Race and Socioeconomic Status Influence Outcomes of UnrelatedDonor Hematopoietic Cell Transplantation

K. Scott Baker1, Stella M. Davies2, Navneet S. Majhail3,4, Anna Hassebroek4, John P.Klein5, Karen K. Ballen6, Carolyn L. Bigelow7, Haydar A. Frangoul8, Cheryl L. Hardy7,Christopher Bredeson9, Jason Dehn10, Debra Friedman7, Theresa Hahn11, GregoryHale12, Hillard M. Lazarus13, C.F. LeMaistre14, Fausto Loberiza15, Dipnarine Maharaj16,Philip McCarthy11, Michelle Setterholm10, Stephen Spellman4, Michael Trigg16, Richard T.Maziarz17, Galen Switzer18, Stephanie J. Lee1, and J. Douglas Rizzo51Fred Hutchinson Cancer Research Center, Seattle WA2Cincinnati Children’s Hospital Medical Center, Cincinnati OH3University of Minnesota, Minneapolis MN4Center for International Blood and Marrow Transplant Research, Minneapolis MN5Center for International Blood and Marrow Transplant Research, Milwaukee WI6Massachusetts General Hospital, Boston MA7University of Mississippi Medical Center, Jackson MS8Vanderbilt University Medical Center, Nashville TN9Medical College of Wisconsin, Milwaukee WI10National Marrow Donor Program, Minneapolis MN11Roswell Park Cancer Institute, Buffalo NY12St. Jude Children's Research Hospital, Memphis TN13University Hospitals Case Medical Center, Cleveland OH14Texas Transplant Institute, San Antonio TX15University of Nebraska Medical Center, Omaha NE16South Florida Bone Marrow/Stem Cell Transplant Institute, Boynton Beach FL; 16 Merck & Co.Inc., Wilmington DE17Oregon Health & Science University, Portland OR18University of Pittsburgh, Pittsburgh PA.

Abstract

© 2009 The American Society for Blood and Marrow Transplantation. Published by Elsevier Inc. All rights reserved.Address correspondence to: K. Scott Baker, MD, MS, Director, Survivoship Program, Fred Hutchinson Cancer Research Center, 1100Fairview Ave N, Mailstop D5-280, Seattle, WA 98109, Phone: 206-667-5594, Fax: 206-661-5899, ksbaker@fhcrc.org.Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customerswe are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resultingproof before it is published in its final citable form. Please note that during the production process errors may be discovered which couldaffect the content, and all legal disclaimers that apply to the journal pertain.Presented in part at the Annual Meeting of the American Society of Hematology, 2007

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Published in final edited form as:Biol Blood Marrow Transplant. 2009 December ; 15(12): 1543–1554. doi:10.1016/j.bbmt.2009.07.023.

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Success of hematopoietic-cell transplantation (HCT) can vary by race, but the impact ofsocioeconomic-status (SES) is not known. To evaluate the role of race and SES, we studied 6207unrelated-donor myeloablative HCT recipients transplanted between 1995–2004 for acute or chronicleukemia or myelodysplastic syndrome. Patients were reported by transplant center to be White(n=5253), African-American (n=368), Asian/Pacific-Islander (n=141), or Hispanic (n=445). Patientincome was estimated from residential ZIP Code at time of HCT. Cox-regression analysis adjustingfor other significant factors showed that African-American (but not Asian or Hispanic) recipientshad worse overall survival (OS) (relative-risk [RR] 1.47 (95% CI 1.29–1.68), P<0.001) comparedto Whites. Treatment-related mortality (TRM) was higher in African-Americans (RR 1.56, (1.34–1.83), P<0.001) and in Hispanics (RR 1.30, (1.11–1.51), P=0.001). Across all racial groups, patientswith median incomes in the lowest quartile (<$34,700) had worse OS (RR 1.15 (1.04–1.26), P=0.005)and higher risks of TRM (RR 1.21 (1.07–1.36), P=0.002). Inferior outcomes among African-Americans are not fully explained by transplant-related factors or SES. Potential other mechanismssuch as genetic polymorphisms that impact drug metabolism or unmeasured co-morbidities,socioeconomic factors and health behaviors may be important. Low SES, regardless of race, has anegative impact on unrelated donor HCT outcomes.

KeywordsAllogeneic hematopoietic cell transplantation; unrelated donor; race; socioeconomic status; survival

INTRODUCTIONThe use of hematopoietic cell transplantation (HCT) is increasing worldwide. The prognosticimpact of patient and donor specific demographic factors has been well described, but thereare limited data regarding the impact of race and socioeconomic status (SES) on outcome ofHCT. Many studies have described racial differences in tumor presentation, histology, stageat diagnosis and response to therapy in cancer patients, including prostate cancer1–3, carcinomaof the breast4,5, colon4, oral cancers5, acute myeloid leukemia (AML)6 and Hodgkinlymphoma7. Possible explanations for these differences might include cultural attitudes inseeking medical care, treatment variability as well as potential lack of access to primary care(and subsequently delayed diagnosis). SES has also been considered as a contributing factorto racial differences in outcome for cancer patients. However, even controlling for stage ofdisease, most studies suggest that SES alone cannot explain a racial difference in outcome8–11.

Until recently, differences in the outcome of ethnic minorities undergoing HCT have not beendescribed in detail. A previous study from the Center for International Blood and MarrowTransplant Research (CIBMTR) compared trends in survival rates in ethnic minorities afterHCT from human leukocyte antigen (HLA)-identical sibling donors12. The study found thatHispanics had lower 1-year and 3-year survival rates compared with Whites, while nodifferences were identified between Whites and African-Americans or Asians12. A follow-upstudy found that the decrease in overall survival among Hispanics was primarily related tohigher risks of treatment failure (death or relapse) and higher risk of overall mortality13.Mielcarek et al, in a cohort of sibling and unrelated donor HCT recipients, have also reporteda significantly higher risk of mortality among African-American HCT recipients compared toWhite recipients.14.

Increased genetic disparity at both the HLA locus and at minor transplantation antigens mayimportantly influence the outcome of HCT. In addition, polymorphism in cytokine genes canalso influence HCT outcomes15,16. These genetic factors might be expected to vary betweenethnicities and may contribute to disparate outcomes. A previous CIBMTR study among

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recipients of sibling donor HCT, performed in collaboration with transplant registries in Japan,Scandinavia and Ireland, showed reduced risk of graft-versus-host disease (GVHD) in the lessgenetically diverse Japanese and Scandinavian populations compared with White-Americanand African-American populations17. However, the risks of GVHD were similar between theIrish and the White-American and African-American populations. The study concluded thatthe etiology of ethnic disparities in GVHD are complex and may include differences in HLAand minor antigen diversity, frequencies of cytokine polymorphisms, and non-genetic variablessuch as diet, environment and differences in GVHD diagnosis and management.

Available studies investigating race in HCT are largely limited to recipients of sibling donorHCT and suggest important and as yet unexplained racial differences. Also, the impact of socio-cultural factors on outcomes of HCT has not been well described14. In the current study weexplore the association of race and SES with outcomes in unrelated HCT recipients.

METHODSData source

The CIBMTR is a research affiliation of the International Bone Marrow Transplant Registry(IBMTR), Autologous Blood and Marrow Transplant Registry (ABMTR) and the NationalMarrow Donor Program (NMDP) that comprises a voluntary working group of more than 450transplantation centers worldwide that contribute detailed data on consecutive allogeneic andautologous hematopoietic SCT to a Statistical Center at the Medical College of Wisconsin inMilwaukee and the NMDP Coordinating Center in Minneapolis. Participating centers arerequired to report all transplants consecutively; compliance is monitored by on-site audits.Patients are followed longitudinally, with yearly follow-up. The overall follow-up of the cohortwas 100% at 1 year and 95% overall and did not differ significantly among the various racialcategories. Computerized checks for errors, physicians’ review of submitted data and on-siteaudits of participating centers ensure data quality. Observational studies conducted by theCIBMTR are done so with a waiver of informed consent and in compliance with HIPAAregulations as determined by the Institutional Review Board and the Privacy Officer of theMedical College of Wisconsin.

ParticipantsThe study included patients who received an unrelated donor allogeneic HCT with amyeloablative preparative regimen using either a bone marrow or peripheral blood stem-cellsource for AML, acute lymphoblastic leukemia (ALL), chronic myeloid leukemia (CML) ormyelodysplastic syndrome (MDS) between 1995 and 2004. Only patients transplanted in acenter in the USA and with available residential postal ZIP Codes were eligible for this analysis;8 patients with missing ZIP Code information were excluded. Patients who received unrelatedumbilical cord blood as donor source (n=163) or had previously undergone HCT (n=516) werealso excluded from the study. Information about patient race was reported by transplant centersand was categorized according to the US Office of Management and Budget classification asWhite, African-American, Hispanic or Asian/Pacific-Islander. Patient income was estimatedby the mean household income of their ZIP Code from the 2004 US Census. Distances betweenthe center of a patient’s residence and the transplant center were approximated using theHaversine approximation on the latitude and longitude of the ZIP Code18. The package “ZIPCode deluxe”19 was used to obtain income and location data from the ZIP Code. All survivingrecipients included in this analysis were retrospectively contacted and provided informedconsent for participation in the National Marrow Donor Program (NMDP) research program.Informed consent was waived by the NMDP Institutional Review Board for all deceasedrecipients. Approximately 10% of surviving patients would not provide consent for use ofresearch data. To adjust for the potential bias introduced by exclusion of non-consenting

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surviving patients, a corrective action plan modeling process randomly excluded appropriatelythe same percentage of deceased patients (n=532) using a biased coin randomization withexclusion probabilities based on characteristics associated with not providing consent for useof the data in survivors20. The final study cohort consisted of 6207 patients (Table 1). Thefollowup completeness index from time of HCT, which is the ratio of total observed person-time and the potential person-time of followup in a study,21 was 98% at 1-year and 90% at 5-years post-HCT.

Outcomes and study definitionsThe primary objective of this study was to determine the impact of race and household incomeon overall survival (OS), disease-free survival (DFS), relapse, and treatment-related mortality(TRM). DFS was defined as survival in complete remission after HCT. For OS, death fromany cause was considered an event. Relapse was defined as disease recurrence at any site. TRMwas defined as death in complete remission. OS, DFS, relapse and TRM were assessed fromthe date of HCT. All patients were assessed for acute and chronic GVHD by standardcriteria22,23.

Based on previous CIBMTR publications of disease specific outcomes and differentialoutcomes in ethnic minorities with related donor transplants,12,13,24–27 disease status wasclassified as early, intermediate or advanced. Early disease included AML and ALL in firstcomplete remission, CML in first chronic phase, and MDS with refractory anemia or refractoryanemia with ringed sideroblasts. AML and ALL in second or greater remission or CML inaccelerated phase or second or greater chronic phase was categorized as intermediate disease.Patients with advanced disease had AML and ALL in relapse or primary induction failure,CML in blast phase, or MDS with refractory anemia with excess blasts or excess blasts intransformation.

The NMDP classification of HLA matching status that allows adequate adjustment for donor-recipient HLA compatibility while accounting for best available resolution of typing was usedto categorize HLA matching status as well-matched, partially-matched or mismatched25.Briefly, well-matched patients had no identified mismatches at HLA-A, -B, -C and -DRB1with low/intermediate or high resolution data available at HLA-A, -B and high resolution -DRB1. Partially-matched patients had a single locus mismatch at any of the 4 loci and/ormissing HLA-C data. Mismatched patients had 2 or more allele or antigen mismatches.

Statistical analysisPatient, disease and HCT related characteristics were compared by Chi-square statistic forcategorical variables and the Kruskal-Wallis test for continuous variables. Probabilities of OSand DFS were calculated using the Kaplan-Meier method. Probabilities of TRM, relapse,neutrophil engraftment and acute and chronic GVHD were calculated by the cumulative-incidence function method.

To adjust for differences in baseline characteristics, multivariate Cox proportional-hazardsregression models were used. Household income was correlated with outcome using a seriesof threshold models in the Cox model framework. These models were then constructed to findcut points that best described impact of income on outcome by picking the model with thelargest partial likelihood28. Associations between each outcome and potential prognosticvariables (Table 2) were evaluated using a stepwise approach. Variables significantlyassociated with each outcome event (P<0.05) were included as covariate factors in subsequentcomparisons. The assumption of proportional hazards was tested in a time-dependent covariatefashion. Results were expressed as relative risks (RR) of each outcome. The models for OS,DFS, relapse and TRM were stratified on Karnofsky Score. The models for acute GVHD and

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chronic GVHD were stratified on patient age. For engraftment, logistic regression was used tomodel the chance of neutrophil recovery at day 28. A similar analysis to the Cox analysis wasperformed; the results are reported as the odds in favor of engraftment. For each outcome themain effects of race and household income were tested for an interaction with each of the othercovariates (including gender) that entered the models. This was done for each outcome. Noneof these were found to be significant at a 5% significance level.

The analysis found a significant transplant center effect using a random effects test on thesurvival times29. To adjust for center, a stepwise regression model was used which includedat each step the main effects as well as all covariates adjusted for in the model for the givenevent. The centers found to enter and stay in the model at a 5% significance level were includedin the final model.

To examine the robustness of our results in patients with high-resolution HLA typing, a subsetanalysis limited to patients with allele-level typing at the HLA-A, -B, -C and -DRB1 loci(n=3864) was performed for the endpoints of OS, DFS, relapse and TRM.

All p-values are two-sided and, to account for multiple comparisons, a p-value <0.01 wasconsidered to be significant. Analyses were performed using SAS software, version 9.1 (SASInstitute, Cary, NC).

RESULTSPatient characteristics

Table 1 describes patient, disease and treatment characteristics by race. Asian/Pacific Islandershad the highest median household income ($50,991) while African-Americans had the lowest($36,275).

Table 3 describes our cohort’s characteristics by socioeconomic status. A greater proportionof African-Americans (45%) belonged to the lowest income quartile (median income <$34,700), compared to Hispanics (35%), Whites (21%) or Asian/Pacific-Islanders (9%).

Race and outcomesIn univariate analyses, African-Americans had the lowest probability of OS and DFS and thehighest rates of TRM (Figure 1 and Figure 2). Cumulative incidence of relapse was similaramong all four racial groups.

In a multivariate analysis adjusting for other prognostic variables (including annual income),African-American race was associated with significantly worse OS and DFS and higher TRMthan Whites (Table 4). Risk of TRM was also increased in Hispanics, but OS and DFS wascomparable. The risk for relapse was similar among the four racial groups. Race had no impacton neutrophil engraftment or risks of grades 2–4 acute GVHD. The RR of grade 3–4 acuteGVHD was slightly higher in African-Americans (1.26 [1.03–1.54], P=NS) while that forchronic GVHD was higher in African-Americans (1.34 [1.10–1.63], P=0.003) and Hispanics(1.25 [1.06–1.48], P=0.008). A subset analysis limited to 3,864 recipients with allele-leveltyping at the HLA-A, -B, -C and -DRB1 loci showed risks for OS, DFS, relapse and TRMsimilar to those observed in analyses that included the whole cohort (data not shown).

Income and outcomesPatients with a median annual income in the lowest quartile (<$37,400) had lower probabilityof OS and DFS and higher rates of TRM (Figure 3 and Figure 4). Relapse was similar in allincome categories.

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In a multivariate analysis adjusting for other prognostic variables (including race), patientswith incomes in the lowest quartile (<$37,400) had significantly worse OS (RR 1.15 [1.04–1.26], P=0.005) and TRM (RR 1.21 [1.07–1.36], P=0.002) than those with incomes in thehighest quartile (>$56,000) (Table 4). Household income had no impact on risks of DFS,relapse, acute GVHD or chronic GVHD. A subset analysis limited to patients with allele-leveltyping again showed risks similar to those observed for the whole cohort (data not shown).

Causes of deathFor the whole cohort, the principal causes of death included recurrence of primary malignancy(25%), infection (20%), organ failure (18%) acute or chronic GVHD (14%) and interstitialpneumonitis (12%), and these did not differ when compared by race or SES. Table 5 describesthe causes of death within and after 100 days following transplantation by race and SES.

DISCUSSIONOur study shows notably decreased survival in African-American unrelated donor HCTrecipients compared with White, Asian and Hispanic recipients, despite adjustment inmultivariate analysis for HLA matching, disease status, family income and other variableslikely to influence outcome. Reduced survival was due to increased TRM in African-Americanrecipients with no increased risk of acute GVHD or relapse detected. There are many possiblereasons for reduced survival in African-American HCT recipients, including biology (e.g.polymorphism at non-HLA loci), access to care including post-HCT follow-up, disparities intreatment or follow-up practices, environmental factors (that may also be influenced by SES),and health behaviors. Additionally there were several differences in baseline patientcharacteristics between the groups. However, the analysis was adjusted for the potential patient,disease, and center characteristics that differ between the groups. If the survival differencesfound were caused by these baseline differences, this adjustment would actually tend to lower,not increase, the reported effect of race. Additionally, there was no evidence of an interactionbetween these factors in the model with race or income.

Biological factors, such as increased genetic polymorphism in African-American recipients,could impact outcomes. It is clear that improved HLA matching improves HCT outcome, andit is known that there is greater diversity at HLA loci in the African-American populationcompared with other races and ethnicities17. In our study, however, outcomes were inferior inAfrican-American recipients even after adjustment for HLA matching with the donor. Thisraises the possibility that genetic variation at other loci may be modifying outcomes. At apopulation level, African-Americans show significantly higher levels of nucleotideheterozygosity compared with Americans of European origin30. Polymorphisms that modifyexpression of cytokine genes have been shown to modify a number of HCT endpoints and itis possible that less favorable alleles may occur more frequently in African-American HCTrecipients12,15,16,31. In agreement with our study, reduced graft survival and OS have beenreported in African-American recipients of renal transplants32, with a similar finding reportedafter liver transplantation in African-American recipients secondary to chronic rejection33. Incancer patients, pharmacogenetic variation in drug metabolism has been reported forcyclophosphamide, methotrexate and busulfan, all of which impacted HCT outcomes34–38.Frequencies of many pharmacogenetic variants influencing metabolism of these drugs vary byrace, and future pharmacogenetic studies, which would likely need to be multi-center to achieveadequate sample size, might determine whether this is an important variable, as personalizeddrug dosing might improve outcomes39–41.

Racial disparities exist in health care access and outcomes and are related to SES. It has beenreported that African-American patients with a myocardial infarction and heart failure receiveless intensive and poorer-quality care Whites42,43–45. In a study of Medicare beneficiaries,

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who are presumed to have no financial obstacle to care, treatment and outcomes of heart failurewere similar among White and African-American patients46. All of the patients in our studyreceived HCT so therefore had access to high-cost, technologically demanding care, althoughit is unknown whether their overall insurance coverage was similar. Despite this, survival waslower in those with the lowest income, even after adjustment for race and measured co-morbidities, and the excess mortality was treatment related It is still possible though thatreduced access to or utilization of post-HCT follow-up care might contribute to the inferioroutcomes seen in our study.

The mechanism for the excess mortality seen in African-American recipients seems likely tobe complex. Additional contributors may include unmeasured co-morbidities such as poornutrition, inability to comply with medication regimens, and poor access to follow-up care. Inaddition, the National Health and Nutrition Examination Survey reports increased frequencyof high blood pressure, high body mass index, physical inactivity and diabetes in African-American women, all of which, as unmeasured co-morbidities, might contribute to increasedlate mortality after HCT47. Addressing and improving such issues is challenging, as some aresocietal rather than medical issues. However, awareness of the problem is an important firststep so that care providers can consider the issues and perhaps provide specific resources forthis high-risk population after leaving the transplant center.

Similar to the findings in our study, low SES, assessed independently of race, has been reportedto have an adverse impact on outcomes of many diseases, including cancer, chronic renaldisease and solid organ transplantation38,48,49. Mackillop et al. studied the impact of SES onoutcome of treatment of cancer in Ontario, Canada, where the heath system is designed toprovide equitable access to healthcare for all50. Their study demonstrated higher mortality ratesfrom cancer among poorer communities compared with wealthier areas. Recipients of renaland liver transplants with private insurance have been reported to have better survival thanMedicare recipients, but SES measured by census tract was not associated with outcome.51

The difference in these observations may reflect the dominant influence of the quality of thesurgical procedure and inpatient hospital care on long-term outcomes of solid organtransplantation, in contrast to HCT where the period of immune reconstitution is long (lastingmonths to years) and the incidence of late mortality after the patient has left the transplantcenter is significant51. Clearly, low SES has a significant negative impact on the unrelateddonor HCT outcomes and transplant centers need to carefully examine and optimize theresources available to these individuals during the peri-HCT time period as well as duringongoing long-term follow-up.

Despite the large size of this study and the meaningful cohorts of racial minority groups, thereare limitations that should be considered. Our study only included patients who actuallyreceived HCT and thus we could not address the impact of race or SES on access totransplantation. A challenge for our study, in common with all studies of race, is a lack ofprecision in the definition of race. In our study race was reported by the transplant center, andmay not reflect accurately persons of mixed heritage. While the relative proportions of minorityracial groups in this study do not match that of the US population we feel this is less of an issuerelated to access to care, or to misclassification of race, but rather due to the fact that minoritiesare underrepresented in the unrelated donor pool making it more difficult to obtain a donor forminority patients. Additionally, cancer incidence rates for acute leukemia have been shown tovary by race with a higher incidence being found in Whites compared to Blacks.52 Also, wedo not have data to reflect the insurance status of patients represented in the study. Also, ourstudy could not address other important factors that may impact access to transplant and accessto and quality of post-transplant care. Some of these factors, for instance insurance coverage,lack of adequate support services and cultural biases, are potentially modifiable. In addition,socioeconomic status was estimated from Zip code of residence and was not self-reported by

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patients. Despite these limitations, we believe our data indicate importantly inferior outcomesin African-American unrelated donor HCT recipients that are not explicable by reduced familyincome, and should lead to future biological, sociological and epidemiological studies toaddress and improve this disparity. In addition, we show that reduced family income reducedsurvival in recipients of all races, indicating the need for careful support and follow-up of suchpatients.

AcknowledgmentsThe CIBMTR is supported by Public Health Service Grant/Cooperative Agreement U24-CA76518 from the NationalCancer Institute (NCI), the National Heart, Lung and Blood Institute (NHLBI) and the National Institute of Allergyand Infectious Diseases (NIAID); a Grant/Cooperative Agreement 5U01HL069294 from NHLBI and NCI; a contractHHSH234200637015C with Health Resources and Services Administration (HRSA/DHHS); two GrantsN00014-06-1-0704 and N00014-08-1-0058 from the Office of Naval Research; and grants from AABB; Aetna;American Society for Blood and Marrow Transplantation; Amgen, Inc.; Anonymous donation to the Medical Collegeof Wisconsin; Association of Medical Microbiology and Infectious Disease Canada; Astellas Pharma US, Inc.; BaxterInternational, Inc.; Bayer HealthCare Pharmaceuticals; BloodCenter of Wisconsin; Blue Cross and Blue ShieldAssociation; Bone Marrow Foundation; Canadian Blood and Marrow Transplant Group; Celgene Corporation;CellGenix, GmbH; Centers for Disease Control and Prevention; ClinImmune Labs; CTI Clinical Trial and ConsultingServices; Cubist Pharmaceuticals; Cylex Inc.; CytoTherm; DOR BioPharma, Inc.; Dynal Biotech, an InvitrogenCompany; Enzon Pharmaceuticals, Inc.; European Group for Blood and Marrow Transplantation; Gambro BCT, Inc.;Gamida Cell, Ltd.; Genzyme Corporation; Histogenetics, Inc.; HKS Medical Information Systems; Hospira, Inc.;Infectious Diseases Society of America; Kiadis Pharma; Kirin Brewery Co., Ltd.; Merck & Company; The MedicalCollege of Wisconsin; MGI Pharma, Inc.; Michigan Community Blood Centers; Millennium Pharmaceuticals, Inc.;Miller Pharmacal Group; Milliman USA, Inc.; Miltenyi Biotec, Inc.; National Marrow Donor Program; NaturePublishing Group; New York Blood Center; Novartis Oncology; Oncology Nursing Society; Osiris Therapeutics, Inc.;Otsuka Pharmaceutical Development & Commercialization, Inc.; Pall Life Sciences; PDL BioPharma, Inc; Pfizer Inc;Pharmion Corporation; Saladax Biomedical, Inc.; Schering Plough Corporation; Society for Healthcare Epidemiologyof America; StemCyte, Inc.; StemSoft Software, Inc.; Sysmex; Teva Pharmaceutical Industries; The MarrowFoundation; THERAKOS, Inc.; Vidacare Corporation; Vion Pharmaceuticals, Inc.; ViraCor Laboratories;ViroPharma, Inc.; and Wellpoint, Inc. The views expressed in this article do not reflect the official policy or positionof the National Institute of Health, the Department of the Navy, the Department of Defense, or any other agency ofthe U.S. Government.

References1. Asbell SO, Vijayakumar S. Racial differences in prostate-specific antigen levels in patients with local-

regional prostate cancer. Prostate 1997;31:42–46. [PubMed: 9108885]2. Iselin CE, Box JW, Vollmer RT, Layfield LJ, Robertson JE, Paulson DF. Surgical control of clinically

localized prostate carcinoma is equivalent in African-American and white males. Cancer1998;83:2353–2360. [PubMed: 9840535]

3. Kim JA, Kuban DA, el-Mahdi AM, Schellhammer PF. Carcinoma of the prostate: race as a prognosticindicator in definitive radiation therapy. Radiology 1995;194:545–549. [PubMed: 7529936]

4. Mayberry RM, Coates RJ, Hill HA, et al. Determinants of black/white differences in colon cancersurvival. J Natl Cancer Inst 1995;87:1686–1693. [PubMed: 7473817]

5. Arbes SJ, Slade GD. Racial differences in stage at diagnosis of screenable oral cancers in NorthCarolina. J Public Health Dent 1996;56:352–354. [PubMed: 9089532]

6. Rubnitz JE, Lensing S, Razzouk BI, Pounds S, Pui CH, Ribeiro RC. Effect of race on outcome of whiteand black children with acute myeloid leukemia: the St. Jude experience. Pediatr Blood Cancer2007;48:10–15. [PubMed: 16642489]

7. Metzger ML, Castellino SM, Hudson MM, et al. Effect of race on the outcome of pediatric patientswith Hodgkin's lymphoma. J Clin Oncol 2008;26:1282–1288. [PubMed: 18323551]

8. Bain RP, Greenberg RS, Whitaker JP. Racial differences in survival of women with breast cancer. JChronic Dis 1986;39:631–642. [PubMed: 3734019]

9. Moul JW, Douglas TH, McCarthy WF, McLeod DG. Black race is an adverse prognostic factor forprostate cancer recurrence following radical prostatectomy in an equal access health care setting. JUrol 1996;155:1667–1673. [PubMed: 8627850]

Baker et al. Page 8

Biol Blood Marrow Transplant. Author manuscript; available in PMC 2010 December 1.

NIH

-PA Author Manuscript

NIH

-PA Author Manuscript

NIH

-PA Author Manuscript

10. Lannin DR, Mathews HF, Mitchell J, Swanson MS, Swanson FH, Edwards MS. Influence ofsocioeconomic and cultural factors on racial differences in late-stage presentation of breast cancer.Jama 1998;279:1801–1807. [PubMed: 9628711]

11. Franzini L, Williams AF, Franklin J, Singletary SE, Theriault RL. Effects of race and socioeconomicstatus on survival of 1,332 black, Hispanic, and white women with breast cancer. Ann Surg Oncol1997;4:111–118. [PubMed: 9084846]

12. Serna DS, Lee SJ, Zhang MJ, et al. Trends in survival rates after allogeneic hematopoietic stem-celltransplantation for acute and chronic leukemia by ethnicity in the United States and Canada. J ClinOncol 2003;21:3754–3760. [PubMed: 14551294]

13. Baker KS, Loberiza FR Jr, Yu H, et al. Outcome of ethnic minorities with acute or chronic leukemiatreated with hematopoietic stem-cell transplantation in the United States. J Clin Oncol 2005;23:7032–7042. [PubMed: 16145067]

14. Mielcarek M, Gooley T, Martin PJ, et al. Effects of race on survival after stem cell transplantation.Biol Blood Marrow Transplant 2005;11:231–239. [PubMed: 15744242]

15. Cavet J, Middleton PG, Segall M, Noreen H, Davies SM, Dickinson AM. Recipient tumor necrosisfactor-alpha and interleukin-10 gene polymorphisms associate with early mortality and acute graft-versus-host disease severity in HLA-matched sibling bone marrow transplants. Blood 1999;94:3941–3946. [PubMed: 10572111]

16. Dickinson AM, Harrold JL, Cullup H. Haematopoietic stem cell transplantation: can our genes predictclinical outcome? Expert Rev Mol Med 2007;9:1–19. [PubMed: 17976248]

17. Oh H, Loberiza FR Jr, Zhang MJ, et al. Comparison of graft-versus-host-disease and survival afterHLA-identical sibling bone marrow transplantation in ethnic populations. Blood 2005;105:1408–1416. [PubMed: 15486071]

18. Sinnott R. Virtures of the Haversine. Sky and Telescope 1984:159.19. Zip-Codes.com. Zip Code Database-Deluxe Database specifications.20. Farag SSBA, Eapen M, Hurley C, Dupont B, Caligiuri MA, Boudreau C, Nelson G, Oudshoorn M,

van Rood J, Velardi A, Maiers M, Setterholm M, Confer D, Posch PE, Anasetti C, Kamani N, MillerJS, Weisdorf D, Davies SM. KIR Study Group. Center for International Blood and MarrowTransplantation Research. The Effect of KIR Ligand Incompatibility on the Outcome of UnrelatedDonor Transplants: A report from the Center for International Blood and Marrow TransplantResearch, the European Blood and Marrow Transplant Registry and the Dutch Registry. Biology ofBlood and Marrow Transplantation 2006;12:876–884. [PubMed: 16864058]

21. Clark TG, Altman DG, De Stavola BL. Quantification of the completeness of follow-up. Lancet2002;359:1309–1310. [PubMed: 11965278]

22. Przepiorka D, Weisdorf D, Martin P, et al. 1994 Consensus Conference on Acute GVHD Grading.Bone Marrow Transplant 1995;15:825–828. [PubMed: 7581076]

23. Sullivan KM, Agura E, Anasetti C, et al. Chronic graft-versus-host disease and other latecomplications of bone marrow transplantation. Semin Hematol 1991;28:250–259. [PubMed:1887253]

24. Ringden O, Pavletic SZ, Anasetti C, et al. The graft-versus-leukemia effect using matched unrelateddonors is not superior to HLA-identical siblings for hematopoietic stem cell transplantation. Blood2009;113:3110–3118. [PubMed: 19059878]

25. Weisdorf D, Spellman S, Haagenson M, et al. Classification of HLA-matching for retrospectiveanalysis of unrelated donor transplantation: revised definitions to predict survival. Biol BloodMarrow Transplant 2008;14:748–758. [PubMed: 18541193]

26. Szydlo R, Goldman JM, Klein JP, et al. Results of allogeneic bone marrow transplants for leukemiausing donors other than HLA-identical siblings. J Clin Oncol 1997;15:1767–1777. [PubMed:9164184]

27. Pasquini M, Wang Z. CIBMTR summary slides - 2007 (Part 2). CIBMTR Newsletter 2008;14:6–13.28. Klein JaW, JT. Handbook of Statistics. Advances in Survival Analysis. Vol. Vol. 25. Elsevier Science;

2004. Chapter 2 Discretizing a Continuous Covariate in Survival Studies.29. Andersen CA. Score Tests Of Homogeneity For Survival Data. Lifetime Data Analysis 1:145–156.

[PubMed: 9385097]

Baker et al. Page 9

Biol Blood Marrow Transplant. Author manuscript; available in PMC 2010 December 1.

NIH

-PA Author Manuscript

NIH

-PA Author Manuscript

NIH

-PA Author Manuscript

30. Lohmueller KE, Indap AR, Schmidt S, et al. Proportionally more deleterious genetic variation inEuropean than in African populations. Nature 2008;451:994–997. [PubMed: 18288194]

31. Kim DH, Park JY, Sohn SK, Lee NY, Suh JS, Lee KB. The association between multidrug resistance-1gene polymorphisms and outcomes of allogeneic HLA-identical stem cell transplantation.Haematologica 2006;91:848–851. [PubMed: 16769591]

32. Chesney RW, Wyatt RJ. Racial disparities in renal transplantation in children. Pediatrics2003;112:409–411. [PubMed: 12897294]

33. Nair S, Eustace J, Thuluvath PJ. Effect of race on outcome of orthotopic liver transplantation: a cohortstudy. Lancet 2002;359:287–293. [PubMed: 11830194]

34. McDonald GB, Slattery JT, Bouvier ME, et al. Cyclophosphamide metabolism, liver toxicity, andmortality following hematopoietic stem cell transplantation. Blood 2003;101:2043–2048. [PubMed:12406916]

35. Robien K, Schubert MM, Bruemmer B, Lloid ME, Potter JD, Ulrich CM. Predictors of oral mucositisin patients receiving hematopoietic cell transplants for chronic myelogenous leukemia. J Clin Oncol2004;22:1268–1275. [PubMed: 15051775]

36. Srivastava A, Poonkuzhali B, Shaji RV, et al. Glutathione S-transferase M1 polymorphism: a riskfactor for hepatic venoocclusive disease in bone marrow transplantation. Blood 2004;104:1574–1577. [PubMed: 15142875]

37. Robien K, Bigler J, Yasui Y, et al. Methylenetetrahydrofolate reductase and thymidylate synthasegenotypes and risk of acute graft-versus-host disease following hematopoietic cell transplantationfor chronic myelogenous leukemia. Biol Blood Marrow Transplant 2006;12:973–980. [PubMed:16920564]

38. McCune JS, Batchelder A, Deeg HJ, et al. Cyclophosphamide following targeted oral busulfan asconditioning for hematopoietic cell transplantation: pharmacokinetics, liver toxicity, and mortality.Biol Blood Marrow Transplant 2007;13:853–862. [PubMed: 17580264]

39. Suarez-Kurtz G, Pena SD. Pharmacogenomics in the Americas: the impact of genetic admixture. CurrDrug Targets 2006;7:1649–1658. [PubMed: 17168840]

40. Spielman RS, Bastone LA, Burdick JT, Morley M, Ewens WJ, Cheung VG. Common genetic variantsaccount for differences in gene expression among ethnic groups. Nat Genet 2007;39:226–231.[PubMed: 17206142]

41. Zhang W, Duan S, Kistner EO, et al. Evaluation of genetic variation contributing to differences ingene expression between populations. Am J Hum Genet 2008;82:631–640. [PubMed: 18313023]

42. Popescu I, Vaughan-Sarrazin MS, Rosenthal GE. Differences in mortality and use of revascularizationin black and white patients with acute MI admitted to hospitals with and without revascularizationservices. Jama 2007;297:2489–2495. [PubMed: 17565083]

43. Stafford RS, Saglam D, Blumenthal D. National patterns of angiotensin-converting enzyme inhibitoruse in congestive heart failure. Arch Intern Med 1997;157:2460–2464. [PubMed: 9385297]

44. Ayanian JZ, Weissman JS, Chasan-Taber S, Epstein AM. Quality of care by race and gender forcongestive heart failure and pneumonia. Med Care 1999;37:1260–1269. [PubMed: 10599607]

45. Kahn KL, Pearson ML, Harrison ER, et al. Health care for black and poor hospitalized Medicarepatients. Jama 1994;271:1169–1174. [PubMed: 8151874]

46. Rathore SS, Foody JM, Wang Y, et al. Race, quality of care, and outcomes of elderly patientshospitalized with heart failure. Jama 2003;289:2517–2524. [PubMed: 12759323]

47. Winkleby MA, Kraemer HC, Ahn DK, Varady AN. Ethnic and socioeconomic differences incardiovascular disease risk factors: findings for women from the Third National Health and NutritionExamination Survey, 1988–1994. Jama 1998;280:356–362. [PubMed: 9686553]

48. Zell JA, Cinar P, Mobasher M, Ziogas A, Meyskens FL Jr, Anton-Culver H. Survival for patientswith invasive cutaneous melanoma among ethnic groups: the effects of socioeconomic status andtreatment. J Clin Oncol 2008;26:66–75. [PubMed: 18165642]

49. Zell JA, Rhee JM, Ziogas A, Lipkin SM, Anton-Culver H. Race, socioeconomic status, treatment,and survival time among pancreatic cancer cases in California. Cancer Epidemiol Biomarkers Prev2007;16:546–552. [PubMed: 17372250]

50. Mackillop WJ, Zhang-Salomons J, Groome PA, Paszat L, Holowaty E. Socioeconomic status andcancer survival in Ontario. J Clin Oncol 1997;15:1680–1689. [PubMed: 9193369]

Baker et al. Page 10

Biol Blood Marrow Transplant. Author manuscript; available in PMC 2010 December 1.

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-PA Author Manuscript

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-PA Author Manuscript

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-PA Author Manuscript

51. Yoo HY, Thuluvath PJ. Outcome of liver transplantation in adult recipients: influence ofneighborhood income, education, and insurance. Liver Transpl 2004;10:235–243. [PubMed:14762861]

52. SEER Cancer Statistics Review. 1975–2006 [accessed 07-21-2009].http://www.seer.cancer.gov/csr/1975_2006/browse_csr.php?section=13&page=sect_13_table.07.html

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Figure 1.Probability of overall survival by race.

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Figure 2.Cumulative incidence of treatment-related mortality by race.

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Figure 3.Probability of overall survival by income.

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Figure 4.Cumulative incidence of treatment-related mortality by income.

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Baker et al. Page 16Ta

ble

1

Cha

ract

eris

tics o

f pat

ient

s tra

nspl

ante

d at

US

cent

ers w

ho re

ceiv

ed u

nrel

ated

don

or m

yelo

abla

tive

hem

atop

oiet

ic c

ell t

rans

plan

ts fo

r AM

L, A

LL, C

ML,

and

MD

S fr

om 1

995–

2004

by

race

Var

iabl

eW

hite

N (%

)A

fric

an-

Am

eric

anN

(%)

Asi

an/

Paci

ficIs

land

erN

(%)

His

pani

cN

(%)

P V

alue

Num

ber o

f pat

ient

s52

5336

814

144

5N

umbe

r of c

ente

rs11

987

4080

Age

, med

ian

(ran

ge),

year

s35

(<1–

70)

25 (<

1–58

)30

(<1–

56)

22 (<

1–62

)<0

.001

Age

at t

rans

plan

t, ye

ars

<0.0

01

< 1

053

5 (1

0)64

(17)

22 (1

6)99

(22)

1

0–19

683

(13)

83 (2

3)24

(17)

92 (2

1)

20–

2984

6 (1

6)70

(19)

23 (1

6)97

(22)

3

0–39

1091

(21)

65 (1

8)35

(25)

81 (1

8)

40–

4912

91 (2

5)69

(19)

28 (2

0)54

(12)

≥

50

807

(15)

17 (5

)9

(6)

22 (5

)M

ale

gend

er29

79 (5

7)21

4 (5

8)83

(59)

270

(61)

0.39

Med

ian

inco

me,

200

0 a

$44,

776

$36,

275

$50,

991

$40,

111

<0.0

01

Mis

sing

524

3912

60D

ista

nce

to tr

ansp

lant

cen

ter

<0.0

01

< 1

7 M

iles

1109

(21)

159

(43)

64 (4

6)18

1 (4

1)

17–

55 M

iles

1321

(25)

69 (1

9)34

(24)

113

(25)

5

5–15

0 M

iles

1398

(27)

76 (2

1)17

(12)

74 (1

7)

> 1

50 M

iles

1364

(26)

62 (1

7)23

(16)

74 (1

7)

Mis

sing

ZIP

Cod

e61

(1)

2 (<

1)3

(2)

3 (<

1)K

arno

fsky

stat

us0.

06

≥ 9

035

74 (6

8)26

8 (7

3)92

(65)

323

(73)

<

90

1352

(26)

75 (2

0)43

(30)

94 (2

1)

Mis

sing

327

(6)

25 (7

)6

(4)

28 (6

)C

omor

bid

cond

ition

s0.

01

0–1

con

ditio

ns47

92 (9

1)34

2 (9

3)13

6 (9

6)42

0 (9

4)

≥ 2

con

ditio

ns46

1 (9

)26

(7)

5 (4

)25

(6)

Bod

y m

ass i

ndex

, kg/

m2

25 (1

1–44

)24

(11–

42)

21 (1

3–41

)23

(11–

44)

<0.0

01D

isea

se<0

.001

A

ML

1825

(35)

108

(29)

39 (2

8)98

(22)

A

LL12

61 (2

4)90

(24)

48 (3

4)19

3 (4

3)

CM

L15

31 (2

9)15

3 (4

2)39

(28)

121

(27)

M

DS

636

(12)

17 (5

)15

(11)

33 (7

)D

isea

se st

atus

at t

rans

plan

t<0

.001

E

arly

2067

(39)

120

(33)

47 (3

3)15

8 (3

6)

Int

erm

edia

te15

28 (2

9)16

3 (4

4)49

(35)

182

(41)

A

dvan

ced

1490

(28)

80 (2

2)38

(27)

99 (2

2)

Unk

now

n16

8 (3

)5

(1)

7 (5

)6

(1)

HLA

mat

ch st

atus

<0.0

01

Wel

l-mat

ched

2421

(46)

81 (2

2)41

(29)

122

(27)

P

artia

lly m

atch

ed19

39 (3

7)13

5 (3

7)48

(34)

160

(36)

M

ism

atch

ed89

3 (1

7)15

2 (4

1)52

(37)

163

(37)

Rac

e m

atch

(don

or/re

cipi

ent)

<0.0

01

Mat

ch41

38 (7

8)25

1 (6

8)11

6 (8

2)21

1 (4

7)

Mis

mat

ch43

1 (9

)11

0 (3

0)21

(15)

205

(46)

U

nkno

wn

684

(13)

7 (2

)4

(3)

29 (7

)D

onor

age

, med

ian

(ran

ge),

year

s35

(18–

61)

36 (1

9–60

)34

(18–

59)

34 (1

9–59

)0.

09A

ge a

t tra

nspl

ant,

year

s0.

11

18–

1938

(1)

3 (1

)2

(1)

5 (1

)

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Baker et al. Page 17V

aria

ble

Whi

teN

(%)

Afr

ican

-A

mer

ican

N (%

)

Asi

an/

Paci

ficIs

land

erN

(%)

His

pani

cN

(%)

P V

alue

2

0–29

1475

(28)

102

(28)

46 (3

3)12

5 (2

8)

30–

3920

29 (3

9)11

5 (3

1)51

(36)

184

(41)

4

0–49

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(26)

120

(33)

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≥ 5

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10 (7

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Gen

der m

atch

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or/re

cipi

ent)

<0.0

01

Mal

e/m

ale

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103

(28)

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0)14

6 (3

3)

Mal

e/fe

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62 (2

4)72

(20)

34 (2

4)81

(18)

F

emal

e/m

ale

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(18)

111

(30)

41 (2

9)12

4 (2

8)

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fem

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(19)

82 (2

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mat

ch (d

onor

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pien

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ive/

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tive

1945

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63 (1

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(6)

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3)

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ativ

e/po

sitiv

e15

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36 (2

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1 (2

9)

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/neg

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e82

0 (1

6)69

(19)

20 (1

4)72

(16)

P

ositi

ve/p

ositi

ve88

7 (1

7)13

3 (3

6)75

(53)

176

(40)

U

nkno

wn

87 (2

)9

(2)

2 (1

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(2)

Yea

r of t

rans

plan

t<0

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1

995–

1999

2716

(52)

181

(49)

71 (5

0)17

7 (4

0)

200

0–20

0425

37 (4

8)18

7 (5

1)70

(50)

268

(60)

Con

ditio

ning

regi

men

<0.0

01

Bu

+ C

y ±

othe

r10

66 (2

0)50

(14)

16 (1

1)52

(12)

C

y +

TBI ±

oth

er37

20 (7

1)27

9 (7

6)12

0 (8

5)33

6 (7

6)

TB

I ± o

ther

183

(3)

10 (3

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(4)

26 (6

)

Oth

er28

4 (6

)29

(8)

031

(7)

GV

HD

pro

phyl

axis

b

CsA

+ M

TX ±

oth

er26

81 (5

1)16

7 (4

5)86

(61)

187

(42)

T

acro

limus

+ M

TX ±

oth

er12

00 (2

3)85

(23)

25 (1

8)14

4 (3

2)

T-c

ell d

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tion

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her

941

(18)

88 (2

4)16

(11)

73 (1

6)

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or t

acro

limus

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ther

371

(7)

27 (7

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(9)

37 (8

)

Oth

er60

(1)

1 (<

1)1

(<1)

4 (<

1)G

raft

type

0.02

B

one

mar

row

4298

(82)

321

(87)

109

(77)

358

(80)

P

erip

hera

l blo

od95

5 (1

8)47

(13)

32 (2

3)87

(20)

Infu

sed

cell

dose

b

BM

> 2

× 1

0826

59 (6

2)17

3 (5

4)61

(56)

219

(61)

B

M ≤

2 ×

108

1601

(37)

146

(45)

43 (3

9)13

9 (3

9)

BM

mis

sing

38 (<

1)2

(<1)

5 (5

)0

P

B >

5 ×

108

592

(62)

28 (6

0)18

(56)

62 (7

1)

PB

≤ 5

× 1

0829

2 (3

1)19

(40)

12 (3

8)22

(25)

P

B m

issi

ng71

(7)

02

(6)

3 (3

)Ti

me

from

dia

gnos

is to

tran

spla

nt,

med

ian

(ran

ge),

mon

ths

10 (1

–309

)15

(2–2

73)

13 (2

–179

)16

(2–1

70)

<0.0

01

Don

or se

arch

tim

e, m

edia

n(r

ange

), m

onth

s c

Dia

gnos

is to

pre

limin

ary

sear

ch3

(<1–

303)

5 (<

1–26

8)5

(<1–

134)

5 (<

1–16

4)<0

.001

P

relim

inar

y se

arch

to fo

rmal

sear

ch<1

(<1–

116)

<1 (<

1–51

)<1

(<1–

85)

<1 (<

1–41

)0.

03

F

orm

al se

arch

to tr

ansp

lant

3 (<

1–12

5)4

(1–9

1)3

(<1–

89)

4 (1

–58)

<0.0

01Fo

llow

-up

of su

rviv

ors,

med

ian

(ran

ge),

mon

ths

66 (3

–138

)48

(3–1

30)

64 (1

1–12

7)48

(11–

132)

<0.0

01

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Baker et al. Page 18A

bbre

viat

ions

: AM

L, A

cute

mye

loid

leuk

emia

; ALL

, Acu

te ly

mph

obla

stic

leuk

emia

; MD

S, M

yelo

dysp

last

ic sy

ndro

me;

CM

L, C

hron

ic m

yelo

id le

ukem

ia; H

LA, h

uman

-leuk

ocyt

e an

tigen

; CM

V,

cyto

meg

alov

irus;

Cy,

Cyc

loph

osph

amid

e; B

u, B

usul

fan;

TB

I, To

tal b

ody

radi

atio

n; C

sA, C

yclo

spor

ine;

MTX

, Met

hotre

xate

; GV

HD

, gra

ft-ve

rsus

-hos

t dis

ease

; BM

, bon

e m

arro

w; P

B, p

erip

hera

l blo

od

a Bas

ed o

n 20

04 C

ensu

s tra

ct d

ata

linki

ng in

com

e to

resi

dent

ial Z

IP C

ode.

b Uni

varia

te c

ompa

rison

not

don

e du

e to

smal

l cel

l cou

nts

c Prel

imin

ary

sear

ch p

rovi

des a

list

of p

oten

tial d

onor

s at a

giv

en ti

me

but d

oes n

ot in

itiat

e co

ntac

t with

nor

furth

er te

stin

g of

the

dono

rs. I

f the

tran

spla

nt c

ente

r dec

ides

to p

roce

ed w

ith u

nrel

ated

don

orH

CT,

form

al se

arch

is in

itiat

ed o

n be

half

of th

e pa

tient

. Thi

s inc

lude

s con

firm

ator

y H

LA ty

ping

of t

he p

atie

nt a

nd d

onor

and

con

firm

atio

n of

the

avai

labi

lity

of th

e do

nor f

or o

btai

ning

hem

atop

oiet

icst

em c

ells

.

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Baker et al. Page 19

Table 2

Variables tested in multivariate analysis

Main effect variableRace/ethnicity: White* vs. African-American vs. Asian/Pacific Islander vs. HispanicPatient-related variablesAge: ≤ 10* vs. 11–20 vs. 21–30 vs. 31–40 vs. 41–50 vs. > 50Gender: Male* vs. femaleKarnofsky performance status at transplant: < 90% vs. ≥ 90%* vs. missingMedian income: above* vs. below median vs. missingCo-morbid medical conditions: 0–1* vs. ≥ 2 comorbiditiesDistance to transplant center: above* vs. below median vs. missingDisease-related variablesDisease: AML* vs. ALL vs. CML vs. MDSDisease status: early* vs. intermediate vs. advanced diseaseTime from diagnosis to transplant: continuousTransplant-related variablesSource of stem cells: bone marrow* vs. peripheral bloodHLA match: well-matched* vs. partially matched vs. mismatchedDonor age: 18–20* vs. 21–30 vs. 31–40 vs. 41–50 vs. > 50Donor-recipient gender match: F-M vs. M-F vs. M-M* vs. F-FDonor-recipient CMV status: −/−* vs. −/+ vs. +/− vs. +/+ vs. unknownYear of transplant: 1995–1999 vs. 2000–2004*

Conditioning regimen: Bu + Cy ± others vs. Cy + TBI ± others * vs. TBI ± others vs. otherDonor-recipient race match: same ethnicity* vs. disparate ethnicity vs. unknownInfused cell dose: ≤ 2 × 108 vs. > 2 × 108* nucleated cells/kg for bone marrow and ≤ 5 × 108 vs. > 5 × 108 * nucleated cells/kg for peripheral bloodDonor search time (months) (diagnosis to preliminary search, preliminary search to formal search and formal search to transplant): above* vs. below median

Abbreviations: AML, Acute myeloid leukemia; ALL, Acute lymphoblastic leukemia; MDS, Myelodysplastic syndrome; CML, Chronic myeloid leukemia;HLA, human-leukocyte antigen; F, female; M, male; CMV, cytomegalovirus; Cy, Cyclophosphamide; Bu, Busulfan; TBI, Total body radiation

*Reference group

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Baker et al. Page 20Ta

ble

3

Cha

ract

eris

tics o

f pat

ient

s tra

nspl

ante

d at

US

cent

ers w

ho re

ceiv

ed u

nrel

ated

don

or m

yelo

abla

tive

hem

atop

oiet

ic c

ell t

rans

plan

ts fo

r AM

L, A

LL, C

ML,

and

MD

S fr

om 1

995–

2004

by

soci

oeco

nom

ic st

atus

Var

iabl

e

Med

ian

Inco

me

a

<$34

,700

N (%

)$3

4,70

0–43

,600

N (%

)

$43,

600–

56,3

00N

(%)

>$56

,300

N (%

)P

Val

ue

Num

ber o

f pat

ient

s14

1415

4115

1715

59N

umbe

r of c

ente

rs10

711

611

110

7A

ge, m

edia

n (r

ange

), ye

ars

31 (<

1–65

)33

(<1–

67)

34 (<

1–70

)35

(<1–

67)

<0.0

01A

ge a

t tra

nspl

ant,

year

s<0

.001

<

10

172

(12)

189

(12)

167

(11)

177

(11)

1

0–19

234

(17)

215

(14)

216

(14)

191

(12)

2

0–29

264

(19)

264

(17)

245

(16)

233

(15)

3

0–39

298

(21)

316

(21)

303

(20)

316

(20)

4

0–49

293

(21)

351

(23)

370

(24)

388

(25)

≥

50

153

(11)

206

(13)

216

(14)

254

(16)

Mal

e ge

nder

814

(58)

889

(58)

849

(56)

885

(57)

0.76

Rac

e<0

.001

W

hite

1091

(77)

1308

(85)

1321

(87)

1383

(89)

A

fric

an-A

mer

ican

160

(11)

89 (6

)53

(3)

54 (3

)

Asi

an/P

acifi

c Is

land

er12

(1)

37 (2

)28

(2)

57 (4

)

His

pani

c15

1 (1

1)10

7 (7

)11

5 (8

)65

(4)

Dis

tanc

e to

tran

spla

nt c

ente

r<0

.001

<

20

Mile

s27

4 (1

9)31

2 (2

0)41

4 (2

7)50

0 (3

2)

20–

70 M

iles

157

(11)

331

(21)

464

(31)

558

(36)

7

0–17

5 M

iles

509

(36)

505

(33)

353

(23)

169

(11)

>

175

Mile

s47

4 (3

4)39

3 (2

6)28

6 (1

9)33

2 (2

1)K

arno

fsky

stat

us0.

29

≥ 9

095

9 (6

8)10

70 (6

9)10

47 (6

9)10

63 (6

8)

< 9

037

8 (2

7)38

6 (2

5)37

1 (2

4)38

4 (2

5)

Mis

sing

77 (5

)85

(6)

99 (7

)11

2 (7

)C

omor

bid

cond

ition

s0.

21

0–1

con

ditio

ns12

92 (9

1)14

14 (9

2)13

78 (9

1)14

48 (9

3)

≥ 2

con

ditio

ns12

2 (9

)12

7 (8

)13

9 (9

)11

1 (7

)B

ody

mas

s ind

ex, k

g/m

224

(11–

44)

25 (1

2–44

)25

(13–

44)

24 (1

3–43

)0.

008

Dis

ease

0.91

A

ML

471

(33)

508

(33)

511

(34)

520

(33)

A

LL38

2 (2

7)39

0 (2

5)38

4 (2

5)39

1 (2

5)

CM

L41

7 (2

9)46

1 (3

0)44

3 (2

9)46

7 (3

0)

MD

S14

4 (1

0)18

2 (1

2)17

9 (1

2)18

1 (1

2)D

isea

se st

atus

at t

rans

plan

t0.

37

Ear

ly51

5 (3

6)58

8 (3

8)60

2 (4

0)60

8 (3

9)

Int

erm

edia

te46

4 (3

3)48

2 (3

1)44

5 (2

9)47

7 (3

1)

Adv

ance

d40

3 (2

9)42

4 (2

8)41

7 (2

7)42

4 (2

7)

Unk

now

n32

(2)

47 (3

)53

(3)

50 (3

)H

LA m

atch

stat

us0.

009

W

ell-m

atch

ed58

2 (4

1)63

0 (4

1)67

5 (4

4)70

5 (4

5)

Par

tially

mat

ched

523

(37)

584

(38)

531

(35)

586

(38)

M

ism

atch

ed30

9 (2

2)32

7 (2

1)31

1 (2

1)26

8 (1

7)R

ace

mat

ch (d

onor

/reci

pien

t)0.

54

Mat

ch18

7 (1

3)18

0 (1

2)18

8 (1

2)19

0 (1

2)

Mis

mat

ch10

69 (7

6)11

84 (7

7)11

63 (7

7)11

68 (7

5)

Unk

now

n15

8 (1

1)17

7 (1

1)16

6 (1

1)20

1 (1

3)

Biol Blood Marrow Transplant. Author manuscript; available in PMC 2010 December 1.

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NIH

-PA Author Manuscript

Baker et al. Page 21

Var

iabl

e

Med

ian

Inco

me

a

<$34

,700

N (%

)$3

4,70

0–43

,600

N (%

)

$43,

600–

56,3

00N

(%)

>$56

,300

N (%

)P

Val

ue

Don

or a

ge, m

edia

n (r

ange

), ye

ars

35 (1

8–60

)35

(18–

60)

36 (1

8–60

)35

(18–

61)

0.01

1G

ende

r mat

ch (d

onor

/reci

pien

t)0.

89

Mal

e/m

ale

535

(38)

573

(37)

573

(38)

592

(38)

M

ale/

fem

ale

321

(23)

354

(23)

364

(24)

379

(24)

F

emal

e/m

ale

279

(20)

316

(21)

276

(18)

293

(19)

F

emal

e/fe

mal

e27

9 (2

0)29

8 (1

9)30

4 (2

0)29

5 (1

9)C

MV

mat

ch (d

onor

/reci

pien

t)0.

002

N

egat

ive/

nega

tive

417

(29)

511

(33)

543

(36)

546

(35)

N

egat

ive/

posi

tive

456

(32)

412

(27)

416

(27)

434

(28)

P

ositi

ve/n

egat

ive

207

(15)

250

(16)

228

(15)

267

(17)

P

ositi

ve/p

ositi

ve30

8 (2

2)34

2 (2

2)30

4 (2

0)28

8 (1

8)

Unk

now

n26

(2)

26 (2

)26

(2)

24 (2

)Y

ear o

f tra

nspl

ant

0.19

1

995–

1999

741

(52)

761

(49)

783

(52)

766

(49)

2

000–

2004

673

(48)

780

(51)

734

(48)

793

(51)

Con

ditio

ning

regi

men

0.00

3

Bu

+ C

y ±

othe

r23

4 (1

7)30

4 (2

0)33

7 (2

2)28

8 (1

8)

Cy

+ TB

I ± o

ther

1022

(72)

1118

(73)

1045

(69)

1129

(72)

T

BI ±

oth

er72

(5)

47 (3

)51

(3)

50 (3

)

Oth

er86

(6)

72 (5

)84

(6)

92 (6

)G

VH

D p

roph

ylax

is0.

10

CsA

+ M

TX ±

oth

er71

3 (5

0)77

7 (5

0)78

3 (5

2)77

0 (4

9)

Tac

rolim

us +

MTX

± o

ther

300

(21)

356

(23)

342

(23)

404

(26)

T

-cel

l dep

letio

n ±

othe

r27

9 (2

0)28

9 (1

9)26

3 (1

7)25

9 (1

7)

CsA

or t

acro

limus

± o

ther

112

(8)

101

(6)

114

(7)

107

(7)

O

ther

10 (1

)18

(1)

14 (1

)19

(2)

Gra

ft ty

pe0.

007

B

one

mar

row

1201

(85)

1262

(82)

1232

(81)

1251

(80)

P

erip

hera

l blo

od21

3 (1

5)27

9 (1

8)28

5 (1

9)30

8 (2

0)In

fuse

d ce

ll do

se

BM

> 2

× 1

0874

4 (6

2)74

8 (5

9)75

6 (6

1)78

6 (6

3)

BM

≤ 2

× 1

0844

5 (3

7)50

1 (4

0)46

6 (3

8)45

6 (3

6)

BM

mis

sing

12 (1

)13

(1)

10 (1

)9

(1)

P

B >

5 ×

108

132

(62)

181

(65)

178

(62)

190

(62)

0.36

P

B ≤

5 ×

108

68 (3

2)86

(31)

85 (3

0)89

(29)

P

B m

issi

ng13

(6)

12 (4

)22

(8)

29 (9

)Ti

me

from

dia

gnos

is to

tran

spla

nt,

med

ian

(ran

ge),

mon

ths

Don

or se

arch

tim

e, m

edia

n(r

ange

), m

onth

s

12 (2

–309

)11

(1–3

09)

11 (2

–242

)10

(<1–

232)

0.04

D

iagn

osis

to p

relim

inar

yse

arch

4 (<

1–30

0)3

(<1–

303)

3 (<

1–23

1)3

(<1–

192)

0.06

P

relim

inar

y se

arch

to fo

rmal

sear

ch<1

(<1–

69)

<1 (<

1–77

)<1

(<1–

116)

<1 (<

1–10

6)0.

33

F

orm

al se

arch

to tr

ansp

lant

3 (<

1–81

)3

(<1–

94)

3 (<

1–12

1)3

(<1–

125)

0.81

Follo

w-u

p of

surv

ivor

s, m

edia

n(r

ange

), m

onth

s60

(5–1

33)

60 (5

–135

)69

(3–1

38)

64 (3

–137

)<0

.001

Abb

revi

atio

ns: A

ML,

Acu

te m

yelo

id le

ukem

ia; A

LL, A

cute

lym

phob

last

ic le

ukem

ia; M

DS,

Mye

lody

spla

stic

synd

rom

e; C

ML,

Chr

onic

mye

loid

leuk

emia

; HLA

, hum

an-le

ukoc

yte

antig

en; C

MV

,cy

tom

egal

oviru

s; C

y, C

yclo

phos

pham

ide;

Bu,

Bus

ulfa

n; T

BI,

Tota

l bod

y ra

diat

ion;

CsA

, Cyc

losp

orin

e; M

TX, M

etho

trexa

te; G

VH

D, g

raft-

vers

us-h

ost d

isea

se; B

M, b

one

mar

row

; PB

, per

iphe

ral b

lood

Biol Blood Marrow Transplant. Author manuscript; available in PMC 2010 December 1.

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Baker et al. Page 22a B

ased

on

2004

Cen

sus t

ract

dat

a lin

king

inco

me

to re

side

ntia

l ZIP

Cod

e.

Biol Blood Marrow Transplant. Author manuscript; available in PMC 2010 December 1.

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Baker et al. Page 23

Table 4

Multivariate analysis for overall survival, disease-free survival, relapse and transplant-related mortality

VariableRelative risk (95% confidence intervals) a

Overall survival Disease-freesurvival Relapse Transplant-

related mortality

Race White b 1.00 1.00 1.00 1.00 African-American 1.47 (1.29–1.68) d 1.48 (1.30–1.69) d 1.32 (1.03–1.68) 1.56 (1.34–1.83) d Asian/Pacific Islander 0.96 (0.76–1.20) 1.04 (0.83–1.31) 1.13 (0.80–1.61) 0.99 (0.75–1.32) Hispanic 1.15 (1.01–1.30) 1.14 (1.00–1.29) 0.87 (0.70–1.09) 1.30 (1.11–1.51) d

Income c

> $56,300 b 1.00 1.00 1.00 1.00 $43,600–56,300 1.06 (0.97–1.16) 1.03 (0.94–1.13) 0.94 (0.81–1.10) 1.11 (0.99–1.24) $34,700–43,600 1.06 (0.97–1.16) 1.02 (0.93–1.12) 0.97 (0.83–1.13) 1.11 (0.99–1.24) <$34,700 1.15 (1.04–1.26) d 1.12 (1.01–1.23) 1.07 (0.92–1.26) 1.21 (1.07–1.36) d Missing 1.10 (0.86–1.39) 1.08 (0.85–1.38) 0.97 (0.63–1.48) 1.16 (0.87–1.55)

aModels were stratified on Karnofsky performance status prior to hematopoietic cell transplant

bReference group; Table 2 lists variables tested in multivariate analysis

cBased on 2004 Census data linking income to residential ZIP Code

dP<0.01

Biol Blood Marrow Transplant. Author manuscript; available in PMC 2010 December 1.

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Baker et al. Page 24Ta

ble

5

Impo

rtant

cau

ses o

f dea

th b

y ra

ce a

nd so

cioe

cono

mic

stat

us

Var

iabl

eT

otal

deat

hs

Cau

se o

f dea

th

Rel

apse

Infe

ctio

nG

VH

DO

rgan

toxi

city

a

Cau

ses o

f dea

th <

100

day

sR

ace

W

hite

1531

167

(11%

)33

9 (2

2%)

236

(15%

)59

3 (3

9%)

A

fric

an-A

mer

ican

147

10 (7

%)

24 (1

6%)

28 (1

9%)

57 (3

9%)

A

sian

/Pac

ific

Isla

nder

512

(4%

)10

(20%

)8

(16%

)25

(49%

)

His

pani

c13

98

(6%

)32

(23%

)31

(22%

)51

(37%

)In

com

e

> $

56,3

0041

747

(11%

)95

(23%

)69

(17%

)15

1 (3

6%)

$

43,6

00–5

6,30

043

843

(10%

)84

(19%

)75

(17%

)18

0 (4

1%)

$

34,7

00–4

3,60

045

844

(10%

)10

0 (2

2%)

66 (1

4%)

188

(41%

)

< $

34,7

0049

050

(10%

)10

8 (2

2%)

80 (1

6%)

182

(37%

)C

ause

s of d

eath

≥10

0 da

ysR

ace

W

hite

1969

735

(37%

)35

7 (1

8%)

266

(14%

)45

7 (2

3%)

A

fric

an-A

mer

ican

132

40 (3

0%)

30 (2

3%)

22 (1

7%)

27 (2

1%)

A

sian

/Pac

ific

Isla

nder

4621

(46%

)8

(17%

)6

(13%

)10

(22%

)

His

pani

c17

460

(35%

)31

(18%

)25

(14%

)40

(23%

)In

com

e

> $

56,3

0055

021

3 (3

9%)

83 (1

5%)

77 (1

4%)

142

(26%

)

$43

,600

–56,

300

580

207

(36%

)11

3 (2

0%)

77 (1

3%)

131

(23%

)

$34

,700

–43,

600

598

221

(37%

)11

6 (1

9%)

83 (1

4%)

125

(21%

)

<$3

4,70

052

819

3 (3

7%)

103

(20%

)67

(13%

)12

4 (2

4%)

a Incl

udes

pat

ient

s with

cau

se o

f dea

th re

porte

d as

org

an fa

ilure

or i

nter

stiti

al p

neum

oniti

s

Biol Blood Marrow Transplant. Author manuscript; available in PMC 2010 December 1.