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Introduction : Multiple myeloma (MM) is a heterogeneous disease with diverse clinical outcomes. Although survival in MM has improved, high risk patients still experience early relapses and shorter survival. Current methods for risk stratification in MM are useful at diagnosis but need to be refined as our knowledge of disease pathobiology evolves. Tumor-associated macrophages, derived from peripheral blood monocytes, support malignant plasma cell proliferation in the bone marrow (BM) microenvironment. Since peripheral blood absolute monocyte count (AMC) could reflect the BM microenvironment, we evaluated the prognostic significance of AMC in MM at diagnosis and during the disease course. Methods: We used the nationwide Veterans Affairs electronic health records to include treatment-naïve MM patients diagnosed between 2000 and 2019 without concomitant aplastic anemia, myelodysplastic syndrome, myeloproliferative neoplasm, and acute or chronic leukemia. We obtained AMC (x10 3) closest to and within 90 days from diagnosis and every 3 months thereafter up to 2.5 years. Patients were stratified into 4 AMC groups: low (AMC < 0.2), normal (AMC 0.2 to < 0.8), elevated (AMC 0.8-1.25), and severely elevated (AMC > 1.25). Our selection criteria excluded any treatment-related change in AMC. Overall survival (OS) was evaluated using the Kaplan-Meier estimator and logrank tests. Cox proportional hazard models were used for multivariable analysis. Results: We analyzed 10,822 patients, median age 70 years (interquartile range [IQR] 63-77) with a median follow up of 2.9 years (IQR 1.3-5.3). At diagnosis, 25.3% of patients (2737 of 10,822) presented with abnormal AMC; with 5% having low, 16.7% elevated, and 3.6% severely elevated AMC. Patients with monocytosis (elevated or severely elevated AMC) were younger and more likely to have higher median levels of beta-2-microglobulin and lactate dehydrogenase (LDH) and lower median levels of albumin (p < 0.001) than those without monocytosis. Abnormal AMC at diagnosis significantly impacted overall survival (p < 0.001) . Patients with low, severely elevated, elevated, and normal AMC at diagnosis had median OS of 2.3, 2.7, 3.1, and 3.5 years (p < 0.001), respectively (Figure 1). Persistent AMC abnormality also impacted outcomes. Abnormal AMC > 1 year after diagnosis was also associated with inferior OS (median OS at 2.5 years - 2.0, 2.6, 3.4, and 3.9 years in patients with low, severely elevated, elevated, and normal AMC respectively [p < 0.001]) (Figure 2). If patients with normal AMC at diagnosis developed an abnormal AMC > 1 year after diagnosis, median OS was reduced relative to if they maintained normal AMC (Figure 3). Notably, median OS improved across all AMC groups in patients with MM diagnosed after 2012 when modern therapies became standard of care. However, the adverse survival impact of low, elevated, or severely elevated AMC persisted in all time periods. After adjusting for known prognostic factors (age, ISS Stage, LDH), multivariable analysis showed similar results, with a significant association of OS with AMC at diagnosis (Figure 4) and AMC measured up to 2.5 years after diagnosis. Hazard Ratios (HR) at diagnosis were 1.28 (95% confidence interval [CI] 1.16-1.41; p < 0.001), 1.10 (95%CI 1.04-1.17; p = 0.002), and 1.19 (95%CI 1.06-1.34; p = 0.004), and HRs at 2.5 years after diagnosis were 1.53 (95%CI 1.22-1.93; p < 0.001), 1.11 (95%CI 1.00-1.23; p = 0.043, 1.58 (95%CI 1.22-2.04; p < 0.001) for low, elevated and severely elevated AMC, respectively. Conclusion : Abnormal AMC is frequently observed in MM and is a powerful, easily attainable prognostic biomarker. Abnormal AMC at diagnosis or follow up of MM is significantly associated with inferior OS, independent of established prognostic factors. Survival was also inferior for patients who had normal AMC at diagnosis but then developed abnormal AMC, possibly suggesting changes in the BM microenvironment over time. Given the improved prognosis of patients with severely elevated AMC in patients diagnosed with MM after 2012, our data potentially highlights the mechanism of action of novel treatments interacting with the tumor microenvironment. Whether these findings reflect disease biology, a consequence of disease progression, or both warrants further in vitro, prospective studies. Overall, AMC is a readily available metric that could be included in the risk stratification of MM at diagnosis and beyond. Figure 1 Figure 1. Disclosures Munshi: Takeda: Consultancy; Bristol-Myers Squibb: Consultancy; Amgen: Consultancy; Janssen: Consultancy; Legend: Consultancy; Novartis: Consultancy; Adaptive Biotechnology: Consultancy; Pfizer: Consultancy; Karyopharm: Consultancy; Celgene: Consultancy; Oncopep: Consultancy, Current equity holder in publicly-traded company, Other: scientific founder, Patents & Royalties; Abbvie: Consultancy.

Introduction : Multiple myeloma (MM) is an incurable hematologic malignancy caused by the neoplastic proliferation of plasma cells within the bone marrow. The tumor microenvironment within the bone marrow consists of a diverse array of immune cells which regulate MM cell proliferation and survival. Specifically, tumor-associated macrophages (TAMs) derived from peripheral blood monocytes migrate to the bone marrow where they support MM cell growth and promote resistance to apoptosis. Several studies suggest that the amount of bone marrow TAMs directly correlates with disease activity and worse clinical outcomes in MM. Considering that peripheral blood absolute monocyte count (AMC) could reflect the burden of bone marrow TAMs, we sought to determine the prognostic significance of AMCs at diagnosis of MM. Methods: Using the integrated nationwide VA electronic health records and VA Corporate Data Warehouse, patients were identified by International Classification of Diseases (ICD) codes for MM. Patients were required to have at least 3 visits with an MM ICD code on separate days, have received at least one MM drug with the exception of corticosteroids after the date of diagnosis and have 2 or more absolute monocyte counts measured by automated or manual differential at separate visits within 18 months before and 7 days after MM diagnosis. We further confirmed the date of diagnosis using the VA Cancer Registry. We excluded patients with aplastic anemia, myelodysplastic syndrome, chronic myelomonocytic leukemia and other myeloproliferative neoplasms. In this cohort, monocytosis was defined based on the institution's cut-off as a sustained absolute increase in monocyte count of 0.8 (800/mm3) or greater with extreme monocytosis being greater than 1.25 (1250/mm3). Patients were stratified into three groups according to AMC at diagnosis, namely AMC 1.25. To avoid extreme values significantly affecting the analysis, the Kruskal-Wallis test was used to compare continuous variables between the groups. Chi-squared tests were used to compare categorical variables. Hazard estimates for the prognostic analysis were obtained via adjusted Cox proportional hazard models. Overall survival was estimated using the Kaplan-Meier method and log-rank tests were used to compare the survival of each group. Results: A total of 5,265 patients with MM were included in the final analysis with a median follow up of 2.9 years (range 1.3 - 5.2). At diagnosis of MM, 39.3% of patients presented with monocytosis. Patients with monocytosis were younger and more likely to have abnormal levels of prognostic markers known to be associated with increased tumor burden and worse outcomes in MM. Notably, patients with monocytosis had higher median levels of β2-microglobulin and lactate dehydrogenase (p 1.25 groups respectively (p 1.25 HR of 1.312, p Conclusion : The results of our study suggest that an elevated absolute monocyte count at MM diagnosis is associated with worse overall survival independent of known poor prognostic factors. The role of peripheral blood monocyte count as a surrogate biomarker for the state of the bone marrow microenvironment in MM warrants further in vitro, prospective studies. Disclosures Munshi: AbbVie: Consultancy; Amgen: Consultancy; Legend: Consultancy; Adaptive: Consultancy; Janssen: Consultancy; C4: Current equity holder in private company; OncoPep: Consultancy, Current equity holder in private company, Membership on an entity's Board of Directors or advisory committees, Patents & Royalties; Karyopharm: Consultancy; Takeda: Consultancy; BMS: Consultancy.

Background: In the recent decade, there have been dramatic improvements in multiple myeloma (MM) survival, owing principally to developments in therapeutic options. However, these developments have also raised concerns as to increase in second primary malignancies (SPMs) attributable to these therapies. For example, a Swedish study showed an increased risk of developing acute myeloid leukemia (AML)/myelodysplastic syndrome (MDS) in MM patients (11.51 fold), along with 1.19-fold increased risk of non-hematologic malignancies. However, it is presently unclear whether this increase is related to therapy or other factors such as host, environment or behavioral patterns. Here, we study incidence of SPM and association with demographics, exposure, and therapy in a large population in the US Veterans Affairs (VA) healthcare system. Methods: We used the VA's nationwide Corporate Data Warehouse to identify patients diagnosed with MM from 1999 to 2017, as well as their age, race, therapy at induction, stem-cell transplant status, and exposure status. For each patient, we identified the first SPM after MM treatment initiation using the VA Central Cancer Registry. We excluded patients who had records of malignancies prior to MM treatment initiation. Results: We identified 14,261 patients meeting the inclusion criteria, of whom 552 (3.9%) had SPMs, consistent with prior literature. Median age at MM diagnosis was 69.22 years overall (95% CI 51.98-84.76), 66.7 years (52.03-83.86) for those with SPM, and 69.32 years (51.99-) for those without SPM. Median age at diagnosis of SPM was 70.2 years (55.43-86.75). Median time from MM treatment initiation to SPM was 2.38 years (0.09-9.37). Of the 552 observed SPMs, 69 (12.4%) were hematologic (25 MDS, 19 lymphoma, 15 acute leukemia, 6 chronic leukemia, 4 MPN) while 84.5% (466) were oncologic. Prostate cancer was the most common SPM (n=125, 22.6%). We did not observe statistically significant differences in incidence of SPM by smoking status (4.1% among current/former smokers vs 3.7% among never smokers; P=0.347), or Agent Orange exposure (4.2% among those exposed vs 3.8% among those not exposed; P=0.476). We also examined the relationship of common treatments to SPM. SPM is more common among those exposed to lenalidomide (4.3% vs 3.4%, p=0.003), bortezomib (4.8 vs 3.3%, p Conclusion: In comparison to data from the VA Central Cancer Registry on cancer incidence at the VA in general, the incidence of SPM (3.9%) that we report among MM patients is substantially higher than the overall incidence of malignancy in the VA (0.78%). Moreover, we find that common risk factors for developing malignancy, including smoking status and exposure to Agent Orange, are not significantly associated with developing SPM after MM diagnosis. In contrast, we find that therapy utilization, particularly transplant, is associated with significant increases in susceptibility to SPM. Better understanding of these risk factors is needed to appropriately assess the tradeoff of decreased myeloma-related mortality, but potentially increased risk of secondary malignancies with common myeloma therapy options. Disclosures Yellapragada: Novartis: Employment, Other: Spouse Employment ; Celgene: Research Funding; BMS: Research Funding; Takeda: Research Funding. Munshi:Abbvie: Consultancy; Adaptive: Consultancy; Adaptive: Consultancy; Amgen: Consultancy; Amgen: Consultancy; Celgene: Consultancy; Celgene: Consultancy; Janssen: Consultancy; Janssen: Consultancy; Takeda: Consultancy; Takeda: Consultancy; Oncopep: Consultancy; Oncopep: Consultancy; Abbvie: Consultancy.