Citations

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.

Introduction: Myeloma response to treatment can be biochemical, pathological, or radiological, with pathological assessments being invasive. Next-generation blood flow (PBF) for assessment of circulating tumor plasma cells (CTCs) has shown promising results as a prognostic in Multiple Myeloma (MM) patients. CTC detection via PBF has a potential to serve as non-invasive method for assessing pathological burden of disease and response to treatment. Comparing CTC responses to the International Myeloma Working Group (IMWG) criteria will further help to understand PBF's utility in predicting response to therapy. Patients and Methods: The study conducted is a retrospective observational study. We included patients with MM treated at Mayo Clinic from 01/01/2011 to 12/31/2019 with CTC records available at the time of best response (BR) to frontline therapy. The CTC values were expressed as the number of plasma cell events per 150,000 Peripheral Blood Mononuclear Cells (CD38, CD138, CD19, CD45, Kappa, Lambda). The CTC levels were compared across all response(IMWG Criteria) groups at BR, and at baseline. The CTC response was expressed as % CTC decrease at BR from baseline. Time-to-event analyses utilized the Kaplan Meier method and Cox-proportional hazards models, with comparisons made using the log-rank test. Results: We identified 621 patients with CTC data at the time of BR to frontline therapy. Of these, 148 (24%) had baseline CTC data from diagnosis. The median age at diagnosis was 62.3 (27.2-83.7). The median follow-up was 66.15 months; the distribution of patients by treatment class is as follows- Alkylator: 0.8%, PI(Proteasome Inhibitor)+Cyclophosphamide: 27.4%, IMid: 12.7%, PI+IMid(Immunomodulator): 55.9%, PI+IMid+antiCD38: 3.2%; 378 patients (78.8%) underwent an autologous transplant. BR to initial therapy was sCR/stringent Complete Response (10, 1.6%), CR (230, 36.9%), VGPR/Very Good Partial Response (224, 36.1%), PR (123, 19.8%), MR/Minimal Response (12, 1.9%), SD/Stable Disease (14, 2.3%), PD/Progressive Disease (8, 1.3%). In the study, 64 patients (10.31%) had detectable CTCs at their BR. The distribution of CTCs across the different response categories was as follows: none (0%) in sCR, 3 patients (1.3%) in CR, 18 patients (8%) in VGPR, 24 patients (19.5%) in PR, 8 patients (66.7%) in MR, 6 patients (42.9%) in SD, and 5 patients (62.5%) in PD. The median CTC counts and their interquartile ranges for these categories showed significant variability: CR had a median of 46 (IQR: 28.5, 923), VGPR had 39.5 (IQR: 15.5, 111.25), PR had 47 (IQR: 22.75, 82.5), MR had 55 (IQR: 28.5, 85), SD had 96.5 (IQR: 22.25, 218.75), and PD had 317 (IQR: 57, 415). This Analysis of Variance (ANOVA) for response-wise distribution of CTC was <0.01. Response was dichotomized as PR and above for sCR, CR, VGPR, PR and less than PR for MR, SD and PD. Median Overall Survival(OS) for PR and above was 127.8 months (vs less than PR 56.7 months, p=0.01). Median OS for CTC+ at BR was 56.7 months (vs 134.8 for CTC negative, p=0.01). On multivariate analysis, presence of CTC at best response (Hazards Ratio = 2.9, n=1.1-2.9), RISS staging at diagnosis (Hazards Ratio = 2.35, n=1.5-3.05), less than PR (Hazards Ratio =1.8, 1.1-2.9) were independent predictors of inferior OS. In patients with data for CTC available at both baseline and at BR to frontline therapy (n=148), 110 had CTC detectable at diagnosis. Among patients in various response categories, a complete disappearance of CTCs was observed in sCR (n=3, 75.0%), CR (n=36, 69.2%), VGPR (n=38, 64.4%), and PR (n=14, 60.9%). CTC responses greater than 90% were noted in VGPR (n=3, 5.1%), PR (n=2, 8.7%), and SD (n=2, 40.0%). No CTC response was reported in sCR (1, 25.0%), CR (16, 30.8%), VGPR (2, 3.4% and 13, 22.0%), PR (3, 13.0% and both 2, 8.7%), SD (1, 20.0% and both 2, 40.0%), MR (1, 50.0%), and PD (1, 33.3% and 1, 50.0%, respectively). The median OS for those with a CTC response was 112.4 months vs 28.2 months for no response. (p=0.01). Conclusion: The presence of CTC at best response is an independent prognostic marker for inferior OS. Depth of response to frontline therapy correspond to a high rate of clearance of CTCs. Presence of CTC at best response provides independent prognostic value beyond the depth of response. A complete clearance of CTC at best response is associated with improved OS. CTC levels have not been corrected for WBC counts and may not be applicable in all settings.

INTRODUCTION Primary plasma cell leukemia (pPCL) is a rare and aggressive form of multiple myeloma (MM) with poor survival outcomes. Fluorescence in situ hybridization (FISH) evaluation is essential for the initial risk stratification in MM, and the presence of multiple high-risk (HR) cytogenetic abnormalities by FISH portends a worse prognosis in MM. We have previously observed that the presence of HR cytogenetic abnormalities by FISH at diagnosis is known to confer a poor overall survival (OS) in patients with pPCL. However, less is known about the cumulative effect of multiple HR cytogenetics abnormalities compared to a single HR cytogenetic abnormality on the OS outcomes of patients with pPCL. AIM To evaluate the prognostic implications of additive HR cytogenetics abnormalities by FISH in patients with pPCL treated with novel agents. METHODS We evaluated patients with newly diagnosed pPCL at the Mayo Clinic Comprehensive Cancer Center from 2014 - 2023 that received induction with novel agent combinations. pPCL was defined as patients meeting the diagnostic criteria for MM with 5% or more circulating plasma cells (cPCs) present on morphologic evaluation of their peripheral blood smear. HR cytogenetics abnormalities by FISH was defined by the presence of any one of the following: 1q gain/amplification, t(4;14), t(14;16), t(14;20), and del(17p). Time to next treatment (TTNT) and OS analysis were performed using the Kaplan-Meier method, and differences were assessed using the log-rank test. Statistical analyses were performed using the SAS biostatistical software JMP 17.0.1 (SAS Institute Inc). RESULTS We included 89 patients with newly diagnosed pPCL who received novel agents as first-line therapy between 2014 to 2023. The median follow-up was 45 months (95% CI: 35 - 65). At diagnosis, the median bone marrow plasma cell content was 80% (Range: 10 - 100), and the median cPC% on the peripheral smear was 21% (range: 5 - 85). There were 51 patients (59%) who had 20% or more cPCs on their peripheral smear. There was a preponderance of pPCL patients who had t(11; 14) as their primary cytogenetic abnormality (43%). The median lines of therapy received were 2 (Range: 1 - 9). There were 12 (13%) patients who received intensive induction therapy containing continuous infusional chemotherapy regimens at the onset of their diagnosis. Of the remaining patients, 35 (45%) were treated with a quadruplet (anti-CD38 antibody, proteasome inhibitor and immunomodulator), 24 (31%) with a triplet (proteasome inhibitor and immunomodulator) and 18 (23%) with a doublet (proteasome inhibitor only). The median OS for all pPCL patients in this cohort was 47 months (95% CI: 37 - 100). However, when stratified by cytogenetic risk, the median OS was 101 months (95% CI: 57 - NR) for those patients without any HR cytogenetic abnormalities (N = 24, 27%) vs. 37 months (95% CI: 22 - 63) for those with one or more HR cytogenetic abnormalities (N = 65, 73%) (P = 0.006). Of the patients with any HR cytogenetic abnormalities, 33 (36%) had one HR cytogenetic abnormalities and 32 (34%) had two or more HR cytogenetic abnormalities. The median OS for patients with one compared to two or more HR cytogenetic abnormalities were 47 (95% CI: 38 - 111), and 22 (95% CI: 17 - 37) months, respectively (P = 0.031). The median TTNT was 22 months (95% CI: 16 - 58) for those patients without any HR cytogenetic abnormalities vs. 16 months (95% CI: 9 - 21) for those with one or more HR cytogenetic abnormalities (P = 0.09). The median TTNT from the time of diagnosis for pPCL patients with one compared to two or more HR cytogenetic abnormalities were 18 (95% CI: 6 - 41) and 16 (95% CI: 10 - 19) months, respectively (p = 0.247). CONCLUSION Patients with pPCL with more than one HR cytogenetic abnormality had an inferior OS compared to those with only one HR cytogenetic abnormality, implicating the additive adverse effects of multiple HR cytogenetics abnormalities. In contrast, patients with pPCL without any HR cytogenetic abnormalities had a relatively long median OS (over 100 months).

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: The current definition of plasma cell leukemia (PCL) is based on peripheral blood smear (PBS) demonstrating ≥5% plasma cells. However, PCL cases are enriched in translocation t(11;14), which often has a lympho-plasmacytoid appearance. Detection and quantification of circulating tumor plasma cells (CTC) through peripheral blood flow cytometry (PBF) has emerged as a promising approach for assessing disease burden and prognosis in multiple myeloma (MM) patients. While PBF is more sensitive, the potential threshold values on PBF that correspond with the PBS detection of circulating plasma cells (PBS-PC) remain undetermined. It is important to understand this comparison better to categorize PCL based on PBF. Patients and Methods: This is a retrospective cross-sectional diagnostic accuracy study. We reviewed results of patients diagnosed with plasma cell dyscrasia at the Mayo Clinic from January 2011 to December 2020. The presence of circulating tumor plasma cells (CTC) in encounters was evaluated using peripheral blood flow cytometry (PBF) and peripheral blood smear (PBS) for plasma cells (PBS-PC). PBS-PC was measured as a percentage of plasma cells (PC) in a 100-cell manual differential smear count, and PBF was expressed as the number of plasma cell events per 150,000 peripheral blood mononuclear cells (PBMCs) (Ficoll-isolated peripheral blood mononuclear cells using antibodies to CD38, CD138, CD19, CD45, kappa, lambda, sensitivity (Sn)=6.7x10-5). The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of PBS with respect to PBF were calculated. For threshold analysis, four groups were defined: A = absent PBS-PC, C = ≥1% and <5%, D = ≥5%. Sensitivity and specificity of detecting PBS-PC (y-axis) for groups A vs. B, B vs. C, and C vs. D were plotted against CTC levels on PBF (x-axis) to determine the best cut-off. Area Under the Curve (AUC) was calculated to determine accuracy. Agreement analysis was done for internal validation and reliability assessment. Results: 6066 test records of CTC were reviewed. Circulating tumor plasma cells (CTC) by peripheral blood flow cytometry (PBF) were reported in 1610 (26.5%) instances, and peripheral blood smear for plasma cells (PBS-PC) in 226 (3.7%) tests. Peripheral blood smear (PBS) demonstrated a sensitivity of 9.3%, specificity of 99.5%, positive predictive value (PPV) of 86.7%, and negative predictive value (NPV) of 75.3% when compared to peripheral blood flow cytometry (PBF). The correlation between PBS-PC% and CTC was weakly positive (Spearman's rho=0.27, p<0.01). The median (Q1, Q3) of circulating tumor plasma cells (CTC) for group A (n=5840) was 0 (0, 0), group B (n=82) was 780 (97.75, 4012.75), group C (n=67) was 1801 (61.50, 8723.50), and group D (n=77) was 20518 (2296, 41349) (p-value <0.001). On post-hoc analysis, all pairs had significant differences in CTCs. To distinguish between A and B, a threshold of 32.5 for CTC demonstrated a sensitivity of 81.8% (AUC=87.8%), and to distinguish B and C, 1125 demonstrated a sensitivity of 59.4% (AUC=63.2%). To distinguish between C and D, 5875 for CTC demonstrated a sensitivity of 68.8% (AUC=74.6%). Agreement Analysis: The Bland-Altman plot demonstrates a slight positive bias between the Clonal Event % and %PBS-PC values (mean of difference = 0.28). The variability of differences increases with higher mean values, indicating a potential proportional bias. All predicted thresholds lie within the limits of agreement (LoA) (upper: 6.13, lower: -5.58) and are therefore reliable. The precision range (upper: 0.35, lower: 0.2) is narrower for the predicted thresholds. The methods should not be compared beyond a circulating tumor plasma cell (CTC) count of 9,195. Conclusion: Detection of circulating tumor plasma cells (CTC) by peripheral blood smear (PBS) is very specific but not sensitive and can be improved by peripheral blood flow cytometry (PBF) detection of CTC. Important clinical cutoffs by morphology (presence and ≥5%) have their counterparts by PBF (32 and 5875 out of 150,000 peripheral blood mononuclear cells (PBMC), respectively). The predicted thresholds are reliable. The study is retrospective and may not be generalizable across all demographics and disease severity. Circulating tumor plasma cell (CTC) values aren't absolute counts and may not be generalizable for low white blood cell (WBC) counts.

Background: There is an increased risk of second primary malignancies including second hematological malignancies (SHM) in multiple myeloma (MM) patients undergoing autologous stem cell transplant (auto-SCT) followed by lenalidomide maintenance. We analyzed the characteristics and outcomes of patients who developed SHM after an auto- SCT for MM. Methods: A retrospective study of all MM patients who underwent auto- SCT at Mayo Clinic, Rochester between January 1, 1990, and 31 August 2023 and later developed SHM. Demographic, clinical and pathologic data were collected retrospectively. Overall survival (OS) was calculated from the date of auto-SCT to the date of last follow up. Statistical analyses were performed using GraphPad prism 9.0. Chi-square test was used to calculate the difference between categorical variables. Kaplan Meier method and log rank test were used to estimate OS. Results: Among 3513 patients who underwent at least 1 auto-SCT, 104 (2.9%) developed a SHM at a median follow up of 59 (range, 0.2-265) months. Patients who developed SHM, more frequently received pretransplant alkylating agents (37.5 vs 24.2 %, odds ratio [OR], 1.87; P=0.003) and topoisomerase II inhibitors (anthracyclines/etoposide) (17.3% vs 10.4%, OR [1.79]; P=0.03) compared to a control group of MM patients without SHM. Further, exposure to lenalidomide (77.8% vs 57.6%, OR[2.59]; P <0.0001) and radiation therapy (32.6% vs 23.1%, [1.54]; P=0.04) were more often seen in the SHM cohort compared to control group. Among the 381 patients who underwent > 1 auto- SCT, 3.1% developed SHM. Therapy related myeloid neoplasms (t-MN) accounted for 90.3% of cases [n=94; t-myelodysplastic syndrome (t-MDS=64), t-acute myeloid leukemia (t-AML=12), t-MDS transformed to AML(n=16), chronic myeloid leukemia (n=1), MDS/myeloproliferative neoplasm overlap syndrome (n=1)]. Eight patients (7.6%) developed therapy related B- cell acute lymphoblastic leukemia (t-ALL); Philadelphia (Ph) negative ALL (n=7) and Ph- like ALL (n=1). One patient each developed mixed phenotype acute leukemia and acute leukemia, not otherwise specified. Sixty patients (57.6%) were males and the median age at diagnosis of SHM was 70 (range, 43-84) years. The median time from auto-SCT to diagnosis of SHM was 58.5 (range, 7-236) months. In a multivariate analysis, receiving an alkylating agent (hazard ratio [95% confidence interval]: 2.51 [1.54 to 4.01]; P = 0.0002) and/or topoisomerase II inhibitor as induction for MM (3.12 [1.59 to 5.88]; P = 0.0006), exposure to lenalidomide (7.08 [3.92 to 13.50]; P = <0.0001) and radiation therapy (1.60 [1.02 to 2.44]; P = 0.03) were independent predictors of developing SHM. At diagnosis, 57% (n=37) of t-MDS and 71% (n=20) with t-AML had high risk disease per R-IPSS and 2022 European Leukemia Net respectively. Clonal abnormality in chromosome 5 and/or 7 was present in 45% (n=42) of patients. Complex and monosomal karyotype was seen in 32% (n=30) with t-MN. The most frequently mutated genes based on next generation sequencing data included TP53 (n=33), DNMT3A (n=9), RUNX1 (n=5), TET2 (n=4) and CEBPA (n=4). In the t-MDS/AML cohort, 3 patients (3.1%) underwent second auto-SCT and 9 (9.5%) received allogenic SCT (allo-SCT) for SHM. After a median follow-up of 27.2 months, the median OS from t-MDS/AML diagnosis was 8.04 months (95%CI, 6.1-11.0 months) and there was no difference in median OS for allo-SCT recipients versus nonrecipients (9.1 vs 6.8 months, P =0.19). In the t-ALL (n=8) cohort, all of them received lenalidomide based induction and five received lenalidomide maintenance. Most of the t-ALL patients had adverse risk cytogenetics [IKZF1 deletion (n=2), complex karyotype (n=2), TP53 mutation (n=1) and P2RY8-CRLF2 fusion (n=1)]. Three patients with t-ALL underwent allo-SCT and the median OS for allo-SCT recipients versus non recipients were 8.3 vs 7.9 months respectively, P=0.50. Among patients with SHM, 92.3% (n = 96) have died with SHM (72%) being the most common cause of death. MM patients who developed SHM had an inferior OS when compared to those without SHM (median OS, 75 vs 90 months, P =0.006). Conclusion: SHM following auto-SCT tends to have aggressive disease biology with poor outcomes. Short term follow up underestimates the risk of SHM and the higher incidence noted in our study may be due to longer follow up. As the OS in MM patients continues to improve, SHM remains an important challenge in improving long term outcomes.

Introduction: Light chain (AL) amyloidosis is a clonal plasma cell disorder characterized by tissue deposition of misfolded immunoglobulin light chains in the form of amyloid, leading to organ dysfunction. Halting the production of the amyloidogenic free light chains by achieving a deep hematologic response (HemR) is key to improving organ function, however, variation in organ responses exists. In this work, we investigated variables associated with liver response (LivR) in a large cohort of patients with AL amyloidosis. Methods: Retrospective study of newly diagnosed AL amyloidosis patients with liver involvement seen at Mayo Clinic within 90 days of diagnosis between January 2000 and December 2021. Patients were eligible if they (1) had liver involvement, defined as a baseline alkaline phosphatase (ALP) ≥ 1.5 x upper limit of normal (ULN) and (2) had LivR measurements at least twice annually in the first year from treatment and annually afterward. LivR was defined as a >50% reduction in alkaline phosphatase (ALP) from baseline value or normalization of ALP. LivR was recorded at 6, 12, and 24 months from treatment initiation and at the best LivR achieved. Patients who died prior to landmark assessment were considered non-responders at subsequent milestone assessments. Covariates associated with LivR were identified by univariate and multivariable logistic regression analyses and a proportional subdistribution hazard (Fine-Gray) model for competing risk (treating death as a competing event). Multivariable logistic regression models for LivR were created using best subset selection, with calculation of odds ratio (OR) and 95% confidence interval (CI). Results: A total of 130 patients were included, with a median age of 60 years (IQR 53-66), male predominance (69%), and a median follow-up of 8.8 years. Sixty percent of patients had lambda isotype, the median ALP was 368 IU/mL (IQR 279-589), with 48% of patients having ALP ≥3 fold the upper limit of normal (ULN). Median bilirubin was 0.7 mg/dL (IQR 0.5-1.1). Forty-three percent of patients received front-line autologous stem cell transplant (ASCT) with or without prior induction therapy, and 5% received daratumumab-based therapy as their front-line treatment. Liver response rate increased with time, with 36 patients (28%) achieving a LivR at 6 months, 47 (36%) at 12 months, 63 (48%) at 24 months, and 94 (72%) at best response. The median time to liver response was 14 months (7.22-32.67). At the 24-month landmark, age <60 years, ALP ≥3 fold ULN, and front-line ASCT were significantly associated with achieving a LivR on univariate logistic regression. On univariate logistic regression at best liver response, age <60 years, ALP ≥3 fold the ULN, kappa isotype, ≥HemVGPR within 6 months, and front-line ASCT were significantly associated with obtaining a LivR. On multivariable logistic regression, at 24 months, ALP ≥3 folds of ULN (OR=2.9, 95% CI 1.4-6.3, P=0.004) was significantly associated with an increased likelihood of LivR. Achieving ≥HemVGPR and front-line ASCT were also associated with increased LivR likelihood, although not statistically significant (p=0.094, p=0.078, respectively). At best liver response, achieving ≥HemVGPR within 6 months (OR=5.2, 95% CI 1.9-14.8), kappa isotype (OR=3.2, 95% CI 1.1-10.0), ALP ≥3 folds of ULN (OR=3.3, 95% CI 1.3-9.9), and front-line ASCT (OR=5.3, 95% CI 1.9-16.7) were factors significantly associated with LivR. The Fine-Gray model demonstrated kappa isotype (HR=1.7), baseline ALP ≥3 folds of ULN (HR=2.1), ≥HemVGPR within 6 months (HR=1.9), and age <60 years at diagnosis (HR=1.9) to be positively associated with achieving LivR (P<0.05). Conclusions: In this large cohort of liver AL amyloidosis, LivR was achieved in 72% of patients, and amongst responders, the median time to response was 14 months from therapy initiation. Predictors of LivR included kappa isotype, deep hematological response in the first 6 months of initial therapy, ASCT usage, and higher baseline ALP levels. These findings better inform clinicians on the likelihood of achievement of liver response and may enable ways to improve its achievement.

Background: Multiple myeloma (MM) involves the proliferation of monoclonal plasma cells (PCs) in the bone marrow. The plasma cell labeling index (PCLI), indicating the percentage of PCs in the S-phase, is a key prognostic factor in newly diagnosed multiple myeloma (NDMM) patients. Methods: A retrospective study at Mayo Clinic analyzed bone marrow Affymetrix microarray datasets from 136 NDMM patients (2001-2012). Data normalization and quality assessment were followed by differential gene expression analysis using limma-voom, adjusted for age, BMPC percentage, and disease stage (RISS). Selected genes were dichotomized by median and subjected to logistic regression for high/low PCLI. Data from 594 patients with a Proliferation Index at baseline was pooled from the MMRF (CoMMpass) dataset for validation after normalization across assays. Results: The baseline characteristics of the patients are as follows: 62 (46%) were female and 74 (54%) were male, with a mean age at diagnosis of 61.6 ± 11.5 years. RISS staging included 36 patients (26.5%) at stage 1, 32 (23.5%) at stage 2, 29 (21.32%) at stage 3, and 39 patients (28.67%) with unknown stage. PCLI distribution showed 113 patients (83.7%) with <2%, and 23 (16.3%) ≥2%. Differential Analysis: The differential analyses reveal several critical insights. In the primary continuous differential analysis, 21,367 genes were analyzed, identifying 654 as differentially expressed with an FDR-adjusted p-value ≤0.05. Of these, 481 genes were upregulated (top 5: SPC25, TRAT1, PBK, E2F8, ASPM) and 173 were downregulated (top 5: SPARC, CD24, MYOF, CXCL12, VCAM1). Univariate and multivariate stratified analyses showed significant findings: 668 genes in age stratification, 395 genes in BMPC% stratification, and 536 genes in RISS stratification. In multivariate analysis, 408 genes were significant with an FDR-adjusted p-value <0.05 for PCLI and ≥0.05 for BMPC%, age, and RISS. 3-Fold Internal Validation: 240 significant genes were identified in fold 1, 25 in fold 2, and 167 in fold 3, with 21 genes common across all folds (e.g., MCM10, GTSE1, UBE2S, NCAPG, FOXM1, STMN1, NEK2, CENPF, MND1, HJURP, E2F8, TOP2A, SKA1, CCNB2, CCNF, CHAF1A, PBK, EXO1, AURKB, CDCA2, DHFR). 19 genes were common in the sensitivity analysis by excluding RISS 3. 20 genes were common in categorical analysis (Categories <1%, 1-2%, 2-3%, 3-4%, >4%). 3 Gene-Based Proliferation Score (3GPS): On univariate logistic regression analysis of 21 genes for high/low PCLI, 17 significant genes were identified. In the step-wise multivariate analysis, CDCA2 (OR=11.56), DHFR (OR=9.6), and CENPF (OR=6.11) were significant. Log-odds were used as weights. For the high expression(median and above) of gene as 1 and low expression as 0: 3GPS=2.4*CDCA2+ 2.3*DHFR +1.8*CENPF A cut-off of 2.4 was chosen as CDCA2 had the highest positive concordance rate (90.91%) versus DHFR (86.36%) and CENPF (77.27%). External Validation: In the CoMMpass dataset, the sensitivity and specificity for the presence of high expression of any of the 3 genes with ≥2 Proliferation Index (PI) were 92.4% and 73.8%, respectively (AUC=83.1%). The median 3GPS was 0 for <2 PI (n=238) and 6.5 for ≥2 PI (n=356). The sensitivity and specificity for the 3GPS in predicting ≥2 PI were 82.6% and 93.6%, respectively (AUC=88.1%). Pathway Analysis: Significant pathways using Reactome include polo-like kinase mediated events in G2/M transition, condensation of prometaphase chromosomes in metaphase, resolution of sister chromatid cohesion in anaphase, and APC-Cdc20 mediated degradation of Nek2A for regulation of the cell cycle. p53 signaling, cancer pathways, and microtubule regulation were also mapped. Survival Analysis: In our cohort, for CDCA2 quartiles (Q)3 and Q4, for CENPF Q3 and Q4, and for DHFR Q4 were associated with inferior overall survival. 3GPS ≥2.4 was associated with inferior survival of 60.28 months versus 111.5 months for <2.4 (p<0.01). In the validation dataset, median survival was not reached at 100 months (vs. high 79.7, p<0.01). The multivariate Cox model found 3GPS score ≥2.4 as an independent predictor (HR=1.64, 95% CI: 1.23 - 2.19), along with ECOG status, ISS stage, gender, age, and whether the patient underwent Stem Cell Transplant. Conclusion: CDCA2, DHFR, and CENPF are associated with ≥ 2% PCLI. The 3GPS score can serve as a measure of gene-based proliferation index. Prospective validation is needed for clinical practice.

Background: AL amyloidosis is a potentially fatal plasma cell dyscrasia. In a randomized phase 3 study (Kastritis E et al, NEJM 2021;385:46-58), the addition of daratumumab to cyclophosphamide, bortezomib and dexamethasone (Dara-CyBorD) significantly improved hematological and organ responses, and prolonged event-free survival (EFS). There was no overall survival (OS) difference at a median follow-up of 11.4 months. Methods: A retrospective study of AL amyloidosis patients seen at our institution between January 2018 and December 2022 who received upfront Dara-CyBorD or CyBorD. We excluded patients who received other forms of upfront therapy (including modifications of the above regimens, such as bortezomib-dexamethasone or daratumumab-dexamethasone). We compared the hematologic and organ responses, EFS and OS between the two treatment groups. Hematologic response was assessed at 2 and 6 months from therapy initiation, while cardiac and renal responses at 6- and 12-month landmarks. In all response evaluations, we included responses up to autologous stem cell transplantation (ASCT) if used or second-line therapy for any reason. For EFS analysis, an event was defined as death of any cause, hematological progression, end-stage cardiac or renal failure, or need for subsequent anti-plasma cell therapy in the absence of hematological progression. OS was calculated from the time of treatment initiation to death or last follow-up. Results: Among 641 newly diagnosed patients seen at our center between 2018 and 2022, 361 patients (56%) were included on intention-to-treat analysis [Dara-CyBorD =147 (41% of the cohort); CyBorD=214 (59%)]. There was no difference in the baseline characteristics between the treatment groups, including age, sex, difference between involved and uninvolved light chains, bone marrow plasma cells percentage, NT-proBNP and 24-hour proteinuria. The 2-month hematologic complete response (hemCR; 15.3% vs 4.4%, P<0.001) and very good partial response or better (≥hemVGPR; 62.2% vs 32.5%, respectively; P<0.001) were higher with Dara-CyBorD compared to CyBorD. At 6 months, the hemCR and ≥hemVGPR were again in favor of the Dara-CyBorD group compared to CyBorD (32.0% vs 13.7%, and 72.8% vs 46.7%, respectively; P≤0.002). The 6- and 12-month cardiac response rate in the Dara-CyBorD and CyBorD groups were 40.2% vs 22.6% (P=0.01) and 44.1% vs 23.2%, respectively (P=0.006). Cardiac ≥VGPR at the 6- and 12-month landmarks were statistically higher with Dara-CyBorD compared to CyBorD and increased in both arms between 6 and 12 months [20.5 % vs 9.3% (P=0.03) and 34.3 % vs 20.0% (P=0.04), respectively]. The 6-month and 12-month renal response to first-line therapy were numerically higher with Dara-CyBorD compared to CyBorD but were not statistically significant (48% vs 31.3%, P=0.10; 54.1% vs 30.1%, P=0.05). The 6 month and 12 months, renal ≥VGPR were numerically higher with Dara-CyBorD compared to CyBorD, again without statistical significance (26% vs 19.6%, P=0.63; 35.7% vs 17.2%, P=0.11, respectively). Treatment with Dara-CyBorD was significantly associated with lower 6-month mortality rate compared to CyBorD (8.8% vs 16.3%, P=0.04). With a median follow-up of 43.3 months (30 vs 59.4 months for Dara-CyBorD vs CyBorD, respectively; P<0.001), the two-year EFS was superior in the Dara-CyBorD group compared to CyBorD (69.1% vs 30.3%, hazard ratio (HR) 0.36, 95% confidence interval (CI), 0.26 to 0.48, P<0.001). The 2-year OS was also statistically higher in the Dara-CyBorD group compared to CyBorD (82.0% vs 69.6%, HR 0.53, 95% CI, 0.36 to 0.79, P=0.003). 148 patients (40.9%) proceeded to second-line therapy with a median of 5.1 months from first line therapy. To adjust for difference in follow-up time between the two treatment groups, we analyzed the second line therapy utilization at the 12-month mark which was statistically higher with CyBorD compared to Dara-CyBorD (42.9% vs 14.9%, P<0.001). Also, at 12 months, a higher proportion of patients treated with CyBorD received ASCT compared to Dara-CyBorD (24.3% vs 13.6%, P= 0.01). Conclusions: In this cohort of newly diagnosed AL amyloidosis patients in a large referral center, we confirmed higher hematological and organ response rates with Dara-CyBorD compared to CyBorD. We have also demonstrated that these higher response rates translate into a survival advantage of Dara-CyBorD over CyBorD.