Disparities in Utilization of Autologous Hematopoietic Cell Transplantation for Treatment of Multiple Myeloma

Disparities in Utilization of Autologous Hematopoietic Cell

Transplantation for Treatment of Multiple Myeloma

Luciano J. Costa

_{, Jia-Xing Huang}

_{, Parameswaran N. Hari}

1_{Division of Hematology and Oncology, Department of Medicine, University of Alabama at Birmingham, Birmingham, Alabama} 2_{Center for International Blood and Marrow Transplant Research, Milwaukee, Wisconsin}

3_{Division of Hematology and Oncology, Department of Medicine, Medical College of Wisconsin, Milwaukee, Wisconsin}

Article history: Received 16 October 2014 Accepted 19 December 2014 Key Words: Multiple myeloma Healthcare disparity Peripheral blood stem cell transplantation

Autologous transplantation

a b s t r a c t

Autologous hematopoietic cell transplantation (AHCT) is an established therapy for multiple myeloma (MM), with an impact on quality of remission and survival. We analyzed the role of race, ethnicity, sex, and age disparities in AHCT utilization in the United States. We combined MM incidence derived from the Surveil-lance, Epidemiology and End Results program with transplantation activity reported to the Center for International Blood and Marrow Transplant Research for the period of 2005 to 2009 to assess the impact of disparities in AHCT. Utilization (number of transplantations/new cases) was compared between groups using the relative utilization ratio (RUR), defined as [utilization for a given category]/[utilization for the entire population]. Data were obtained from 22,462 actual MM cases and 13,311 AHCT. The age-adjusted RUR was 1.17 (95% confidence interval [CI], 1.15 to 1.19) among Hispanic Whites (NHW), higher than in non-Hispanic Blacks (NHB) (age-adjusted RUR, .69; 95% CI, .67 to .72;P<.0002), Hispanics (age-adjusted RUR, .64; 95% CI, .60 to .69;P<.002), and Asians (age-adjusted RUR, .65; 95% CI, .58 to .73;P<.0002]. AHCT utilization was higher in men than in women among Hispanics (age-adjusted RUR .72 versus .56,P¼.007), but not among NHW, NHB, or Asians. Sex disparity prevents 1.3% of potential AHCTs in patients with MM (10.4% among Hispanics). Racial-ethnic disparities prevent 13.8% of AHCTs (44.7% in Hispanic and Asians, 39.9% in NHBs). Race-ethnicity disparity greatly affects AHCT utilization in MM. Sex disparity plays a lesser role, except among Hispanics. The ongoing decrease in age disparity will continue to drive major increase of AHCT activity. Two-year and 5-year increases in the age of the AHCT population would result in 12% and 32% increases, respectively, in volume of AHCT.

Ó2015 American Society for Blood and Marrow Transplantation.

INTRODUCTION

Autologous hematopoietic cell transplantation (AHCT) is an established modality in the upfront treatment of patients with multiple myeloma (MM). When employed early in the management of MM in younger patients, AHCT prolongs both the depth and duration of response and, in some studies,

overall survival[1,2]. At the population level, the expansion in

use of AHCT for management of MM over the last 2 decades

has also been linked to improved survival[3-5].

Recently, the feasibility and low toxicity of AHCT have been demonstrated in older patients, with toxicity and disease

control comparable to younger patients[6,7]. Similarly, Black

patients undergoing AHCT for MM have outcomes similar to

their White counterparts[8]but they are less likely to undergo

this treatment[9,10]. Little is known about transplantation

utilization in Hispanics and Asians in the United States. We recently published a report on the increasing but yet low utilization of AHCT among MM patients in the United

States [11]. Here, we combine MM incidence information

from Surveillance, Epidemiology and End Results (SEER)

database with the profile of patients with MM undergoing

AHCT reported to the Center for International Blood and Marrow Transplant Research (CIBMTR) during the same period to understand how race, sex, and age can affect uti-lization of AHCT and how correction of disparities could affect transplantation activity.

METHODS Data Sources

We estimated the number of new MM cases utilizing the National Cancer Institute’s SEER registry. The SEER-18 includes the Atlanta, Con-necticut, Detroit, Hawaii, Iowa, New Mexico, San Francisco-Oakland, Seattle-Puget Sound, Utah, Los Angeles, San Jose-Monterey, Rural Georgia, Alaska

Financial disclosure:See Acknowledgments on page 705.

*Correspondence and reprint requests: Luciano J. Costa, MD, PhD, Department of Medicine and UAB-CCC, 1802 6th Avenue South, Birming-ham, AL 35294.

E-mail address:ljcosta@uabmc.edu(L.J. Costa).

http://dx.doi.org/10.1016/j.bbmt.2014.12.024

1083-8791/Ó2015 American Society for Blood and Marrow Transplantation.

Biology of Blood and

Marrow Transplantation

Native, Greater California, Kentucky, Louisiana, New Jersey, and Greater Georgia tumor registries. It covers 27.8% of the US population and the rep-resentation of each racial and ethnic group is known[12]. To estimate the number of new MM cases (International Classification of Diseases 3 9732/3) diagnosed in the United States during the period of study (2005 to 2009), we inquired the database using the case listing function of SEER*Stat8.1.5. For each case, we extracted age, sex, race, and ethnicity (Hispanic, non-Hispanic). We excluded cases for which the only source of information was a death certificate or autopsy report. By knowing the number of newly diagnosed MM cases for each racial and ethnic category (REC) and the cat-egory’s proportional representation in the database, we were able to esti-mate the approxiesti-mate number of new MM cases in the entire US population. Cases were grouped in 4 RECs: non-Hispanic Whites (NHW), non-Hispanic Blacks (NHB), Hispanics (regardless of race), and Asians. Cases with un-known race or ethnicity were excluded. Another racial group, American Indian/Alaska Native, was not included in the analysis as it accounted for only .2% of the MM cases and .3% of the AHCT.

We obtained the approximate number of AHCT for MM and basic patient demographics using data from the CIBMTR. The CIBMTR is the research affiliation of the International Bone Marrow Transplant Registry and the National Marrow Donor Program. Established in 2004, it receives data from >500 transplantation centers worldwide on allogeneic and autologous he-matopoietic progenitor cell transplantations. Data are submitted to the statistical center at the Medical College of Wisconsin in Milwaukee and the National Marrow Donor Program coordinating center in Minneapolis, where computerized checks for discrepancies, physicians’ review of submitted data, and on-site audits of participating centers ensure data quality. In this analysis, we utilized data regarding recipients offirst AHCT for MM in the United States between 2005 and 2009. The information required consisted of age, sex, race, and ethnicity and was obtained from the pretransplantation essential data form. The CIBMTR does not capture the totality, but instead a known proportion of autologous transplantation events in the United States, (methodology described elsewhere [13]). Therefore, by multiplying the number of registered transplantations by a correction factor, one can arrive at the approximate number of transplantations for the group of interest. For the purpose of the present work, it was assumed that there was no age, sex, race, or ethnicity bias in reporting AHCT procedures.

For residents of the United States, the pretransplantation essential data form allows selection of ethnicity (Hispanic of Latino, not Hispanic, or un-known) and race (White, Black, or African American, Asian, American Indian or Alaska Native, Native Hawaiian, or other Pacific Islander). Contrary to as in SEER, individuals can be identified by more than 1 race. Patients were placed in RECs as described above for SEER. There were 3.2% of AHCT cases iden-tified as“others,”reflecting mostly situations where more than 1 race or no race was selected. These cases were distributed into the main RECs in pro-portion to the number of registered cases for a given age. To ensure that this reassignment did not produce false findings, we performed sensitivity analysis with 2 other scenarios: exclusion of all AHCT with“others” iden-tified as REC and distribution of the“others”into the 4 main categories, proportional to the number of cases for a given age, doubling the weight of the Hispanic and Asian categories. None of these scenarios altered the

findings of this analysis.

Utilization

We assessed utilization as the ratio betweenfirst AHCT for MM and number of newly diagnosed cases in the period of interest. Because the scope of the present work is disparity more than underutilization itself, and to avoid possible errors intrinsic to the correction factor, we chose to work with the concept of relative utilization ratio (RUR). We arrived at RUR for each category of interest by dividing the apparent rate of utilization for a given category by the utilization rate for the entire population. The RUR was calculated for each sex, REC, and age. The population of women is slightly older than the population of men with MM. RECs also have a diverse age structure[12]. Therefore, we also compared RUR between RECs and between sexes within a given category by adjusting the age structure of MM cases in each category to match that of the most numerous categories (NHW men). Statistics

We described continuous numerical variables by median and inter-quartile range. Comparisons between proportions were performed using chi-square test. All statistical analysis was performed utilizing SPSS (IBM Corp. Released 2013. IBM SPSS Statistics for Windows, Version 22.0. Armonk, NY). In all inference analyses, 2-sided P values of less than .05 were considered to indicate statistical significance.

RESULTS

We utilized data from 22,462 actual MM cases reported to SEER (excluding 178 cases with unknown race) and 13,311

actual AHCT reported to CIBMTR.Table 1displays the

dis-tribution of MM cases and AHCT cases by sex and REC after

calculation of the total United States’numbers, along with

the median age for each subcategory. Median age at diag-nosis of MM was higher in NHW than in any of the other

RECs (P¼.0002). In all RECs, the age at diagnosis was older in

women than in men. Disparity

Both the unadjusted and the age-adjusted RURs are

dis-played inTable 2for each sex and REC. Higher utilization of

AHCT was detected in men among Hispanics but not among NHB or Asians. Among NHW, the apparently higher RUR in

men becomes nonsignificant when RUR is adjusted for age

structure. Thisfinding suggests that the higher AHCT

utili-zation in NHW men than in NHW women is a function more of younger age at diagnosis than sex.

We subsequently aggregated data from both sexes to compare AHCT utilization among the RECs. Adjusted RUR

was 1.17 (95% confidence interval [CI], 1.15 to 1.19) among

NHW, higher than in NHB (.69; 95% CI, .67 to .72;P<.0002),

Hispanics (.64; 95% CI, .60 to .69;P<.002), and Asians (.65;

95% CI, .58 to .73;P<.0002). In fact,Figure 1displays RUR as

a function of age and sex for all RECs, making clear the highest AHCT utilization among NHW. It is also obvious that AHCT declines with age in all RECs for both men and women, with the decline becoming very pronounced after the age of 55 years.

Even though the reasons for racial and ethnic disparity in transplantation access are unknown, we performed an exploratory analysis in an attempt to recognize possible links

between health care insurance and REC. Insurance

Table 1

Age Distribution of the MM and AHCT Cases according to Race/Ethnicity

Gender NHW NHB Hispanic Asian

MM cases 72.0% 18.7% 6.7% 2.6% Male 55.6% 70 (61-78) 65 (57-74) 65 (55-74) 69 (60-77) Female 44.4% 72 (62-81) 67 (57-76) 66 (56-76) 70 (59-78) AHCT 77.4% 15.8% 5.2% 1.6% Male 58.5% 60 (53-65) 58 (51-64) 56 (49-62) 57 (52-62) Female 41.5% 59 (53-65) 57 (50-62) 57 (48-62) 58 (50-65) Age expressed in median (interquartile range).

Table 2

RUR for AHCT in MM according to Sex and Race/Ethnicity

Unadjusted RUR Adjusted RUR

REC Men Women P Men Women P

NHW 1.13 (1.11-1.15) 1.02 (.99-1.04) .02 1.18 (1.16-1.20) 1.16 (1.13-1.18) .23

NHB .87 (.83-.92) .82 (.78-.87) .11 .70 (.66-.74) .69 (.65-.73) .89

Hispanic .90 (.83-.97) .67 (.60-.74) <.0002 .72 (.66-.79) .56 (.50-.63) .007

Asian .67 (.57-.77) .60 (.49-.69) .35 .66 (.56-.77) .64 (.54-.76) .81

information is available in SEER for the years of 2007 and onward. We found that only 3.1% of the NHW patients with

MM younger than 65 were identified as uninsured versus

8.1% of NHB, 11.9% of Hispanics, and 3.2% of Asians (P_<

.0001). Along the same lines, Medicaid was the primary in-surance for 7.1% of NHW, versus 17.8% of NHB, 28% of

His-panics, and 13.5% of Asians (P<.001).

Effect of Disparities in AHCT Activity

We subsequently aimed to understand the impact of disparities in the overall AHCT utilization and trans-plantation volumes for MM. This was obtained by simulating AHCT numbers for the subcategory of interest when the utilization rates of a reference subcategory are applied to its MM population. Therefore, for estimation of underutilization due to sex disparity, utilization in men was used as reference. For estimation of underutilization due to race, NHW was the reference group.

We found that 1.3% of potential AHCT procedures are unrealized because of sex disparity. This reaches 10.4% among Hispanics and is lower among Asians and NHB (Figure 2A).

A much bigger impact can be attributed to race and ethnicity disparity that prevents 13.8% of AHCT procedures, with a much greater impact seen in NHB, Hispanics, and

Asians (Figure 2B).

The impact of age disparity is more complex. Comorbid-ities impeding AHCT tend to become more common with age and there are very limited data supporting AHCT for the treatment of MM in individuals older than 75. Therefore, some decline in AHCT utilization with age is to be expected. It is known that the median age of MM patients pursuing AHCT

continues to increase[11]. We estimated the potential future

impact of this increase by calculating transplantation vol-umes when the current utilization rate for a given age is replaced by that of a younger age. For example, to calculate the impact of 2-year increase in age at AHCT, we projected transplantation volume by applying to a population of a certain age (eg, 70 years) the current utilization rate of age minus 2 (in this example, 68 years). The impact of age

disparity in AHCT utilization can be seen inFigure 2C. A

2-year increase in age of the AHCT population would lead to a 12% increase, whereas a 5-year increase would lead to a 32% in the volume of AHCT for MM. Because RECs have diverse age structures, they are affected differently by the aging of the AHCT population. A larger effect would be seen among NHW and Asians, whereas a smaller effect would be seen among NHB and Hispanics.

DISCUSSION

Age and sex disparities in access to AHCT for treatment of

MM have been described before[9,10]. A prior publication

from the CIBMTR covering autologous transplantation activity in the United States from 1997 to 2002 found that Whites were more likely than Blacks (odds ratio, 1.72) and males were more likely than females (odds ratio, 1.1) to undergo AHCT for

MM[9]. Importantly, by performing sensitivity analysis, that

study found that selective under-reporting of transplantations performed in ethnic minorities, in addition to being unlikely, is not expected to affect the main conclusion. Similar dispar-ities were seen in transplantation utilization for other hema-tologic disorders. That study, however, did not address transplantation utilization in Hispanic and Asians or sex

dis-parities in access within each specific race.

More recently, Al-Hamadani et al.[10]used data from

the National Cancer Data Base to identify socio-geo-Figure 1.Relative utilization ratio for AHCT in MM according to sex and age in the different race and ethnicity categories.

demographic factors associated with the utilization of AHCT

for upfront treatment of MM. This study identified Black

and Asian races, Hispanic ethnicity, older age, low neigh-borhood income or education, residence in a metro area,

and no or unknown medical insurance as factors associated with lower likelihood of use of upfront AHCT. Of interest, sex was not an independent factor associated with use of AHCT.

Figure 2.Estimated impact of sex (panel A) and race and ethnicity disparities (panel B) in AHCT activity. Potential impact in volume of AHCT for MM resulting from the increase in the age of patients undergoing transplantation (panel C).

The present study explores, in detail, AHCT utilization in all main RECs, addresses the differential impact of sex in transplantation utilization among the different RECs, and provides detailed information on the effect of age in AHCT within each REC. Moreover, we estimated the impact of each recognized disparity in the overall volume of AHCT for MM. Unfortunately, because information linking transplantation

and patient’s place of residence is missing from the CIBMTR

database, it was not possible to confirm the recently found

underutilization of AHCT for MM in the Northeast[10].

Our study confirms the prior demonstration of profound

underutilization of AHCT among Black patients with MM. However, underutilization almost to the same magnitude can be seen among Hispanics and Asians. Unfortunately, the da-tabases used for the study do not provide an explanation for the strong link between REC and AHCT utilization. Recent work using data from the National Cancer Data Base demon-strated that racial disparity in access to AHCT persists even

when adjusted for income and education[10]. It is possible

that patient and physician bias play a role in the decision to pursue transplantation. Another possibility is that income and educational differences within a given geographic area may be linked to both race and transplantation utilization, and these differences are not captured when those variables are analyzed collectively instead of at the individual patient level. Our data also suggest that lack of health care insurance or coverage under Medicaid may be linked to the lower AHCT utilization among NHB and Hispanics, as 2 studies have shown

lower utilization of AHCT among Medicaid beneficiaries

[10,14]. However, it is unlikely that insurance plays a major role among Asians, as the pattern of insurance coverage was very similar to that seen in NHW.

Prior studies addressing disparity in access to AHCT have not explored the interaction between sex and REC or have

not found such an interaction[9,10]. We found, however, that

the underutilization of AHCT among women with MM is only

significant among Hispanics for reasons that are unknown.

Lastly, we estimated the impact of access disparities in AHCT volumes. Racial disparity itself prevents approximately 1 in 7 potential AHCT for MM. Among NHB, Hispanics, and Asians, almost one half of the potential transplantations do not occur because of disparity in access. In addition to the possible detrimental effect on outcome from the lack of transplantation therapy, it is also possible that trans-plantation serves as a surrogate for more advanced tertiary level care. Barriers preventing minority patients from accessing transplantation may be the same as those pre-venting them from accessing advanced supportive care, novel agents, clinical trials, and expert consultation, with potential further impairment of outcomes.

As thefield evolves, age is no longer considered an

ab-solute barrier to transplantation in general [15], although

only 1 positive randomized trial comparing transplantation and nontransplantation therapy in MM included patients

older than 65[16]and 1 study with patients 65 to 75 years

old failed to show advantage of “reduced-intensity”AHCT

over conventional therapy[17]. Age disparity is, however, the

main contributor to AHCT underutilization in MM. As

demonstrated inFigure 2, the evolving inclusion of AHCT as a

viable therapy for older patients will sharply increase transplantation volumes at a rate of approximately 6% for each year of increase in the median age of AHCT patients. Even though this is a positive trend, it will present a further challenge because of the anticipated workforce shortage in

blood and marrow transplantation[18].

In summary, race and ethnicity disparity greatly affects AHCT utilization for management of MM in the United States. Sex disparity plays a much lesser role, except among His-panics. The profound age disparity is decreasing over time and will likely continue to drive major increase of AHCT activity.

ACKNOWLEDGMENTS

The CIBMTR is supported by Public Health Service Grant/ Cooperative Agreement U24-CA76518 from the National Cancer Institute, the National Heart, Lung, and Blood Insti-tute, and the National Institute of Allergy and Infectious Diseases; a grant/cooperative agreement 5U01HL069294 from National Heart, Lung, and Blood Institute and National Cancer Institute; a contract HHSH234200637015C with Health Resources and Services Administration; 2 grants,

N00014-06-1-0704 and N00014-08-1-0058, from the Office

of Naval Research; and grants from Allos, Inc.; Amgen, Inc.; Angioblast; anonymous donation to the Medical College of Wisconsin; Ariad; Be the Match Foundation; Blue Cross and Blue Shield Association; Buchanan Family Foundation;

Car-idianBCT; Celgene Corporation; CellGenix, GmbH; Children’s

Leukemia Research Association; Fresenius-Biotech North America, Inc.; Gamida Cell Teva Joint Venture Ltd.; Gen-entech, Inc.; Genzyme Corporation; GlaxoSmithKline; His-toGenetics, Inc.; Kiadis Pharma; The Leukemia & Lymphoma Society; The Medical College of Wisconsin; Merck & Co, Inc.; Millennium: The Takeda Oncology Co.; Milliman USA, Inc.; Miltenyi Biotec, Inc.; National Marrow Donor Program; Optum Healthcare Solutions, Inc.; Osiris Therapeutics, Inc.;

Otsuka America Pharmaceutical, Inc.; RemedyMD; Sanofi;

Seattle Genetics; Sigma-Tau Pharmaceuticals; Soligenix, Inc.; StemCyte, A Global Cord Blood Therapeutics Co.; Stemsoft Software, Inc.; Swedish Orphan Biovitrum; Tarix Pharma-ceuticals; Teva Neuroscience, Inc.; THERAKOS, Inc.; and Wellpoint, Inc.

This work was presented at the 56th ASH Annual Meeting and Exposition on December 8, 2014.

Financial disclosure:The authors have nothing to disclose. Conflict of interest statement:There are no conflicts of in-terest to report.

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