obtained by clinicians. Patients were classified into patients with PMD due to mtDNA‐related defects (mtDNA maintenance, mtDNA deletions, and mtDNA‐encoded tRNA variants), PMD due to structural defects or other nuclear causes, and in non‐mitochondrial disease. Patients with liver disease or systemic critical illness were excluded. GDF15 was assayed in a clinical laboratory with a cutoff of 750 ng/L. There were 38 mtDNA‐related PMD (GDF15 >750 pg/mL in 76%), 35 other nuclear DNA‐encoded PMD or structural subunits (31% elevated GDF15), 309 non‐mitochondrial disorders (13% elevated GDF15). Based on the highest Youden J‐index, the optimal cut‐off value to identify these target mtDNA‐related disorders was 815 pg/mL, with sensitivity 76%, specificity 88%, positive predictive value of 41% and negative predictive value of 97%. At this optimized cutoff level, mtDNA‐encoded PMD patients had elevated GDF15 in 76%, nuclear DNA‐encoded PMD in 26%, and non‐mitochondrial disorders in 11% of patients. Thus, in a real‐life clinical setting, after excluding abnormal liver function and critical illness, GDF15 had good clinical utility increasing the odds at predicting mtDNA‐related primary mitochondrial disorders 14‐fold, but not for structural or other nuclear‐encoded primary mitochondrial disorders.

Abstract Introduction The Geriatric Emergency Care Applied Research Network 2.0‐Advancing Dementia Care (GEAR 2.0‐ADC) aims to advance research efforts to improve the emergency care of persons living with dementia (PLWDs). Objective To support this objective, GEAR 2.0‐ADC convened a virtual consensus conference to prioritize emergency care research opportunities for PLWDs inclusive of perspectives of PLWDs to ensure identification of research gaps in response to their experiences and priorities. Inclusion of PLWDs as research partners is increasingly recognized as a best practice, however, approaches to facilitating consensus participation are lacking. Methods Best practices for supporting the engagement of PLWDs in a consensus conference, applied across its three phases (pre‐conference, during the conference, and post‐conference), include: establishing a learning environment focused on research priorities before the event, presenting information in ways that align with participants' learning preferences while accommodating cognitive impairments, and providing multiple opportunities and methods for gathering post‐conference feedback from PLWDs. Results These strategies were identified by PLWDs and care partners (CPs) through semi‐structured interviews, who were involved in the convening process, aimed at exploring ways to enhance facilitation techniques for participants. Conclusion Additionally, these summarized insights aim to encourage the use of community‐engaged approaches in discussions and consensus‐building around research priorities in emergency care, particularly for PLWDs and their CPs.

ABSTRACTCellular senescence is a biological mechanism of aging and age‐related diseases. The aim of this study was to examine whether senescence biomarkers are associated with frailty and physical function trajectories in patients undergoing kidney transplantation (KT). We also discussed the relationship between senescence biomarkers and KT function. In this multicenter study, we prospectively assessed plasma levels of senescence biomarkers, frailty as measured by the Physical Frailty Phenotype, and physical function as measured by the Short Physical Performance Battery prior to KT. Frailty, physical function, and KT function were also measured 1 year after KT. Variable associations were assessed using Cox and relaxed least absolute shrinkage and selection operation regression. The cohort consisted of 197 participants (mean age 53 ± 13 years, 61.4% male, and 80.2% White race). Higher pre‐KT levels of macrophage‐derived chemokine (MDC/CCL22) and growth differentiation factor‐15 (GDF‐15) were independently associated with less improvement in frailty and/or physical function during the first year after KT. Higher pre‐KT levels tumor necrosis factor receptor superfamily member 6 (FAS) and MMP‐9 levels were independently associated with lower KT function one year after KT. Pre‐KT cellular senescence may contribute to frailty, physical function, and kidney function trajectories during the first year after KT.

Abstract Objective An accurate evaluation of behavioral responsiveness during and after seizures in people with epilepsy is critical for diagnosis and management. Current methods for assessing behavioral responsiveness are characterized by substantial variation, subjectivity, and limited reliability and reproducibility in ambulatory and epilepsy monitoring unit settings. In this study, we aimed to develop and implement a novel mobile platform for deployment of automated responsiveness testing in epilepsy—the ARTiE Watch—to facilitate standardized, objective assessments of behavioral responsiveness during and after seizures. Methods We prospectively recruited patients admitted to the epilepsy monitoring units for diagnostic evaluation and long‐term video‐electroencephalographic monitoring at Mayo Clinic and Yale New Haven Hospital. Participants wore the ARTiE Watch, a smartwatch paired with custom smartphone software integrated with cloud infrastructure allowing for remote activation of standardized assessment on the participants' smartwatches. The assessment consisted of 18 command prompts that test behavioral responsiveness across motor, language, and memory domains. Upon visually identifying an electrographic seizure during EMU monitoring, the BrainRISE platform was used to deploy the ARTiE Watch behavioral testing sequence. Responsiveness scoring was conducted on smartwatch files. Results Eighteen of 56 participants had a total of 39 electrographic seizures assessed with the ARTiE Watch. The 18 subjects with ARTiE Watch‐tested seizures had a total of 67 baseline (interictal) ARTiE Watch tests collected for analysis. The analysis showed distinct ARTiE Watch behavioral responsiveness phenotypes: (1) decreased responsiveness across all ARTiE Watch commands during seizure (ictal–postictal) periods compared (to baseline ( p < .0001), (2) decreased responsiveness in bilateral tonic–clonic seizures compared to baseline ( p < .0001) and compared to focal seizures ( p < .0001), and (3) decreased responsiveness during focal impaired awareness seizures compared to baseline ( p < .0001) and compared to focal aware seizures ( p < .001). Significance ARTiE Watch behavioral testing deployed utilizing a mobile cloud‐based platform is feasible and can provide standardized, objective behavioral responsiveness assessments during seizures.