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AbstractSeveral tools exist for assessing frailty in multiple myeloma (MM), but most are based on clinical trial datasets. In this study, we evaluate the prognostic impact of frailty based on the cumulative deficit frailty index (FI), and the prognostic impact of relationship and socioeconomic status (SES) in newly diagnosed MM patients. This is a retrospective study including 515 patients with MM seen at Mayo Clinic (Rochester, MN) at diagnosis between 2005–2018. The FI was calculated using patient-reported data on activities of daily living and comorbidity data. Items were scored as 0/0.5/1, with 1 indicating deficit. The FI was calculated by adding individual scores and dividing that by the number of non-missing items. Frailty was defined as FI ≥ 0.15; 61% were non-frail and 39% were frail. Frailty and non-married/relationship status were associated with higher disease stage, decreased 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. In conclusion, a cumulative deficit FI was associated with higher symptom burden and decreased survival in a real-world cohort of newly diagnosed MM patients. Social support has prognostic value and should be assessed in clinical practice.

CONCLUSION The most widely used multiple myeloma (MM) staging system, the Revised International Staging System (R-ISS), is based on lactate dehydrogenase (LDH), albumin, high-risk genetic markers by FISH, and beta-2 microglobulin (B2M). However, it does not account for additional risk impacted by multiple genetic abnormalities, or the risk imparted by presence of gain of chromosome 1q, and most patients are staged as R-ISS Stage 2. Two new staging systems, the Mayo Additive Staging System (MASS), and the Second Revision of the International Staging System (R2-ISS) have been recently proposed. A comparison of the performance of these two systems has not previously been done. We aimed to externally demonstrate the application of these staging systems and compare their performances in a large, contemporary cohort of patients in the United States. We conducted a retrospective cohort study using the nationwide Flatiron Health electronic health record (EHR)-derived de-identified database, comprising de-identified patient-level structured and unstructured data, curated via technology-enabled abstraction and originating from approximately 280 US cancer clinics (~800 sites of care). The study included newly diagnosed MM patients initiating treatment between January 1, 2016 and October 1, 2022. We used the Kaplan-Meier method to evaluate real-world overall survival (rwOS) and patients were followed from first-line treatment initiation (index date) until the first of death, end of the study period or last recorded activity. The log-rank test to compare survival curves across derived stages. Multivariable analysis was conducted using stratified Cox models to account for non-proportional hazards by age with covariate adjustment for race/ethnicity, sex, practice type (academic or community) and diagnosis year (2016-2019 vs 2020-2022). Discrimination and calibration were evaluated in crude models using Harrell's c-index and the Hosmer-Lemeshow goodness-of-fit test, respectively. There were 497 patients with MM included. Patient characteristics are listed in Panel A. The distribution of patients across R-ISS stages were as follows, 24%, 63% and 13% for Stage 1, 2 and 3 respectively. rwOS differed across R-ISS stage (log-rank p = 0.0006) and the median OS (OS) was not reached (NR), 63, and 37 months for R-ISS stage 1, 2, and 3, respectively. 34%, 35% and 31% for MASS 1, 2, and 3, respectively. The corresponding survival curves were significantly different (p < 0.0001), with associated mOS of 77, 61 and 45 months for MASS stages 1, 2, and 3, respectively. R2-ISS includes four risk categories (stages I-IV) and in our cohort, 20% (n = 100) were stage I (low), 126 (25%) were stage II (low-intermediate), 229 (46%) were stage III (intermediate), and 42 (9%) were stage IV (high). Survival across stages were significantly different (p<0.0001), though the survival curves for low and low-intermediate, and intermediate-high and high, were clustered, suggesting comparable outcomes in stages I-II and stages III-IV. mOS for R2-ISS stages I, II, III, and IV was NR, 69, 50 and 51 months respectively (Panel B). In fully adjusted analyses, as compared to MASS I, the hazards of death were 2.0 (95% CI 1.3-3.2) for MASS II and 2.7 (1.7-4.2) for MASS III. The hazards of death were similar for R2-ISS low and low-int (HR for low-int vs low: 1.2 [0.7, 2.3]). As compared to R2-ISS low, the hazards of death were similarly higher for int-high and high (HRs: 2.4 [1.4, 4.1] and 2.6 [1.3, 5.2], respectively). Discrimination and calibration were similar across all staging systems (c = 0.6, and Hosmer-Lemeshow p>0.05 for all three staging systems). Application of contemporary MM staging systems in a large cohort of US patients shows that they are prognostic for OS in MM. MASS demonstrated a greater separation for OS across stages, whereas R2-ISS intermediate-high and high were largely overlapping. Although our results demonstrate similar accuracy and reliability of MASS and R2-ISS, the discrimination of patients across different stages seen with the newer staging systems, as opposed to R-ISS, calls for greater use of these newer staging systems in routine clinical practice.

Background: Frailty is a state of decreased reserve affecting multiple organ systems, thereby increasing vulnerability to stressors. Several tools have been proposed to measure frailty in multiple myeloma (MM), such as the IMWG frailty index, and the Revised Myeloma Comorbidity Index. However, these are based on clinical trial datasets, and include chronological age as one of the indicators of frailty. A frailty index based on the principle of accumulation of health deficits (Rockwood doi:10.1093/gerona/62.7.738), provides a measure of physiologic age. This index can be readily calculated using various combinations of health deficits and has been shown to predict outcomes in several populations. Social support has been associated with improved outcomes in various populations, however its impact on survival in patients with MM has not been well studied. The objective of this study was to assess the impact of frailty measured by a deficit accumulation frailty index and the impact of relationship status on outcomes in patients with newly diagnosed MM. Methods: This is a retrospective study including patients diagnosed with MM between January 6 th, 2005, and September 19 th, 2018. We calculated a deficit accumulation frailty index using previously published methods (McNallan et. al doi.org/10.1016/j.ahj.2013.07.008, Searle et al. doi.org/10.1186/1471-2318-8-24). We used the electronic medical record system at Mayo Clinic in Rochester, MN, to extract data on activities of daily living (14 items) provided by patient-completed questionnaires, and data on comorbidities as recorded by treating providers (16 items), within 6 months prior to diagnosis. Each item was scored as 0, 0.5, or 1, with 1 indicating the presence of deficit (Table 1). The frailty index was defined as the sum of individual scores divided that by the total number of non-missing items. Patients who had N >2 missing items were excluded. Patients with a frailty index ≥0.15 were considered frail. We also extracted data on self-reported relationship status within 6 months prior to diagnosis. Variables were compared between groups using Fisher's exact test and Wilcoxon signed-rank test for categorical and continuous variables, respectively. Univariate and multivariate analysis were performed using Cox proportional hazard models. Overall survival (OS) was estimated using the Kaplan-Meier method and compared between groups using the Log-rank test. P values <0.05 were considered statistically significant. Results: We included 578 patients. Median age was 67 (interquartile range: 59-74) years, and 40% were female. Among all patients, 226 (39%) were frail. Compared to fit patients, patients who were frail were older (median age: 70 vs. 65 years, P<0.001) and more likely to have International Staging System (ISS) III (vs. I/II) disease (47% vs. 27%, P<0.001) and ECOG performance status ≥2 (vs. 0 or 1) (45% vs. 17%, P<0.001). There was no difference in R-ISS III disease or presence of high-risk cytogenetic abnormalities between fit and frail patients. Median OS was 7.6 and 4.1 years in fit and frail patient, respectively (P<0.001). Physician assessed ECOG performance status was available for 268 patients. Among patients with ECOG performance status 0 or 1 (193 patients), 136 (70%) were fit, and 57 (30%) were frail. The OS was 8.3 and 4.6 years in the 2 groups, respectively (P=0.006) (table 2). On multivariate analysis including age, frailty status, and R-ISS stage (III vs. I/II), all were associated with OS with frailty's hazard ratio (HR): 1.4 (95%CI [1.1-1.8]), P=0.004; the HR was 1.4 (95%CI [1.1-1.9]), P=0.02, when analysis was restricted to patients ≥60 years. Among all patients, those who were married or in a committed relationship (474 patients) had improved survival (median OS: 7.0 vs. 3.7 years, respectively, P<0.001) compared to patients who were divorced/separated, widowed, or single (96 patients). On multivariate analysis, which included age, R-ISS III, frailty status, and relationship status, all were associated with OS. The HR for relationship status was 1.4 (95%CI [1.0-1.8]), P=0.0465. Conclusion: Frailty, defined by the deficit accumulation frailty index, is independently associated with decreased survival in patients with newly diagnosed MM. Being married or in a committed relationship is associated with improved survival independent of age, disease stage, and frailty.

Abstract The approach to patients with high-risk smoldering multiple myeloma (SMM) varies among clinicians; while some advocate early intervention, others reserve treatment at progression to multiple myeloma (MM). We aimed to describe the myeloma-defining events (MDEs) and clinical presentations leading to MM diagnosis among SMM patients seen at our institution. We included 406 patients diagnosed with SMM between 2013-2022, seen at Mayo Clinic, Rochester, MN. The 2018 Mayo 20/2/20 criteria were used for risk stratification. Median follow-up was 3.9 years. Among high-risk patients who did not receive treatment in the SMM phase (n=71), 51 progressed by last follow-up; the MDEs included: bone lesions(37%), anemia(35%), hypercalcemia(8%), and renal failure(6%); 24% met MM criteria based on marrow plasmacytosis (≥60%) and/or free light chain ratio (>100); 45% had clinically significant MDEs (hypercalcemia, renal insufficiency, and/or bone lesions). MM diagnosis was made based on surveillance labs/imaging(45%), testing obtained due to provider suspicion for progression(14%), bone pain(20%), and hospitalization/ED presentations due to MM complications/symptoms(4%). The presentation was undocumented in 14%. A high proportion (45%) of patients with high-risk SMM on active surveillance develop end-organ damage at progression. About a quarter of patients who progress to MM are not diagnosed based on routine interval surveillance testing.

BackgroundSarcopenia increases with age and is associated with poor survival outcomes in patients with cancer. By using a deep learning–based segmentation approach, clinical computed tomography (CT) images of the abdomen of patients with newly diagnosed multiple myeloma (NDMM) were reviewed to determine whether the presence of sarcopenia had any prognostic value.MethodsSarcopenia was detected by accurate segmentation and measurement of the skeletal muscle components present at the level of the L3 vertebrae. These skeletal muscle measurements were further normalized by the height of the patient to obtain the skeletal muscle index for each patient to classify them as sarcopenic or not.ResultsThe study cohort consisted of 322 patients of which 67 (28%) were categorized as having high risk (HR) fluorescence in situ hybridization (FISH) cytogenetics. A total of 171 (53%) patients were sarcopenic based on their peri‐diagnosis standard‐dose CT scan. The median overall survival (OS) and 2‐year mortality rate for sarcopenic patients was 44 months and 40% compared to 90 months and 18% for those not sarcopenic, respectively (p < .0001 for both comparisons). In a multivariable model, the adverse prognostic impact of sarcopenia was independent of International Staging System stage, age, and HR FISH cytogenetics.ConclusionsSarcopenia identified by a machine learning–based convolutional neural network algorithm significantly affects OS in patients with NDMM. Future studies using this machine learning–based methodology of assessing sarcopenia in larger prospective clinical trials are required to validate these findings.

Abstract Overall Survival estimates from diagnosis are valuable for guiding treatment, but do not consider the years already survived. Conditional survival (CS) provides dynamic survival predictions over time. This study was conducted to estimate CS at 1–8 years from diagnosis and the impact of baseline prognostic factors on CS in multiple myeloma (MM) patients. This is a retrospective study including 2556 MM patients diagnosed between 2004–2019. CS (t|s) was defined as the probability of surviving t years given survival of s years. Median age was 64 years. Median follow-up was 6.2 years and median overall survival from diagnosis was 7.5 years. The 5-year CS estimates at s = 0, 1, 2, 3, and 5 years were 0.64, 0.61, 0.61, 0.61, and 0.58, respectively. On multivariate analysis, age ≥ 65 and proteasome inhibitor + immunomodulatory-based induction were associated with decreased survival and increased survival, respectively, retained at 5 years. The adverse impact of 1q gain/amplification, high-risk IgH translocation, and ISS-3 was significant at 1 and 3 years but not 5 years. Chromosome 17 abnormality was associated with decreased survival only at 1 year. Among MM patients, 5-year CS was stable at 1–5 years from diagnosis. The prognostic impact of high-risk cytogenetic factors decreased with additional years survived.

Abstract Purpose: The prevalence of pathogenic variants in BRCA1 and BRCA2 in populations other than Ashkenazi Jewish (AJ) is not well defined. We describe the racial and ethnic-specific prevalence of BRCA1/2 pathogenic variants and variants of uncertain significance (VUS) among individuals referred for genetic testing in a large urban comprehensive cancer center over a 20-year period. Methods: The population included 3,537 unrelated individuals who underwent genetic testing from January 1999 to October 2019 at the Karmanos Cancer Institute. We estimated the prevalence of pathogenic variants and VUS and evaluated associations with race and ethnicity for African American (AA), Arab, AJ and Hispanic individuals compared to Non-Hispanic Whites (NHW). We used multivariable models to adjust for other predictors of pathogenic variants. We also reported the most common pathogenic variants by racial and ethnic group. Results: The racial and ethnic breakdown of our population was: NHW (68.9%), AA (20.3%), AJ (2.5%), Arab (2.2%), Hispanic (1.0%), Asian Pacific Islander, Native American/Alaskan Native (4.7%), and <1% unknown. The overall prevalence of pathogenic variants in BRCA1/2 was 8.9% and the prevalence of VUS was 5.6%. Compared to NHW, there were no racial or ethnic differences in the rate of pathogenic variants. However, AA individuals were more likely to have VUS in BRCA1 (adjusted OR 2.43, 95% CI 1.38-4.28) and AJ more likely to have VUS in BRCA2 (adjusted OR 3.50, 95% CI 1.61-6.58).Conclusion: These results suggest the continued need for genetic testing and variant reclassification for individuals of all race and ethnic groups.

110 Background: Sarcopenia or a loss of muscle mass increases with aging and is associated with increased overall mortality in patients with cancer. Recent advances in machine learning–based CNN algorithms have allowed for the rapid processing of digital images to produce image classifications of body composition. Since incidence of MM is highly associated with aging, we sought to determine if the presence of sarcopenia, as determined by utilizing this machine learning–based CNN algorithm on CT images, had prognostic value in patients with NDMM. Methods: We identified all patients with NDMM from January 2003 to July 2019 who had a standard-dose CT scan that included the L3 vertebral level performed within 6 months of diagnosis. Using a machine learning–based CNN-algorithm, abdominal CT images were analyzed to measure muscle area. These measurements were normalized by dividing the area values by the height of the patient squared (m2) to obtain skeletal muscle index (SMI) values. Patients were categorized as sarcopenic according to international gender-specific consensus cutoffs for SMI (male: < 55 cm2/m2 and female: < 39 cm2/m2). Patients with the following FISH cytogenetics were considered high risk (HR): t(4;14), t(14;16), t(14;20), and deletion 17p/monosomy 17 whereas the remainder were standard risk (SR). Survival analysis was performed using the Kaplan-Meier method and compared via the log-rank method. Results: The study cohort consisted of 344 patients. 68 (20%) were categorized as HR based on FISH cytogenetics.187 (54%) patients were sarcopenic based on their peri-diagnosis standard-dose CT scan. Sarcopenic patients were more likely to have ISS-3 disease (45% vs. 30%; p =.023), be male (73% vs. 48%; p <.001), and be ≥ age 75 (27% vs. 14%; p =.002) compared to non-sarcopenic patients. The median OS for patients with HR FISH and ISS 2 / 3 disease was 40 months and 57 months respectively compared to 90 months and 119 months for those with SR FISH and ISS-1 disease respectively (FISH: p <.004; ISS: p <.001). The median OS for sarcopenic patients was 44 months compared to 90 months for those not sarcopenic (p <.001). The time to next therapy (TTNT) for sarcopenic patients was 39 months compared to 45 months for those not sarcopenic (p =.05). In a multivariable model, the presence of sarcopenia (HR 1.64, 95% CI, 1.05–2.56; p =.03) retained significance in the presence of HR FISH, ISS 2 / 3 disease, and age ≥ 75. Conclusions: Gender-specific sarcopenia identified by a machine learning–based CNN algorithm significantly affects OS in patients with NDMM and is independent of age, ISS stage, and cytogenetic status. Future studies utilizing this machine learning–based methodology of assessing sarcopenia in larger prospective clinical trials are required to validate these findings.