Visual Abstract
Multiple myeloma (MM) is the leading lymphoid malignancy with significant racial disparities, stemming from disparities in disease epidemiology, disease biology, treatment utilization, and survival. In this review, we highlight important areas of disparities between Black (African descent) and White (European descent) patients with MM by summarizing available evidence and suggesting methods to bridge the gap.
Introduction
Multiple myeloma (MM) is a clonal plasma cell disorder resulting in the accumulation of malignant plasma cells in the bone marrow and the production of monoclonal immunoglobulin and/or light chain, with resultant end-organ damage.1 End-organ damage presents as bone destruction, hypercalcemia, anemia, renal damage, and/or increased susceptibility to infections. MM is the second most common hematological malignancy,2,3 with a global age-standardized incidence rate of 2 per 100 000 people.4 Countries with high social demographic index have a high age-standardized incidence rate due to high aging population and better health care access.4 Risk factors for MM include Black race, older age, physical inactivity, obesity, and diabetes.5,6
Although MM remains an incurable disease, with advances in early prognostic tools and the introduction of novel therapies, survival has dramatically improved in the last decade.7 However, this improvement has not been realized equally across all races.8-10 Disparities in MM between Black and White races exist on many facets, including disparities in disease epidemiology and biology, which ultimately affect clinical phenotype and outcome. Reasons for these disparities are modifiable (ie, socioeconomic status and access to health care utilization) and nonmodifiable (ie, genetic ancestry and familial predisposition), as illustrated in Figure 1. As treatment of MM advances with the development of new drugs, complex immune therapies, and personalized care, it is imperative to dissect existing disparities with the goal to improve survival across races. Therefore, this review aims to discuss existing disparities between Black and White patients with MM, focusing on disease epidemiology, cancer biology, and survival using real-world data.
Existing racial disparity in MM. Inner circle represents primary factors, and the outer cycle represents secondary factors of existing racial disparities between Black and White patients with MM.
Existing racial disparity in MM. Inner circle represents primary factors, and the outer cycle represents secondary factors of existing racial disparities between Black and White patients with MM.
Racial disparity in MM disease epidemiology
A large proportion of MM epidemiological data come from the United States because of the greater sizes of different racial groups and the larger proportion of Black patients (African American individuals). Large population-based studies have demonstrated that Black individuals have a markedly higher prevalence of MM premalignant conditions. In the largest comparison study, to our knowledge, Landgren et al11 quantified the prevalence of monoclonal gammopathy of undetermined significance (MGUS) and subsequent risk of MM among 4 million Black and White male patients admitted to 142 hospitals. The age-adjusted odds ratio of MGUS in Black patients compared with White patients was 3.0 (95% confidence interval [CI], 2.7-3.3). In a more recent study of high sensitivity screening method using mass spectrometry among volunteers aged ≥50 years, the prevalence of MGUS was higher in Black individuals than White individuals: 16.5% vs 10.8% (prevalance ratio, 1.73; 95% CI, 1.31-2.29).12 These were hospital-based studies and included older participants; therefore, the prevalence of an asymptomatic MGUS could have been underestimated. However, in a large population-based study in children and young adults aged 10 to 49 years, the prevalence of MGUS was 4 times higher in Black patients than White patients (0.88% vs 0.22%; P = .001) and, most strikingly, 6 times higher in the 40- to 49-year age group (3.26% vs 0.53%; P = .0013).13 A similar magnitude of MGUS has been replicated in studies conducted in African countries, with an age-adjusted prevalence 1.6- to 1.97-fold higher than White patients.14,15
MGUS clones acquire initial mutations and subsequent secondary genetic events before MM develops.16 The annual progression rate, estimated from long-term MGUS participants followed up for 34 years, is 1%.17 Initial observations suggested that the higher incidence of MM was due to relatively faster disease progression in Black than White patients, but a recent large population MGUS study concluded a slightly higher but statistically similar cumulative risk of developing MM during the first 10 years of follow-up between both races (17% Black vs 15% White individuals).11
MM is a disease of older adults, with median age at diagnosis in the seventh decade of life and <15% of diagnoses are made in those aged <55 years.18 Notably, it presents at a median age up to 7 years younger in Black individuals than White individuals,19 and the proportion of Black patients identified aged under <60 years is twice that of White patients (35.3% vs 16.5%).20 Several other studies have shown relatively younger age at presentation in Black individuals.8,21 The reasons for disparities in disease onset are hypothesized to be due to differences in disease biology at the precursor condition and MM stage.
Disparities in disease presentation/clinical characteristics
Myeloma-defining events are a hallmark of initial disease presentation. It has been consistently observed in racial comparison studies that Black patients with MM present with hemoglobin levels up to 2 g/dL lower than those of White patients.9,22 The noted differences could be the result of known physiological differences in the normal lower hemoglobin levels in Black patients compared with White patients23 or late diagnosis and referral to oncology treatment centers. A number of studies describing disparity in clinical characteristics have concluded that serum calcium (but not fractures) is relatively higher in Black than White patients, possibly because of a higher baseline and lower age-related decline in bone density in this racial group.24 It would be interesting to assess calcium levels between races when the stages of disease are taken into account, because higher calcium levels are associated with advanced disease stage. A high proportion of pathological fracture as the initial presenting feature is a common finding in patients with MM diagnosed in African tertiary hospitals, possibly indicating diagnosis of MM at this late stage of the disease.25-27 Black patients with MM are more likely to have renal dysfunction and advanced chronic kidney disease requiring dialysis than White patients,20,28 both of which are the leading causes of MM emergency admissions.10 The incidence of extramedullary disease (considered a high-risk MM phenotype) is higher in Black patients than White patients (0.16 vs 0.12; incidence rate ratio, 1.39; 95% CI, 1.26-1.52), in a US population–based study.29 Similarly, the annual incidence per 100 000 persons for plasma cell myeloma is more than twice in Black patients compared to White patients (12.3 vs 5.4).30
Disparities in time to diagnosis and time to treatment
The importance of timely care is a major factor in the path to improved outcomes in cancer care and is recognized in many cancers.31 Previous studies have shown the potential benefit of delayed disease progression and reduced skeletal complications with early treatment in MM.32 The presence of myeloma-related symptoms for >6 months before diagnosis is defined as a surrogate for delayed diagnosis and treatment because of its associated complications and shortened progression-free survival compared to symptoms <3 months.33 Longer time to treatment initiation also gives cancer cells more time to evolve, potentially increasing high-risk components and worsening the patient's immune and organ status.
Time to diagnosis, described as the time between the first MM symptom and the actual confirmatory cytological and immunological diagnosis, is often substantial in MM, with a mean diagnostic interval of ∼100 days.34,35 Delays in complete evaluation can subsequently lead to delays in treatment initiation or referral. Using the Surveillance, Epidemiology, and End Results US registry data from 15 360 patients with MM,36 Black patients had a lower frequency of completed diagnostic and risk stratification tests than White patients with MM. More than 12 months from diagnosis to transplant is associated with shorter progression-free survival.37 There are significant delays observed in time to transplant experienced by Black patients with MM compared to Whites at many levels, from significant delays in stem cell collection38 to delays in the time between receipt of induction therapy and referral for stem cell transplant (SCT).9 A single center has reported delays of up to 75 days (median difference) in Black patients compared to White patients undergoing SCT.39 Reasons for delays are multifactorial and can include socioeconomic status and patient baseline functional status.38 Awareness efforts at the health care provider and community levels are needed to address the time gap in minority patients with MM.
Disparities in disease biology
Can differences in race and ancestral immune system explain the existing MM racial biological disparity between Black and White patients? This important question is structured using a logical argument that the immune system is inherited, has racial variations, and is linked to many familiar inflammatory disorders and cancers. Below, we bring forth evidence of existing disparities in myeloma disease biology.
Disparity in B-cell response to antigen and involved immunoglobulin
Recent studies have demonstrated a more intense B-cell humoral response with the production of specific types of immunoglobulins in Black individuals than that seen in White populations after vaccinations and infections. Higher neutralizing immunoglobulin G (IgG) responses in Black individuals to components of inactivated influenza vaccine than in White individuals have been demonstrated.40 Before vaccination, Black patients had higher baseline levels of circulating mature naive, double-negative B cells and antibody-secreting cells, as well as a higher baseline B-cell transcriptome, than White patients.40 Longo et al, in efforts to examine racial differences in B-cell receptor signaling pathway activation in healthy individuals using single-cell network profiling, found differences in B-cell subset frequencies and B-cell receptor (BCR)-mediated signaling pathway activation between Black and White healthy volunteers.41
Identification of involved immunoglobulin is used to characterize MGUS subtypes and their behavior of progression. Individuals with IgA MGUS have a higher risk of progression to malignancy than those with IgG MGUS.42-44 In addition, individuals with small IgG MGUS are considered to be low risk, whereas those with IgA or IgM are at higher risk of progression.45 Furthermore, each type of immunoglobulin is associated with different disease presentation and progression. IgG and IgA MGUS tend to progress to a more advanced premalignant smoldering MM46 or to MM itself, in contrast IgM MGUS that tends to evolve more into Waldenström macroglobulinemia. Consistently, many population-based MGUS and MM studies have demonstrated a higher rate of IgG and a lower rate of IgM in Black patients than White patients,9,14,47-49 reflecting a higher incidence of MM and lower incidence of Waldenström macroglobulinemia in Black patients than White patients.50 In summary, these findings suggest that there is ancestral difference in the overall level of background B-cell immune activity response that may influence disparities seen in MM disease incidence and clinical-pathological features.
Tumor mutation differences
There have been significant efforts to understand MM disease disparity at the cellular/tumor level. A number of studies have revealed a lower incidence of certain high-risk genomic profiles, including certain translocations involving the immunoglobin heavy chain locus, among Black patients than White patients.51-53 In addition, 2 independent studies have revealed a standard risk cytogenetic abnormality t(11;14) found in higher prevalence in White patients than Black patients.54,55 These studies have relied on self-reported race, which is prone to miscategorization. Using genetic ancestry in 881 patients with plasma cell proliferative disorders who had undergone uniform testing to identify primary cytogenetic abnormalities, it was found that the probability of having 1 of 3 specific translocations, namely t(11;14), t(14;16), or t(14;20), was significantly higher in those with the highest African genetic ancestry (≥80%) than those with the lowest African genetic ancestry.56 These contrasting findings call for better-designed studies matched by race with comprehensive probes to determine other mutations that currently limit conclusion.
Manojlovic et al, through somatic whole-exome RNA sequence of tumor cells of newly diagnosed patients with MM, revealed specific genes involved in B-cell malignancies (BCL7A, BRWD3, and AUTS2) with significantly higher mutation frequencies among Black patients and a higher frequency of mutations in TP53 and IRF4 in White patients.52 Lower frequencies of TP53 deletions among Black patients have been confirmed elsewhere.57,SP140, AUTS2, and SETD2 genes are the most frequently mutated genes in Black patients, whereas IRF4 mutations were most common in Hispanic and White patients.58,IRF4 encodes interferon regulatory factor 4, which plays an essential role in controlling B cell to plasma cell differentiation, is central to the pathogenesis of MM,59 and its dysregulation is associated with poor prognosis and poor response to immunomodulatory drugs.60 These novel findings are a first step to understand racial differences in myelomagenesis but should be interpreted with caution due to the nature of the study designs. Their caveats include retrospective identification of self-reported race and underrepresentation of Black patients in the registries.
MM risk loci and familiar/inherited susceptibility
Many genome-wide association studies have discovered risk genetic loci for MM mainly in White populations.61-64 In a large genome-wide association study to uncover MM risk loci in Black patients against 23 known MM risk loci in White patients, 9 loci replicated at a statistically significant level, indicating similar risk loci for MM between the 2 races.65 However, 2 alleles (rs6746082 at 2p23.3 and rs2811710 at 9p21.3) were more common among White patients, and 3 alleles (rs1052501 at 3p22.1, rs4487645 at 7p15.3, and rs1948915 at 8q24.21) were more common in Black patients. In fine mapping of the 22 risk regions, 8 were found to harbor a better marker for MM risk in Black patients. In a meta-analysis of MM risk regions in African and European ancestry populations, Rand et al showed that there are 4 to 5 common risk variants shared across both races; however, an independent signal at chromosome 6p21.33 with rs190055148 variant was observed in African ancestry that will require confirmation in a larger sample and functional characterization.66 Family clusters of MM and MGUS suggest disease heritability and first-degree relatives of patients with MM have up to threefold risk of developing the disease.67,68 In a large pooled data from 11 case-control studies aiming to characterize the association of MM risk with a first-degree relative, the association was particularly strong among Black individuals (odds ratio, 5.52; 95% CI, 1.87-16.27).69 Other studies with much smaller sample sizes have concluded that familial aggregation of MM is stronger in Black individuals than White individuals.70,71 Given high racial admixture in the African American population, genetic data from African patients with MM is a crucial key to answering this complex question.
Disparities in OS
Given the dramatically higher incidence of MM among Black individuals, initial observations suggested that Black patients experienced higher mortality than White patients,72 and in the following years, high-quality independent studies showed inequalities in use of novel agents and SCT resulting in relatively poor overall survival (OS) in Black patients than others.73,74 A large cohort of patients with MM treated with a standard of care showed equal survival advantage between Black and White patients with MM.75 It is therefore important to analyze disparity data with an understanding that cancer survival is influenced by many factors independent of patient characteristics, disease biology, and treatment options. The variables that affect MM survival include, but are not limited to, socioeconomic status (income, education, and insurance) and even geographical location.76,77 It is also imperative to use better comparison measure of disease burden because mortality does not account for higher incidence of disease. In this section, we discuss MM survival disparity using high-quality studies, mainly from the United States, because of the large proportion of Black patients with MM in clinical trials (adjusted for multiple confounders) that use OS with hazard ratio (HR) as a comparison metric, due to its better measure of both disease burden and outcome. These studies are summarized in Table 1.
OS outcomes by receipt of treatment between White and Black patients with MM
Study (author, year) . | Study setting . | Treatment . | Black vs White HR (95% CI) . | Variables adjusted for . |
---|---|---|---|---|
SCT | ||||
Kaur et al20 (2021) | Single center | SCT + induction and systemic therapy | 0.32 (0.07-1.37) | Race, age, risk classification, gender, type and response to induction therapy, and transplant utilization |
Badar et al55 (2020) | Multicenter | SCT + induction/maintenance systemic therapy | 0.53 (0.30-0.93) | Age at transplant, time to transplant, maintenance therapy after transplant, stage at diagnosis, gender, SCT, and comorbidity index |
Ailawadhi et al78 (2020) | Multicenter | SCT + induction/maintenance and systemic therapy | 0.56 (0.35-0.89) | Age group, history of asymptomatic disease, amyloidosis, family history of other cancers, sex, calcium, hemoglobin, and calculated ISS stage |
Lupak et al79 (2021) | Single center | SCT + induction chemotherapy | 0.66 (0.32-1.39) | Cytogenetics, age at diagnosis, comorbidities, induction therapies, and income |
Scott et al74 (2016) | Multicenter | SCT + systemic therapy | 1.7 (1.1-2.5) | High-risk MM, race, ISS/Durie-Salmon stage III, pretransplant response, and planned posttransplant therapy |
No SCT | ||||
Ailawadhi et al78 (2020) | Multicenter | Systemic therapy | 0.86 (0.70-1.06) | Cohort, age group, history of asymptomatic myeloma, history of amyloidosis, family history of other cancers, sex, calcium, hemoglobin, and calculated ISS stage |
Jayakrishnan et al80 (2021) | Multicenter | Systemic therapy | 0.9 (0.87-0.93) | Age, year of diagnosis, comorbidity, sex, lack of insurance or Medicaid insurance, income, facility center type (academic and community), and education |
Kaur et al20 (2021) | Single center | Systemic therapy | 0.83 (0.42-1.75) | Race, age, IMWG risk classification, gender, type and response to induction therapy, and SCT utilization |
Mixed treatment (SCT and/or systemic therapy) | ||||
Kaur et al20 (2021) | Single center | Systemic therapy and transplant | 0.83 (0.42-1.75) | Race, age, IMWG risk classification, gender, type and response to induction therapy, and SCT utilization |
Fiala and Wildes8 (2017) | Multicenter | Systemic therapy and transplant | 0.91 (0.85-0.97) | Demographics (race, sex, year of diagnosis), treatment (SCT and bortezomib use), overall health measures, and potential access barriers |
1.05 (0.99-1.12) | Race, sex, year of diagnosis, and SCT and bortezomib use | |||
1.12 (1.05-1.19) | Race, sex, and year of diagnosis | |||
Fillmore et al81 (2018) | Multicenter | Systemic therapy and transplant | 0.79 (0.72-0.87) | Age, SCT, use of novel therapy, and disease stage |
Ailawadhi et al73 (2017) | Multicenter | Systemic therapy and transplant | 1.11 (1.01-1.22) | Age, sex, rurality, income, stage, and transplantation |
Makhani et al82 (2021) | Multicenter | Not reported | 0.91 (0.85-0.98) | Age, sex, ethnicity, marital status, and area of residence |
Costa et al83 (2016) | Multicenter | Not reported | 1.01 (0.91-1.11) | Age, sex, insurance, education, income, marital status, and demographic area |
Study (author, year) . | Study setting . | Treatment . | Black vs White HR (95% CI) . | Variables adjusted for . |
---|---|---|---|---|
SCT | ||||
Kaur et al20 (2021) | Single center | SCT + induction and systemic therapy | 0.32 (0.07-1.37) | Race, age, risk classification, gender, type and response to induction therapy, and transplant utilization |
Badar et al55 (2020) | Multicenter | SCT + induction/maintenance systemic therapy | 0.53 (0.30-0.93) | Age at transplant, time to transplant, maintenance therapy after transplant, stage at diagnosis, gender, SCT, and comorbidity index |
Ailawadhi et al78 (2020) | Multicenter | SCT + induction/maintenance and systemic therapy | 0.56 (0.35-0.89) | Age group, history of asymptomatic disease, amyloidosis, family history of other cancers, sex, calcium, hemoglobin, and calculated ISS stage |
Lupak et al79 (2021) | Single center | SCT + induction chemotherapy | 0.66 (0.32-1.39) | Cytogenetics, age at diagnosis, comorbidities, induction therapies, and income |
Scott et al74 (2016) | Multicenter | SCT + systemic therapy | 1.7 (1.1-2.5) | High-risk MM, race, ISS/Durie-Salmon stage III, pretransplant response, and planned posttransplant therapy |
No SCT | ||||
Ailawadhi et al78 (2020) | Multicenter | Systemic therapy | 0.86 (0.70-1.06) | Cohort, age group, history of asymptomatic myeloma, history of amyloidosis, family history of other cancers, sex, calcium, hemoglobin, and calculated ISS stage |
Jayakrishnan et al80 (2021) | Multicenter | Systemic therapy | 0.9 (0.87-0.93) | Age, year of diagnosis, comorbidity, sex, lack of insurance or Medicaid insurance, income, facility center type (academic and community), and education |
Kaur et al20 (2021) | Single center | Systemic therapy | 0.83 (0.42-1.75) | Race, age, IMWG risk classification, gender, type and response to induction therapy, and SCT utilization |
Mixed treatment (SCT and/or systemic therapy) | ||||
Kaur et al20 (2021) | Single center | Systemic therapy and transplant | 0.83 (0.42-1.75) | Race, age, IMWG risk classification, gender, type and response to induction therapy, and SCT utilization |
Fiala and Wildes8 (2017) | Multicenter | Systemic therapy and transplant | 0.91 (0.85-0.97) | Demographics (race, sex, year of diagnosis), treatment (SCT and bortezomib use), overall health measures, and potential access barriers |
1.05 (0.99-1.12) | Race, sex, year of diagnosis, and SCT and bortezomib use | |||
1.12 (1.05-1.19) | Race, sex, and year of diagnosis | |||
Fillmore et al81 (2018) | Multicenter | Systemic therapy and transplant | 0.79 (0.72-0.87) | Age, SCT, use of novel therapy, and disease stage |
Ailawadhi et al73 (2017) | Multicenter | Systemic therapy and transplant | 1.11 (1.01-1.22) | Age, sex, rurality, income, stage, and transplantation |
Makhani et al82 (2021) | Multicenter | Not reported | 0.91 (0.85-0.98) | Age, sex, ethnicity, marital status, and area of residence |
Costa et al83 (2016) | Multicenter | Not reported | 1.01 (0.91-1.11) | Age, sex, insurance, education, income, marital status, and demographic area |
IMWG, International Myeloma Working Group; ISS, International Staging System.
Transplant recipients
Initial indication of longer disease-specific survival among Black patients with MM was not translated into improved survival over time given the existing inequalities in treatment utilization. In 2020, Ailawadhi et al investigated the association between race, treatment patterns, and survival outcomes in newly diagnosed MM and found that, after adjustment for several covariates, Black patients who received SCT had significantly longer OS than White patients who underwent SCT (HR, 0.56; 95% CI, 0.35-0.89; P = .0141).78 Similarly, in a larger representative cohort of 3538 patients with MM who underwent autologous SCT, an analysis, limited to those with t(11;14), found that Black patients had superior OS (HR, 0.53; 95% CI, 0.30-0.93; P = .03).55 The maintenance of better OS has also been observed in younger patients (aged <50 years).84 One study observed no difference in OS between the 2 races receiving SCT,85 and 1 study reported OS advantage to White patients,74 although the latter study concluded that the finding was unexpected and should be investigated further.
Nontransplant recipients
In a large real-world data using a multicenter prospective observational cohort, among nontransplant patients OS did not significantly differ by race but favored Black patients (HR, 0.86; 95% CI, 0.70-1.06) when adjusted for age, sex, and family cancer history.78 Better chance of survival among Black than White patients (HR, 0.9; 95% CI, 0.87-0.93; P < .0005) are also reported from the large data of patients after adjustment for social economic status, age, year of diagnosis, comorbidity, and sex, despite slower enrollment rates for Black patients with MM.80
Transplant and systemic therapy recipients
Existing disparities in OS between Black and White patients with MM are partly attributed to inequality in access to novel agents and SCT. Black patients are more likely not to receive proteasome inhibitors and less likely to receive SCT,73 and this underuse contributes to >10% risk of death among Black patients.8 After adjusting for treatment (SCT and proteasome inhibitor use) and treatment access barriers (income and area of residence), no significant difference is seen in OS between Black (HR, 1.05; 95% CI, 0.99-1.12) and White patients with MM (HR, 0.91; 95% CI, 0.85-0.97; P < .01).8 In Europe, 1 study comprising <3.5% Black patients concluded a lower risk of death in the Black patients with MM for both 1-year (HR, 0.66; 95% CI, 0.55-0.79) and 3-year survival (HR, 0.69; 95% CI, 0.58-0.83) than White patients.86
In 2 high-quality studies that did not provide treatment details, 1 concluded that Black patients had a better chance of survival than White patients at both 1 year (HR, 0.91; 95% CI, 0.85-0.98) and 5 years (HR, 0.92; 95% CI, 0.88-0.97),82 and the other concluded no difference in survival outcomes between the 2 races (HR, 1.01; 95% CI, 0.91-1.11).83 With increasing use of cellular and immune therapies, OS is similar between Black and White patients with refractory/relapse MM treated with first generation chimeric antigen receptor T-cell therapy (HR, 1.13; 95% CI, 0.54-2.38).87 Response benefits and progression-free survival to monoclonal antibody against CD38 are similar between the 2 races.88,89
Conclusions
Racial disparities in MM are multifactorial and complex. However, real-world data suggest that improvement in access to approved therapies and increased access to clinical trials in Black populations is the single most important factor in eliminating disparities in survival. We therefore recommend the following to achieve this goal.
Approval for MM clinical trials should consider important recommendations brought forward by key stakeholders (clinical trials, researchers, health care providers, patients, industry partners, and regulators at the US Food and Drug Administration) and specifically have a section on diversity inclusiveness/representation at early stages of trial design.
Strategic efforts in capacity building to conduct clinical trials in African countries are to be encouraged. This is important for informed treatment decisions to physicians in the era of precision medicine.
Eradication of barriers to more equitable treatment access in Black MM communities.
Acknowledgment
The work of E.T. is funded by the Else Kröner-Fresenius Foundation in the framework of the Else Kröner Center Würzburg–Mwanza.
Authorship
Contribution: E.T. wrote and reviewed the manuscript; P.R. and L.R. edited and reviewed the manuscript; and all authors approved the final version of the manuscript.
Conflict-of-interest disclosure: The authors declare no competing financial interests.
Correspondence: Erius Tebuka, Department of Hematology, Catholic University of Health and Allied Sciences, 1464 MWANZA, Mwanza 255, Tanzania; email: eriust@yahoo.com.