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PURPOSE Residents of communities facing social vulnerability (eg, poverty) have limited access to clinical trials, leaving them susceptible to experiencing poor health outcomes. We examined the association between North Carolina county-level social vulnerability and available multiple myeloma (MM) trials. METHODS Using a novel data linkage between ClinicalTrials.gov, the 2019 American Community Survey, and the Centers for Disease Control and Prevention's Social Vulnerability Index, we investigated at the county level (1) availability of MM trial sites and (2) the relationship between Social Vulnerability Index and MM trial site availability using logistic regression. RESULTS Between 2002 and 2021, 229 trials were registered across 462 nonunique trial sites in 34 counties. Nearly 50% of trial sites were in academic medical centers, 80% (n = 372) of all trials were industry-sponsored, 60% (n=274) were early-phase, and 50% (n5232) were for patients with relapsed or refractory MM. Counties with low as opposed to high poverty rates had six times greater odds of having ≥1 MMtrial sites (odds ratio [OR], 5.60; 95% CI, 1.85 to 19.64; P = .004). Counties with the lowest percentage of Black Indigenous Persons of Color and non-native English speakers had 77% lower odds (OR, 0.23; 95% CI, 0.07 to 0.69; P = .011) of having ≥ 1 trial sites. The effect remained significant after accounting for the presence of five academic medical centers (n = 95; OR, 0.18; 95% CI, 0.05 to 0.6; P = .008) and adjustment for metropolitan, suburban, or rural status (OR, 0.25; 95% CI, 0.07 to 0.81; P = .025). CONCLUSION Counties with the lowest poverty rates had more MM trial sites, whereas those with the lowest percentage of Black Indigenous Persons of Color populations had fewer MM trial sites. Multilevel efforts are needed to improve the availability and access to trials for socially vulnerable populations. [ABSTRACT FROM AUTHOR]

PURPOSE We performed a retrospective chart review on 393 patients with multiple myeloma (MM) to determine the utility of the gamma gap (GG). METHODS We calculated the difference between a patient’s total serum protein and albumin as a point-of-care test for assessing disease status in MM. RESULTS GG is highly correlated with the level of M-spike, and the change in GG correlates with myeloma treatment response. In addition, fitted linear models were established that allow for the calculation of M-protein level from the GG within hours from blood draw. CONCLUSION Our study has important implications in the care of MM, particularly in countries/areas with limited resources. [ABSTRACT FROM AUTHOR]

Purpose The distinction of patients with symptomatic multiple myeloma (MM) from those with smoldering MM poses a challenge for researchers who use administrative databases. Historically, researchers either have included all patients or used treatment receipt as the distinguishing factor; both methods have drawbacks. We present an algorithm for distinguishing between symptomatic and smoldering MM using ICD-9-CM (International Classification of Diseases, Ninth Revision, Clinical Modification) codes for the classic defining events of symptomatic MM commonly referred to as the CRAB criteria (hypercalcemia, renal impairment, anemia, and bone lesions). Patients and Methods SEER-Medicare-linked data from 4,187 patients with MM diagnosed between 2007 and 2011 were used for this analysis. Results Eighty-four percent had ICD-9-CM codes consistent with CRAB criteria, whereas only 57% received treatment. Overall survival of patients with symptomatic MM defined as receipt of treatment was 32.3 months versus 26.6 months for the overall population and 22.9 months for patients with symptomatic MM defined by CRAB criteria. Conceptually, removal of patients with smoldering MM should result in a reduction in overall survival; however, the cohort of patients who received treatment tended to be younger and healthier than the overall population, which could have skewed the results. Conclusion The algorithm we present resulted in a larger and more representative sample than classification by treatment status and reduced potential bias that could result from including all patients with smoldering MM in the analysis. Although this study was performed using the SEER-Medicare database, the methodology was broad enough that the algorithm could be extended to additional claims-based data sets with relative ease. [ABSTRACT FROM AUTHOR]

Purpose: To define the biology driving the aggressive nature of acute myeloid leukemia (AML) in elderly patients., Patients and Methods: Clinically annotated microarray data from 425 patients with newly diagnosed de novo AML from two publicly available data sets were analyzed after age-specific cohorts (young or= 55 years; n = 144) were prospectively identified. Gene expression analysis was conducted utilizing gene set enrichment analysis, and by applying previously defined and tested signature profiles reflecting dysregulation of oncogenic signaling pathways, altered tumor environment, and signatures of chemotherapy sensitivity., Results: Elderly AML patients as expected had worse overall survival and event-free survival compared with younger patients. Analysis of oncogenic pathways revealed that older patients had higher probability of RAS, Src, and tumor necrosis factor (TNF) pathway activation (all P < .0001). Older patients were also less sensitive to anthracycline compared with younger patients with AML (P < .0001). Hierarchical clustering revealed that younger AML patients in cluster 2 had clinically worse survival, with high RAS, Src, and TNF pathway activation and in turn were less sensitive to anthracycline compared with patients in cluster 1. However, among elderly patients with AML, those in cluster 1 also demonstrated high RAS, Src, and TNF pathway activation but this did not translate into differences in survival or anthracycline sensitivity., Conclusion: AML in the elderly represents a distinct biologic entity characterized by unique patterns of deregulated signaling pathway variations that contributes to poor survival and anthracycline resistance. These insights should enable development and adjustments of clinically meaningful treatment strategies in the older patient population.