Disparities in Access to Hematopoietic Cell Transplant Persist at a Transplant Center

Disparities in Access to Hematopoietic Cell Transplant Persist at a Transplant Center | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Disparities in Access to Hematopoietic Cell Transplant Persist at a Transplant Center Jamie Shoag, Seth Rotz*, Rabi Hanna, Ilia Buhtoiarov, Elizabeth Dewey, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3845742/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 13 Jun, 2024 Read the published version in Bone Marrow Transplantation → Version 1 posted 9 You are reading this latest preprint version Abstract Race, ethnicity, and socioeconomic status impact access to hematopoietic cell transplant (HCT). Whether differences in accessibility occur within HCT centers remains unknown. We performed a single-center retrospective review of 1,102 patients who underwent HCT consultation. We examined the association between race (Black vs. non-Black and White vs. non-White), ethnicity (Hispanic vs. non-Hispanic) and socioeconomic status (defined by zip code median household income quartiles) with receipt of HCT, time to HCT, and Psychosocial Assessment of Candidates for Transplantation (PACT) scores. Race and ethnicity were not associated with receipt of HCT (p>0.20 for all comparisons). Those living in higher income quartiles and those with private insurance were more likely to receive HCT (p=0.02 and p<0.001, respectively). Among HCT recipients, patients of White race had a shorter time to transplant than those of non-White race (p=0.0175). There was a strong association between lower PACT scores and poorer income quartiles (p<0.001). Socioeconomic status impacts receipt of HCT and PACT scores among patients evaluated at an HCT center. Race and ethnicity did not affect receipt of HCT. However, non-White patients waited longer from consultation to transplant. Further investigation as to whether the psychosocial eligibility evaluation impedes access to HCT in vulnerable populations is warranted. Health sciences/Health care/Health services Health sciences/Health care/Public health hematopoietic cell transplant disparities access socioeconomic race Figures Figure 1 Figure 2 Figure 3 Background Hematopoietic cell transplant (HCT) is a curative therapy for many malignant and non-malignant diseases. 1 With advancements in conditioning regimens and donor sources, the number of patients who receive HCT in the United States is increasing. 2 However, racial, ethnic and socioeconomic disparities continue to limit access to patients who would otherwise benefit. 1–4 Prior studies have shown marked disparities in access to HCT. 5–8 However, there is limited knowledge as to where in the journey from diagnosis to transplant inequities occur. There are several barriers a patient must overcome prior to proceeding with HCT. 2 Many impediments, such as referral 9 and travel 10 to a bone marrow transplant center, occur prior to evaluation by the HCT team. 2 Nevertheless, even amongst those referred for consultation, bias may interfere with receipt of transplant via the eligibility determination (Fig. 1 ). The eligibility determination is a multi-disciplinary decision that weighs the risk of morbidity and mortality associated with HCT compared with those of alternative treatment options. 11 Eligibility assessments consider several disease-, patient-, and donor- related factors that influence the anticipated success of transplant. 12 The National Marrow Donor Program also recommends a comprehensive psychosocial assessment that considers any issues that would adversely influence transplant outcomes. 12 The goal of the psychosocial assessment s to ensure patients have the necessary supports to succeed both during and after the HCT process. 13 Due to a lack of prospective data or comprehensive consensus guidelines, psychosocial eligibility assessments vary across transplant centers and determination is made on a case-by-case basis. 11, 12, 14 For solid organ transplantations (SOT), psychosocial evaluations are standard of practice due to a limited supply of organs. 16 There is an association between the Psychosocial Assessment of Candidates for Transplantation (PACT) score and survival in SOT recipients. 18 However, data on the influence of PACT scores on HCT outcomes are conflicting. Some studies report an association between specific psychosocial factors with overall survival or secondary medical outcomes. 19–22 However, others found no association when controlling for transplant-related factors. 19–23 Here, we investigated the association of race, ethnicity, and socioeconomics in the likelihood of proceeding to transplant, time to transplant, and PACT scores among candidates evaluated at a large metropolitan HCT center with the hypothesis that disparities in access to transplant exist even within a transplant center. Methods Data Source and Cohort A retrospective review of records from the Cleveland Clinic Cancer Center Unified Transplant Database (UTD) was performed. The UTD is an institutional clinical research database of all patients evaluated for HCT, including those who do not proceed to transplant. Large national registries typically do not include detailed disease or patient related information necessary to determine whether HCT consultation was indicated, while HCT registries collect comprehensive information on patients who receive HCT but do not have information on patients who do not. 2 Therefore, the UTD provides a unique opportunity to address a critical knowledge gap of potential disparities in receipt of HCT after consultation. The study was conducted under the guidance of the Cleveland Clinic’s Institutional Review Board. Pediatric and adult subjects who underwent consultation for HCT between January 1, 2015 and December 31, 2018 were included. All disease indications were included. Some patients had multiple consultations. For these subjects, a single record was selected consisting of the consultation date closest to the transplant date. For patients with multiple consultations who did not proceed to transplant, the most recent consultation record was selected. Patient characteristics collected included age at consultation, sex (male or female), race, ethnicity, insurance status (Medicaid, Medicare, other, private), median income quartile by zip code at time of assessment, and vital status. Disease and transplant characteristics collected included transplant type (allogeneic, autologous, other), diagnosis (leukemia, myeloma/amyloidosis, myelodysplastic syndrome [MDS]/myeloproliferative neoplasm [MPN]/myelofibrosis, lymphoma, solid tumor, or other), Karnofsky performance score prior to transplant (> 80 or ≤ 80), HCT comorbidity index (HCT-CI), and PACT score. Race, Ethnicity, and Socioeconomic Status Race and ethnicity were self-reported by patients and obtained from registration data in the electronic medical record. Ethnicity was evaluated as Hispanic vs. non-Hispanic, regardless of race. All Black race patients were non-Hispanic. Race was evaluated as Black vs. non-Black and White vs. non-White. This was done to allow explicit analysis of racial and ethnic identity as social constructs that serve as proxies for individual and collective disparities due to structural racism. 24, 25 Small sample sizes precluded modeling of other individual racial categories. As a proxy for socioeconomic status (SES), median income by zip code was obtained from the 2018 Census tables (5-year estimates from American Community Survey) and linked to the patient zip codes. Postal codes from Canada and other areas were excluded. Median incomes were separated into quartile ranges found in 2018 National Inpatient Survey data element definitions from Healthcare Cost and Utilization Project. 26 Quartiles 1 to 4 reflect the poorest to wealthiest populations, respectively. Median income per zip code was chosen as the best measure since addresses were not available for geocoding and determination of the Area Deprivation Index. 27 PACT Scores The PACT scale is a validated and routinely used tool to stratify psychosocial risk among SOT recipients. 16 PACT is an 8-item rating scale with four sections: social support, psychological health, lifestyle factors, and understanding of transplant and follow-up. 17 It also captures scorer’s assessment of a patient’s substance abuse, compliance, and coping strategies. 17 The overall rater’s impression of the patient’s suitability for transplant is assigned a final PACT score. 17 PACT scores are on an ordinal scale. 17 Statistical Analysis Data was reported as frequencies and percentages. Central measures were presented as means ± standard errors or 95% confidence limits or as medians with 25th and 75th percentiles. For comparisons of means, medians, and categorical tests of association, we applied Satterthwaite t-test, Wilcoxon Rank Sum test, or Pearson's chi-square test as appropriate. Significance was set at p < 0.05 unless noted when adjusted for multiple comparisons. Time to event comparisons across strata were made using Kaplan-Meier estimation methods with log-rank test. Time from most recent assessment to initial transplant was tested using Kaplan Meier log rank tests to compare the median (50th percentile) time to initial transplant across demographic factors and diagnosis groups. Wilcoxon test was also used as being more sensitive to differences early in the follow up period. Post hoc tests were performed to determine differences between groups with longer median time to transplant. PACT values (1 through 4) were compared across two-level factors using Cochran-Mantel-Haenzel test with 1 degree of freedom. Cochran-Mantel-Hanszel (CMH) test for trend was applied to test an ordinal trend across PACT scores across other categorical factors. Results Cohort Demographics We identified a total of 1,102 unique records who underwent HCT consultation. The median age at consultation was 60.6 years (interquartile range [IQR] 50.5, 67.0 years). The cohort was 40.9% female. By race and ethnicity, the cohort was 87.5% White (vs. non-White), 9.0% Black (vs. non-Black), and 2.3% Hispanic (vs. non-Hispanic). Most patients (60.2%) had private insurance. At the time of data collection, 43.2% were deceased. By quartiles of median income for patients’ zip code, 22.1% were from quartile (Q) 1 ($1-45,999), 31.3% from Q2 ($46,000-58,999), 31.8% from Q3 ($59,000-78,999), and 14.9% from Q4 ($79,000+). Receipt of HCT Table 1 shows the distribution of patients by receipt of HCT. Over half (59.5%) of patients had an initial transplant in the study period. White race (compared to non-White race), Black race (compared to non-Black race) and Hispanic ethnicity (compared to non-Hispanic ethnicity) were not associated with receipt of HCT (p>0.20 in all three comparisons). Socioeconomic status was associated with receipt of HCT (p=0.02). Patients in the lowest income quartile accounted for 26.3% of those who did not receive HCT but only 19.2% of those receiving HCT. In contrast, patients in the highest income quartile accounted for 13% of those who did not receive HCT but 16.2% of those who received HCT. Insurance type was also associated with receipt of HCT (p<0.001). Patients who were covered by Medicare accounted for 43.7% of those not transplanted but only 25.7% of those who were transplanted. Meanwhile, patients with private insurance accounted for 50.9% of those who did not receive HCT and 65.8% of those who received HCT. More than half (52.6%) of patients who were assessed but did not receive HCT had died by the time data was collected. More than one-third (36.8%) of those assessed and receiving an initial transplant died between receipt of transplant and data collection. Of those who received HCT, more than half were autologous (58.7%) and over a third were allogenic (38.9%). The most common diagnoses were leukemia/lymphoma (52.7%) followed by myeloma/amyloidosis (33.5%). Other diagnoses including MDS/MPN/myelofibrosis, solid tumors and other were less common and thus grouped together for analysis. Time to Transplant among HCT Recipients Table 2 shows the association between patient and transplant characteristics with median time to transplant among HCT recipients. The median time to transplant of 17 days less White race HCT recipients (109 days, 95% CI 105-113 days) than non-White race HCT recipients (126 days, 95% CI 100-142 days), log-rank test (LRT) p=0.02. Median time to transplant did not differ between Black race vs. non-Black race, Hispanic ethnicity vs. non-Hispanic ethnicity or SES. Median time to transplant differed across diagnosis groups (LRT p=0.02). To investigate whether racial differences were due to differences in the prevalence of diagnoses, we investigated time to transplant by White vs. non-White race separately for each diagnosis group. The median time from consultation to transplant for leukemia/lymphoma patients was 31 days longer for non-White race patients (139 days, 95% CI 94-163 days) compared to White race patients (108 days, 95% CI 101-115 days), LRT p=0.57. While these comparisons were not statistically significant, notably with small sample and large variance, the differences may have clinical impact. Conversely, median time to HCT for myeloma/amyloidosis patients was statistically but not clinically longer by 1 day for non-White race patients (109 days, 95% CI 91-143 days) compared to White race patients (108 days, 95% 105-113 days), LRT p<0.01. Among MDS/MPN/myelofibrosis/solid tumor patients, the median time to transplant did not differ by White (117 days, 95% CI 97-143 days) vs. non-White race (130.5 days, 95% CI 94-199 days), LRT p=0.48. Figure 2 illustrates these differences. Characteristics of Patients Who Received HCT by non-White vs. White race Given that time to transplant varied by White vs. non-White race, we investigated differences in transplant characteristics along this axis (Table 3). Stem cell source did not differ across White and non-White race patients (p=0.65). Diagnosis varied across race. White race HCT patients were more likely to have been diagnosed with leukemia/lymphoma (54.8%) whereas non-White race HCT patients were more likely to have been diagnosed with myeloma/amyloidosis (48%), p<0.01. Karnofsky and HCT-CI scores did not differ significantly by White race (p=0.29 and p=0.17, respectively). PACT Scores Lastly, we looked at ordinal PACT scores by patient demographics (Figure 3). PACT scores did not differ in distribution for White vs. non-White patients (CMH test for trend p=0.11), Black race patients vs. non-Black (CMH test for trend p=0.05) or Hispanic ethnicity vs. non-Hispanic ethnicity (CMH test for trend p=0.73). However, a strong bias was observed between median income quartiles and ordinal PACT scores. Higher PACT scores were strongly associated with higher median income for the patient zip code and lower PACT scores were strongly associated with lower median income for the patient zip code (CMH test for trend p<0.001, p<0.01 overall difference). Discussion Disparities in access to HCT persist even after consultation at an HCT center. Our data show that despite being evaluated for HCT at a metropolitan tertiary care hospital, patients residing in disadvantaged neighborhoods were less likely to proceed with transplant. We also found a strong income bias in PACT scores, part of the routine assessment of suitability for transplant. The strong association between SES and PACT scoring raises concern as to whether psychosocial assessment scoring is systematically impeding access to HCT for vulnerable populations. Encouragingly, race and ethnicity were not associated with the likelihood of transplant nor PACT scores. This contrasts with findings of Hong et. al. limited to adult allogeneic transplants which reported patients of White race were nearly 3-times more likely to have higher PACT scores than those of non-White race. 19 We did however find that among patients who received HCT, those of non-White race waited nearly 3-weeks longer for transplant than those of White race, a trend which remained even when analyzed by diagnoses. Our findings need to be interpreted in the context of its study limitations. Firstly, we were unable to ascertain the definitive reason that some patients who were evaluated did not receive HCT and whether those evaluated underwent eligibility assessment. Despite evidence that PACT scores were worse among those of lower socioeconomic status, we did not determine the specific psychosocial barriers that differed across groups. Demographics of the assessors were unknown and therefore we were unable to assess concordance or discordance between race and ethnicity of assessor and patient. Our cohort was primarily non-Hispanic White, likely owing to differences found between White vs. non-Whites but not the other racial and ethnic groupings. We used a neighborhood-level proxy for individual socioeconomic status and did not have access to more granular measures of adverse social determinants of health that may underly the observed disparities. Of note, the cohort had a high mortality rate, particularly among those who did not receive transplant. Mortality is a biased indicator since patients who were assessed but not transplanted may have died before their transplant whereas the data selection of an initial transplant prevented this competing risk. This was a single-center study. While we expect that similar disparities exist across centers, multi-institutional studies are needed to support our results. This study had several strengths. Foremost, our dataset uniquely provided information on patients who did not proceed with HCT. Diverse diagnoses and transplant types allowed us to investigate whether disparities existed for a discrete subset of patients. The analysis was performed post- 2012, when haploidentical HCT became widely available at this institution to limit racial and ethnic disparities in eligibility due to lack of available donors. Lastly, this period also avoids the COVID-19 pandemic wherein clinical practices were altered. There are important donor, recipient, and caregivers considerations in taking a patient to HCT. 11 Survivors of HCT may be cured of their primary disease but suffer other serious complications, such as infertility, graft-versus-host disease, secondary malignancies, financial toxicity and cognitive impairments. 37 Thus a rigorous eligibility assessment is warranted. Other rating scales used to determine transplant eligibility such as the HCT-CI, have discrete criteria to determine the severity of comorbidities. 38 For example, a patient with a body mass index (BMI) > 35 kg/m 2 receives an additional 1-point on the HCT-CI. 38 This helps ensure uniform evaluation of BMI and provides a target BMI to help patients achieve prior to transplant. Contrastingly, the parameters of psychosocial assessments are more subjective. A survey study of HCT professionals given patient vignettes with psychosocial information found complete lack of unanimity in eligibility determinations. 15 Respondents’ determinations were found to be primarily based on their perceived severity of the psychosocial issue. 15 Inarguably, psychosocial factors have the potential to affect HCT outcomes. For example, patients with crowded living spaces during an extremely immunocompromised state are more likely to have infectious complications. 39 Patients without financial stability are less likely to have a full-time caregiver who can take leave from work. 40 However, instead of making these conditions prohibitive to care, efforts should be devoted to help remove modifiable barriers. The decision to bring a patient to HCT is complex. The rigorous eligibility determination process ensures that patients under consideration for HCT are evaluated by an experienced multi-disciplinary team. 12 In an era of expanding donor pools, indications for transplant, reduced intensity conditioning, and cellular therapy 43 , it is the duty of our HCT centers to ensure these assessments are used to improve outcomes rather than limit access to transplant for vulnerable populations. Declarations Data Availability: The individual-level data underlying this article cannot be shared due for the privacy of those that participated in the study. Summary level data without individual level data are available from the corresponding author on reasonable request. Conflicts of Interest: None Financial Disclosures: None References Majhail NS, Omondi NA, Denzen E, Murphy EA, Rizzo JD. Access to hematopoietic cell transplantation in the United States. Biol Blood Marrow Transplant . 2010;16(8):1070-1075. doi:10.1016/j.bbmt.2009.12.529 Hong S, Majhail NS. Increasing access to allotransplants in the United States: the impact of race, geography, and socioeconomics. Hematology . 2021;2021(1):275-280. doi:10.1182/hematology.2021000259 Hamilton BK, Rybicki L, Sekeres M, et al. Racial differences in allogeneic hematopoietic cell transplantation outcomes among African Americans and whites. 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Glob Cardiol Sci Pract . Sep 30 2016;2016(3):e201626. doi:10.21542/gcsp.2016.26 D'Souza A, Fretham C, Lee SJ, et al. Current Use of and Trends in Hematopoietic Cell Transplantation in the United States. Biol Blood Marrow Transplant . Aug 2020;26(8):e177-e182. doi:10.1016/j.bbmt.2020.04.013 Tables Table 1. Distribution of patients assessed for transplant by receipt of HCT Factor Total (N=1,102) Did not receive HCT (N=446) Received HCT (N=656) p-value Age 60.6 [50.5, 67.0] 62.7 [53.1, 68.8] 59.3 [49.4, 66.1] <0.001 a Sex 0.26 b Female 449 (40.9) 172 (38.8) 277 (42.2) Male 650 (59.1) 271 (61.2) 379 (57.8) Race Black 97 (9.0) 44 (10.4) 53 (8.1) 0.20 b Non-Black, known 981 (91.0) 381 (81.8) 600 (91.9) White 943 (87.5) 365 (85.9) 578 (88.5) 0.20 b Non-White 135 (12.5) 60 (14.1) 75 (11.5) Ethnicity 0.24 b Hispanic 25 (2.3) 7 (1.7) 18 (2.8) Non-Hispanic 1,049 (97.7) 416 (98.3) 633 (97.2) Payor <0.001 b Medicaid 42 (4.2) 13 (3.5) 29 (4.7) Medicare 322 (32.6) 164 (43.7) 158 (25.7) Other 30 (3.0) 7 (1.9) 23 (3.7) Private 595 (60.2) 191 (50.9) 404 (65.8) Patient Deceased <0.001 b No 623 (56.8) 209 (47.4) 414 (63.2) Yes 473 (43.2) 232 (52.6) 241 (36.8) Zip code median income quartile (Q) 0.02 a Q1 ($1-45,999) 233 (22.1) 113 (26.3) 120 (19.2) Q2 ($46,000-58,999) 330 (31.3) 128 (29.8) 202 (32.3) Q3 ($59,000-78,999) 335 (31.8) 133 (30.9) 202 (32.3) Q4 ($79,000+) 157 (14.9) 56 (13.0) 101 (16.2) Statistics presented as Median [P25, P75], N (column %). p-values: a=Wilcoxon Rank Sum test, b=Pearson's chi-square test Table 2. Median times from consultation to initial transplant for those who received HCT N Median Time (days), 95% confidence interval (CI) 25 th percentile (days), 95% CI Log rank test p-value Wilcoxon rank sum p-value Overall 656 110 (106, 114) 84 (79, 86) -- -- Sex 0.29 0.42 Female 277 109 (101, 113) 84 (78, 87) Male 378 111 (106, 120) 83 (77, 89) Race Black 53 109 (94, 155) 85 (72, 94) 0.05 0.39 Non-Black 599 110 (106, 114) 84 (79, 87) White 577 109 (105, 113) 82 (79, 86) 0.02 0.07 Non-White 75 126 (100, 142) 88 (76, 97) Ethnicity Hispanic 18 141.5 (87, 199) 87 (49, 121) 0.54 0.33 Non-Hispanic 632 110 (106, 114) 84 (79, 86) Payor Medicaid 29 102 (87, 138) 84 (75, 94) 0.79 0.44 Medicare 158 114 (106, 121) 91 (82, 97) Other 23 119 (88, 183) 87 (56, 99) Private 403 109 (105, 114) 81 (77, 85) Diagnosis Leukemia/Lymphoma 345 110 (102, 117) 83 (78, 87) 0.02 0.35 MDS/MPN/Myelofibrosis/ Solid tumor/Other 90 121.5 (106, 139) 82 (70, 95) Myeloma/amyloidosis 220 108.5 (105, 113) 85 (77, 91) HCT type Allogeneic 255 104 (97, 112) 79 (76, 84) 0.37 0.56 Autologous 384 113 (107, 118) 86.5 (81, 91) Other 16 136 (55, 249) 61.5 (27, 125) Zip code median income quartile Q1 ( $1-45,999) 120 111.5 (99, 141) 84.5 (77, 94) 0.98 0.91 Q2 ($46,000-58,999) 202 113 (106, 120) 88 (83, 92) Q3 ($59,000-78,999) 201 112 (104, 120) 85 (79, 91) Q4 ($79,000+) 101 107 (98, 122) 82 (76, 89) Table 3. Characteristics of patients who received HCT by non-White vs. White race Factor Total (N=653) Non-White (N=75) White (N=578) p-value HCT type 0.65 c Allogenic 254 (38.9) 27 (36.0) 227 (39.3) Autologous 383 (58.7) 47 (62.7) 336 (58.1) Other 16 (2.5) 1 (1.3) 15 (2.6) Diagnosis <0.01 c Leukemia/Lymphoma 344 (52.7) 27 (36.0) 317 (54.8) Myeloma/Amyloidosis 219 (33.5) 36 (48.0) 183 (31.7) MDS/MPN/Myelofibrosis/ Solid tumor/Other 90 (13.8) 12 (16.0) 78 (13.5) Karnofsky scale 0.29 c Karnofsky>80 475 (73.6) 50 (68.5) 425 (74.3) Karnofsky <=80 170 (26.4) 23 (31.5) 147 (25.7) HCT-CI scores 3.0 [1.0, 4.0] 3.0 [1.0, 4.0] 3.0 [1.0, 4.0] 0.17 b Statistics presented as N (column %), Median [P25, P75] p-values: b=Wilcoxon Rank Sum test, c=Pearson's chi-square test. Additional Declarations The authors have declared there is NO conflict of interest to disclose. Cite Share Download PDF Status: Published Journal Publication published 13 Jun, 2024 Read the published version in Bone Marrow Transplantation → Version 1 posted Editorial decision: revise 12 Feb, 2024 Review # 2 received at journal 07 Feb, 2024 Reviewer # 2 agreed at journal 25 Jan, 2024 Review # 1 received at journal 25 Jan, 2024 Reviewer # 1 agreed at journal 24 Jan, 2024 Reviewers invited by journal 10 Jan, 2024 Submission checks completed at journal 09 Jan, 2024 First submitted to journal 08 Jan, 2024 Editor assigned by journal 08 Jan, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3845742","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":266292719,"identity":"e299f5b0-44be-4909-80ea-b6adcec2e6b4","order_by":0,"name":"Jamie Shoag","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAw0lEQVRIiWNgGAWjYDACCRDBYyPHwMD4gCQtacYMDMwGpGhhOJzYQLQW+dnNBz9+kWFO728/zMDwcU8tYS0Gd44lS8vwsOXOOJPMwDjj2XEitEjkGEhL8PDkbpDgP8DMc+AYEQ6bkWP8W4JHIt1AgpmBOC0MN3LMJD/wGCRAtdQQ4bAbaWnWDDwJhiC/HJxx4AAxDks+fPNnz395/vbDjA8+HKgjwmFAwMzbA2EArThMnBbGHz/gbCJtGQWjYBSMghEFAAGuN4+FqizFAAAAAElFTkSuQmCC","orcid":"https://orcid.org/0000-0002-1538-1884","institution":"Cleveland Clinic","correspondingAuthor":true,"prefix":"","firstName":"Jamie","middleName":"","lastName":"Shoag","suffix":""},{"id":266292720,"identity":"9a6f74eb-cf35-4a5e-806b-b4812fe87b5c","order_by":1,"name":"Seth Rotz*","email":"","orcid":"https://orcid.org/0000-0003-2896-1113","institution":"Cleveland Clinic Foundation","correspondingAuthor":false,"prefix":"","firstName":"Seth","middleName":"","lastName":"Rotz*","suffix":""},{"id":266292721,"identity":"acb50946-c0e7-4fd7-ba50-dd23fdfafe52","order_by":2,"name":"Rabi Hanna","email":"","orcid":"https://orcid.org/0000-0001-7518-309X","institution":"Cleveland Clinic","correspondingAuthor":false,"prefix":"","firstName":"Rabi","middleName":"","lastName":"Hanna","suffix":""},{"id":266292722,"identity":"f8fa23c4-71d9-411f-86e8-c29fcc9fa3c0","order_by":3,"name":"Ilia Buhtoiarov","email":"","orcid":"","institution":"Cleveland Clinic","correspondingAuthor":false,"prefix":"","firstName":"Ilia","middleName":"","lastName":"Buhtoiarov","suffix":""},{"id":266292723,"identity":"c7c4cc05-fc63-4258-85e9-b7c977628409","order_by":4,"name":"Elizabeth Dewey","email":"","orcid":"","institution":"Cleveland Clinic Center for Populations Health Research,","correspondingAuthor":false,"prefix":"","firstName":"Elizabeth","middleName":"","lastName":"Dewey","suffix":""},{"id":266292724,"identity":"ed804311-e08e-4654-8684-961d025f867e","order_by":5,"name":"David Bruckman","email":"","orcid":"","institution":"Cleveland Clinic Center for Populations Health Research,","correspondingAuthor":false,"prefix":"","firstName":"David","middleName":"","lastName":"Bruckman","suffix":""},{"id":266292725,"identity":"5b93c607-228a-4c46-899e-c4b58174aa03","order_by":6,"name":"Betty Hamilton","email":"","orcid":"https://orcid.org/0000-0003-1252-6539","institution":"Cleveland Clinic","correspondingAuthor":false,"prefix":"","firstName":"Betty","middleName":"","lastName":"Hamilton","suffix":""}],"badges":[],"createdAt":"2024-01-08 15:23:18","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3845742/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3845742/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41409-024-02327-x","type":"published","date":"2024-06-13T04:00:00+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":49543737,"identity":"9d495416-aa2d-41b4-8583-77bd3f7e81de","added_by":"auto","created_at":"2024-01-12 17:45:25","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":56724,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eProgression map to HCT\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3845742/v1/b9dfbc79161fe66a7d8b60cb.jpg"},{"id":49543738,"identity":"c118b4d2-f795-4861-8ad1-61560bc3aa49","added_by":"auto","created_at":"2024-01-12 17:45:25","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":117427,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eProduct-limit survival estimates for time (days) between latest consultation to initial HCT by diagnosis and race (White vs. non-White)\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3845742/v1/e3b5f56ea0601c954861323f.jpg"},{"id":49543736,"identity":"92f24641-71a1-4718-aa6d-12dd0296e49b","added_by":"auto","created_at":"2024-01-12 17:45:25","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":130029,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDistribution of PACT scores among HCT recipients by race, ethnicity, and SES\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3845742/v1/b15cc383e3dae88e003b0291.jpg"},{"id":58342594,"identity":"e329b511-422b-4012-b773-f5531f88626d","added_by":"auto","created_at":"2024-06-14 07:07:37","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1090872,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3845742/v1/73e3e8d8-9de3-48cc-abc6-8edb73fca86e.pdf"}],"financialInterests":"The authors have declared there is \u003cb\u003eNO\u003c/b\u003e conflict of interest to disclose.","formattedTitle":"Disparities in Access to Hematopoietic Cell Transplant Persist at a Transplant Center","fulltext":[{"header":"Background","content":"\u003cp\u003eHematopoietic cell transplant (HCT) is a curative therapy for many malignant and non-malignant diseases.\u003csup\u003e1\u003c/sup\u003e With advancements in conditioning regimens and donor sources, the number of patients who receive HCT in the United States is increasing.\u003csup\u003e2\u003c/sup\u003e However, racial, ethnic and socioeconomic disparities continue to limit access to patients who would otherwise benefit.\u003csup\u003e1\u0026ndash;4\u003c/sup\u003e\u003c/p\u003e \u003cp\u003ePrior studies have shown marked disparities in access to HCT.\u003csup\u003e5\u0026ndash;8\u003c/sup\u003e However, there is limited knowledge as to where in the journey from diagnosis to transplant inequities occur. There are several barriers a patient must overcome prior to proceeding with HCT.\u003csup\u003e2\u003c/sup\u003e Many impediments, such as referral\u003csup\u003e9\u003c/sup\u003e and travel\u003csup\u003e10\u003c/sup\u003e to a bone marrow transplant center, occur prior to evaluation by the HCT team.\u003csup\u003e2\u003c/sup\u003e Nevertheless, even amongst those referred for consultation, bias may interfere with receipt of transplant via the eligibility determination (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe eligibility determination is a multi-disciplinary decision that weighs the risk of morbidity and mortality associated with HCT compared with those of alternative treatment options.\u003csup\u003e11\u003c/sup\u003e Eligibility assessments consider several disease-, patient-, and donor- related factors that influence the anticipated success of transplant.\u003csup\u003e12\u003c/sup\u003e The National Marrow Donor Program also recommends a comprehensive psychosocial assessment that considers any issues that would adversely influence transplant outcomes.\u003csup\u003e12\u003c/sup\u003e The goal of the psychosocial assessment s to ensure patients have the necessary supports to succeed both during and after the HCT process.\u003csup\u003e13\u003c/sup\u003e Due to a lack of prospective data or comprehensive consensus guidelines, psychosocial eligibility assessments vary across transplant centers and determination is made on a case-by-case basis.\u003csup\u003e11, 12, 14\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eFor solid organ transplantations (SOT), psychosocial evaluations are standard of practice due to a limited supply of organs.\u003csup\u003e16\u003c/sup\u003e There is an association between the Psychosocial Assessment of Candidates for Transplantation (PACT) score and survival in SOT recipients.\u003csup\u003e18\u003c/sup\u003e However, data on the influence of PACT scores on HCT outcomes are conflicting. Some studies report an association between specific psychosocial factors with overall survival or secondary medical outcomes.\u003csup\u003e19\u0026ndash;22\u003c/sup\u003e However, others found no association when controlling for transplant-related factors.\u003csup\u003e19\u0026ndash;23\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eHere, we investigated the association of race, ethnicity, and socioeconomics in the likelihood of proceeding to transplant, time to transplant, and PACT scores among candidates evaluated at a large metropolitan HCT center with the hypothesis that disparities in access to transplant exist even within a transplant center.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eData Source and Cohort\u003c/h2\u003e \u003cp\u003e A retrospective review of records from the Cleveland Clinic Cancer Center Unified Transplant Database (UTD) was performed. The UTD is an institutional clinical research database of all patients evaluated for HCT, including those who do not proceed to transplant. Large national registries typically do not include detailed disease or patient related information necessary to determine whether HCT consultation was indicated, while HCT registries collect comprehensive information on patients who receive HCT but do not have information on patients who do not.\u003csup\u003e2\u003c/sup\u003e Therefore, the UTD provides a unique opportunity to address a critical knowledge gap of potential disparities in receipt of HCT after consultation. The study was conducted under the guidance of the Cleveland Clinic\u0026rsquo;s Institutional Review Board.\u003c/p\u003e \u003cp\u003ePediatric and adult subjects who underwent consultation for HCT between January 1, 2015 and December 31, 2018 were included. All disease indications were included. Some patients had multiple consultations. For these subjects, a single record was selected consisting of the consultation date closest to the transplant date. For patients with multiple consultations who did not proceed to transplant, the most recent consultation record was selected.\u003c/p\u003e \u003cp\u003ePatient characteristics collected included age at consultation, sex (male or female), race, ethnicity, insurance status (Medicaid, Medicare, other, private), median income quartile by zip code at time of assessment, and vital status. Disease and transplant characteristics collected included transplant type (allogeneic, autologous, other), diagnosis (leukemia, myeloma/amyloidosis, myelodysplastic syndrome [MDS]/myeloproliferative neoplasm [MPN]/myelofibrosis, lymphoma, solid tumor, or other), Karnofsky performance score prior to transplant (\u0026gt;\u0026thinsp;80 or \u0026le;\u0026thinsp;80), HCT comorbidity index (HCT-CI), and PACT score.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eRace, Ethnicity, and Socioeconomic Status\u003c/h2\u003e \u003cp\u003eRace and ethnicity were self-reported by patients and obtained from registration data in the electronic medical record. Ethnicity was evaluated as Hispanic vs. non-Hispanic, regardless of race. All Black race patients were non-Hispanic. Race was evaluated as Black vs. non-Black and White vs. non-White. This was done to allow explicit analysis of racial and ethnic identity as social constructs that serve as proxies for individual and collective disparities due to structural racism.\u003csup\u003e24, 25\u003c/sup\u003e Small sample sizes precluded modeling of other individual racial categories.\u003c/p\u003e \u003cp\u003e As a proxy for socioeconomic status (SES), median income by zip code was obtained from the 2018 Census tables (5-year estimates from American Community Survey) and linked to the patient zip codes. Postal codes from Canada and other areas were excluded. Median incomes were separated into quartile ranges found in 2018 National Inpatient Survey data element definitions from Healthcare Cost and Utilization Project.\u003csup\u003e26\u003c/sup\u003e Quartiles 1 to 4 reflect the poorest to wealthiest populations, respectively. Median income per zip code was chosen as the best measure since addresses were not available for geocoding and determination of the Area Deprivation Index.\u003csup\u003e27\u003c/sup\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003ePACT Scores\u003c/h2\u003e \u003cp\u003eThe PACT scale is a validated and routinely used tool to stratify psychosocial risk among SOT recipients.\u003csup\u003e16\u003c/sup\u003e PACT is an 8-item rating scale with four sections: social support, psychological health, lifestyle factors, and understanding of transplant and follow-up.\u003csup\u003e17\u003c/sup\u003e It also captures scorer\u0026rsquo;s assessment of a patient\u0026rsquo;s substance abuse, compliance, and coping strategies.\u003csup\u003e17\u003c/sup\u003e The overall rater\u0026rsquo;s impression of the patient\u0026rsquo;s suitability for transplant is assigned a final PACT score.\u003csup\u003e17\u003c/sup\u003e PACT scores are on an ordinal scale.\u003csup\u003e17\u003c/sup\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eData was reported as frequencies and percentages. Central measures were presented as means\u0026thinsp;\u0026plusmn;\u0026thinsp;standard errors or 95% confidence limits or as medians with 25th and 75th percentiles. For comparisons of means, medians, and categorical tests of association, we applied Satterthwaite t-test, Wilcoxon Rank Sum test, or Pearson's chi-square test as appropriate. Significance was set at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 unless noted when adjusted for multiple comparisons. Time to event comparisons across strata were made using Kaplan-Meier estimation methods with log-rank test.\u003c/p\u003e \u003cp\u003eTime from most recent assessment to initial transplant was tested using Kaplan Meier log rank tests to compare the median (50th percentile) time to initial transplant across demographic factors and diagnosis groups. Wilcoxon test was also used as being more sensitive to differences early in the follow up period. Post hoc tests were performed to determine differences between groups with longer median time to transplant.\u003c/p\u003e \u003cp\u003ePACT values (1 through 4) were compared across two-level factors using Cochran-Mantel-Haenzel test with 1 degree of freedom. Cochran-Mantel-Hanszel (CMH) test for trend was applied to test an ordinal trend across PACT scores across other categorical factors.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cu\u003eCohort Demographics\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eWe identified a total of 1,102 unique records who underwent HCT consultation. The median age at consultation was 60.6 years (interquartile range [IQR] 50.5, 67.0 years). The cohort was 40.9% female. By race and ethnicity, the cohort was 87.5% White (vs. non-White), 9.0% Black (vs. non-Black), and 2.3% Hispanic (vs. non-Hispanic). Most patients (60.2%) had private insurance. At the time of data collection, 43.2% were deceased. By quartiles of median income for patients\u0026rsquo; zip code, 22.1% were from quartile (Q) 1 ($1-45,999), 31.3% from Q2 ($46,000-58,999), 31.8% from Q3 ($59,000-78,999), and 14.9% from Q4 ($79,000+). \u003c/p\u003e\n\u003cp\u003e\u003cu\u003eReceipt of HCT\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eTable 1 shows the distribution of patients by receipt of HCT. Over half (59.5%) of patients had an initial transplant in the study period. White race (compared to non-White race), Black race (compared to non-Black race) and Hispanic ethnicity (compared to non-Hispanic ethnicity) were not associated with receipt of HCT (p\u0026gt;0.20 in all three comparisons). Socioeconomic status was associated with receipt of HCT (p=0.02). Patients in the lowest income quartile accounted for 26.3% of those who did not receive HCT but only 19.2% of those receiving HCT. In contrast, patients in the highest income quartile accounted for 13% of those who did not receive HCT but 16.2% of those who received HCT. Insurance type was also associated with receipt of HCT (p\u0026lt;0.001). Patients who were covered by Medicare accounted for 43.7% of those not transplanted but only 25.7% of those who were transplanted. Meanwhile, patients with private insurance accounted for 50.9% of those who did not receive HCT and 65.8% of those who received HCT. More than half (52.6%) of patients who were assessed but did not receive HCT had died by the time data was collected. More than one-third (36.8%) of those assessed and receiving an initial transplant died between receipt of transplant and data collection. \u003c/p\u003e\n\u003cp\u003eOf those who received HCT, more than half were autologous (58.7%) and over a third were allogenic (38.9%). The most common diagnoses were leukemia/lymphoma (52.7%) followed by myeloma/amyloidosis (33.5%). Other diagnoses including MDS/MPN/myelofibrosis, solid tumors and other were less common and thus grouped together for analysis. \u003c/p\u003e\n\u003cp\u003e\u003cu\u003eTime to Transplant among HCT Recipients\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eTable 2 shows the association between patient and transplant characteristics with median time to transplant among HCT recipients. The median time to transplant of 17 days less White race HCT recipients (109 days, 95% CI 105-113 days) than non-White race HCT recipients (126 days, 95% CI 100-142 days), log-rank test (LRT) p=0.02. Median time to transplant did not differ between Black race vs. non-Black race, Hispanic ethnicity vs. non-Hispanic ethnicity or SES. Median time to transplant differed across diagnosis groups (LRT p=0.02). \u003c/p\u003e\n\u003cp\u003eTo investigate whether racial differences were due to differences in the prevalence of diagnoses, we investigated time to transplant by White vs. non-White race separately for each diagnosis group. The median time from consultation to transplant for leukemia/lymphoma patients was 31 days longer for non-White race patients (139 days, 95% CI 94-163 days) compared to White race patients (108 days, 95% CI 101-115 days), LRT p=0.57. While these comparisons were not statistically significant, notably with small sample and large variance, the differences may have clinical impact. Conversely, median time to HCT for myeloma/amyloidosis patients was statistically but not clinically longer by 1 day for non-White race patients (109 days, 95% CI 91-143 days) compared to White race patients (108 days, 95% 105-113 days), LRT p\u0026lt;0.01. Among MDS/MPN/myelofibrosis/solid tumor patients, the median time to transplant did not differ by White (117 days, 95% CI 97-143 days) vs. non-White race (130.5 days, 95% CI 94-199 days), LRT p=0.48. Figure 2 illustrates these differences.\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eCharacteristics of Patients Who Received HCT by non-White vs. White race\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eGiven that time to transplant varied by White vs. non-White race, we investigated differences in transplant characteristics along this axis (Table 3). Stem cell source did not differ across White and non-White race patients (p=0.65). Diagnosis varied across race. White race HCT patients were more likely to have been diagnosed with leukemia/lymphoma (54.8%) whereas non-White race HCT patients were more likely to have been diagnosed with myeloma/amyloidosis (48%), p\u0026lt;0.01. Karnofsky and HCT-CI scores did not differ significantly by White race (p=0.29 and p=0.17, respectively).\u003c/p\u003e\n\u003cp\u003e\u003cu\u003ePACT Scores\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eLastly, we looked at ordinal PACT scores by patient demographics (Figure 3). PACT scores did not differ in distribution for White vs. non-White patients (CMH test for trend p=0.11), Black race patients vs. non-Black (CMH test for trend p=0.05) or Hispanic ethnicity vs. non-Hispanic ethnicity (CMH test for trend p=0.73). However, a strong bias was observed between median income quartiles and ordinal PACT scores. Higher PACT scores were strongly associated with higher median income for the patient zip code and lower PACT scores were strongly associated with lower median income for the patient zip code (CMH test for trend p\u0026lt;0.001, p\u0026lt;0.01 overall difference). \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eDisparities in access to HCT persist even after consultation at an HCT center. Our data show that despite being evaluated for HCT at a metropolitan tertiary care hospital, patients residing in disadvantaged neighborhoods were less likely to proceed with transplant. We also found a strong income bias in PACT scores, part of the routine assessment of suitability for transplant. The strong association between SES and PACT scoring raises concern as to whether psychosocial assessment scoring is systematically impeding access to HCT for vulnerable populations.\u003c/p\u003e \u003cp\u003eEncouragingly, race and ethnicity were not associated with the likelihood of transplant nor PACT scores. This contrasts with findings of Hong et. al. limited to adult allogeneic transplants which reported patients of White race were nearly 3-times more likely to have higher PACT scores than those of non-White race.\u003csup\u003e19\u003c/sup\u003e We did however find that among patients who received HCT, those of non-White race waited nearly 3-weeks longer for transplant than those of White race, a trend which remained even when analyzed by diagnoses.\u003c/p\u003e \u003cp\u003eOur findings need to be interpreted in the context of its study limitations. Firstly, we were unable to ascertain the definitive reason that some patients who were evaluated did not receive HCT and whether those evaluated underwent eligibility assessment. Despite evidence that PACT scores were worse among those of lower socioeconomic status, we did not determine the specific psychosocial barriers that differed across groups. Demographics of the assessors were unknown and therefore we were unable to assess concordance or discordance between race and ethnicity of assessor and patient. Our cohort was primarily non-Hispanic White, likely owing to differences found between White vs. non-Whites but not the other racial and ethnic groupings. We used a neighborhood-level proxy for individual socioeconomic status and did not have access to more granular measures of adverse social determinants of health that may underly the observed disparities. Of note, the cohort had a high mortality rate, particularly among those who did not receive transplant. Mortality is a biased indicator since patients who were assessed but not transplanted may have died before their transplant whereas the data selection of an initial transplant prevented this competing risk. This was a single-center study. While we expect that similar disparities exist across centers, multi-institutional studies are needed to support our results.\u003c/p\u003e \u003cp\u003eThis study had several strengths. Foremost, our dataset uniquely provided information on patients who did not proceed with HCT. Diverse diagnoses and transplant types allowed us to investigate whether disparities existed for a discrete subset of patients. The analysis was performed post- 2012, when haploidentical HCT became widely available at this institution to limit racial and ethnic disparities in eligibility due to lack of available donors. Lastly, this period also avoids the COVID-19 pandemic wherein clinical practices were altered.\u003c/p\u003e \u003cp\u003eThere are important donor, recipient, and caregivers considerations in taking a patient to HCT.\u003csup\u003e11\u003c/sup\u003e Survivors of HCT may be cured of their primary disease but suffer other serious complications, such as infertility, graft-versus-host disease, secondary malignancies, financial toxicity and cognitive impairments.\u003csup\u003e37\u003c/sup\u003e Thus a rigorous eligibility assessment is warranted.\u003c/p\u003e \u003cp\u003eOther rating scales used to determine transplant eligibility such as the HCT-CI, have discrete criteria to determine the severity of comorbidities.\u003csup\u003e38\u003c/sup\u003e For example, a patient with a body mass index (BMI)\u0026thinsp;\u0026gt;\u0026thinsp;35 kg/m\u003csup\u003e2\u003c/sup\u003e receives an additional 1-point on the HCT-CI.\u003csup\u003e38\u003c/sup\u003e This helps ensure uniform evaluation of BMI and provides a target BMI to help patients achieve prior to transplant. Contrastingly, the parameters of psychosocial assessments are more subjective. A survey study of HCT professionals given patient vignettes with psychosocial information found complete lack of unanimity in eligibility determinations.\u003csup\u003e15\u003c/sup\u003e Respondents\u0026rsquo; determinations were found to be primarily based on their perceived severity of the psychosocial issue.\u003csup\u003e15\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eInarguably, psychosocial factors have the potential to affect HCT outcomes. For example, patients with crowded living spaces during an extremely immunocompromised state are more likely to have infectious complications.\u003csup\u003e39\u003c/sup\u003e Patients without financial stability are less likely to have a full-time caregiver who can take leave from work.\u003csup\u003e40\u003c/sup\u003e However, instead of making these conditions prohibitive to care, efforts should be devoted to help remove modifiable barriers.\u003c/p\u003e \u003cp\u003eThe decision to bring a patient to HCT is complex. The rigorous eligibility determination process ensures that patients under consideration for HCT are evaluated by an experienced multi-disciplinary team.\u003csup\u003e12\u003c/sup\u003e In an era of expanding donor pools, indications for transplant, reduced intensity conditioning, and cellular therapy\u003csup\u003e43\u003c/sup\u003e, it is the duty of our HCT centers to ensure these assessments are used to improve outcomes rather than limit access to transplant for vulnerable populations.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eData Availability:\u0026nbsp;\u003c/strong\u003eThe individual-level data underlying this article cannot be shared due for the privacy of those that participated in the study. Summary level data without individual level data are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts of Interest:\u0026nbsp;\u003c/strong\u003eNone\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFinancial Disclosures:\u0026nbsp;\u003c/strong\u003eNone\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eMajhail NS, Omondi NA, Denzen E, Murphy EA, Rizzo JD. Access to hematopoietic cell transplantation in the United States. \u003cem\u003eBiol Blood Marrow Transplant\u003c/em\u003e. 2010;16(8):1070-1075. doi:10.1016/j.bbmt.2009.12.529\u003c/li\u003e\n\u003cli\u003eHong S, Majhail NS. Increasing access to allotransplants in the United States: the impact of race, geography, and socioeconomics. \u003cem\u003eHematology\u003c/em\u003e. 2021;2021(1):275-280. doi:10.1182/hematology.2021000259\u003c/li\u003e\n\u003cli\u003eHamilton BK, Rybicki L, Sekeres M, et al. Racial differences in allogeneic hematopoietic cell transplantation outcomes among African Americans and whites. \u003cem\u003eBone Marrow Transplantation\u003c/em\u003e. 2015/06/01 2015;50(6):834-839. doi:10.1038/bmt.2015.44\u003c/li\u003e\n\u003cli\u003eHong S, Rybicki LA, Corrigan D, Schold JD, Majhail NS. Community Risk Score for Evaluating Health Care Disparities in Hematopoietic Cell Transplantation. \u003cem\u003eBiol Blood Marrow Transplant\u003c/em\u003e. Apr 2018;24(4):877-879. doi:10.1016/j.bbmt.2017.12.800\u003c/li\u003e\n\u003cli\u003eJoshua TV, Rizzo JD, Zhang MJ, et al. Access to hematopoietic stem cell transplantation: effect of race and sex. \u003cem\u003eCancer\u003c/em\u003e. Jul 15 2010;116(14):3469-76. doi:10.1002/cncr.25297\u003c/li\u003e\n\u003cli\u003eFiala MA, Wildes TM. Racial disparities in treatment use for multiple myeloma. \u003cem\u003eCancer\u003c/em\u003e. May 1 2017;123(9):1590-1596. doi:10.1002/cncr.30526\u003c/li\u003e\n\u003cli\u003eAilawadhi S, Parikh K, Abouzaid S, et al. Racial disparities in treatment patterns and outcomes among patients with multiple myeloma: a SEER-Medicare analysis. \u003cem\u003eBlood Advances\u003c/em\u003e. 2019;3(20):2986-2994. doi:10.1182/bloodadvances.2019000308\u003c/li\u003e\n\u003cli\u003eWinestone LE, Li Q, Muffly LS, et al. Disparities in the Use of Allogeneic Hematopoietic Stem Cell Transplant Among Children, Adolescents, and Young Adults with Acute Leukemia in California. \u003cem\u003eBlood\u003c/em\u003e. 2020;136(Supplement 1):4-5. doi:10.1182/blood-2020-142240\u003c/li\u003e\n\u003cli\u003ePidala J, Craig BM, Lee SJ, Majhail N, Quinn G, Anasetti C. Practice variation in physician referral for allogeneic hematopoietic cell transplantation. \u003cem\u003eBone Marrow Transplant\u003c/em\u003e. Jan 2013;48(1):63-7. doi:10.1038/bmt.2012.95\u003c/li\u003e\n\u003cli\u003eMitchell JM, Conklin EA. Factors affecting receipt of expensive cancer treatments and mortality: evidence from stem cell transplantation for leukemia and lymphoma. \u003cem\u003eHealth Serv Res\u003c/em\u003e. Feb 2015;50(1):197-216. doi:10.1111/1475-6773.12208\u003c/li\u003e\n\u003cli\u003eKanate AS, Perales MA, Hamadani M. Eligibility Criteria for Patients Undergoing Allogeneic Hematopoietic Cell Transplantation. \u003cem\u003eJ Natl Compr Canc Netw\u003c/em\u003e. May 2020;18(5):635-643. doi:10.6004/jnccn.2020.7559\u003c/li\u003e\n\u003cli\u003eScott BL, Sandmaier BM. The Evaluation and Counseling of Candidates for Hematopoietic Cell Transplantation. \u003cem\u003eThomas\u0026rsquo; Hematopoietic Cell Transplantation\u003c/em\u003e. 2015:349-365.\u003c/li\u003e\n\u003cli\u003eMcQuellon RP, Duckworth KE. Psychosocial Issues in Hematopoietic Cell Transplantation. \u003cem\u003eThomas\u0026rsquo; Hematopoietic Cell Transplantation\u003c/em\u003e. 2015:384-393.\u003c/li\u003e\n\u003cli\u003eSnyder DS. 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The PACT: A rating scale for the study of clinical decision-making in psychosocial screening of organ transplant candidates. \u003cem\u003eClinical Transplantation\u003c/em\u003e. 1989;3:164-169. \u003c/li\u003e\n\u003cli\u003eHitschfeld MJ, Schneekloth TD, Kennedy CC, et al. The Psychosocial Assessment of Candidates for Transplantation: A Cohort Study of its Association With Survival Among Lung Transplant Recipients. \u003cem\u003ePsychosomatics\u003c/em\u003e. 2016/09/01/ 2016;57(5):489-497. doi:https://doi.org/10.1016/j.psym.2016.05.003\u003c/li\u003e\n\u003cli\u003eHong S, Rybicki L, Corrigan D, et al. Psychosocial Assessment of Candidates for Transplant (PACT) as a tool for psychological and social evaluation of allogeneic hematopoietic cell transplantation recipients. \u003cem\u003eBone Marrow Transplant\u003c/em\u003e. Sep 2019;54(9):1443-1452. doi:10.1038/s41409-019-0455-y\u003c/li\u003e\n\u003cli\u003eHarashima S, Yoneda R, Horie T, et al. Psychosocial Assessment of Candidates for Transplantation scale (PACT) and survival after allogeneic hematopoietic stem cell transplantation. \u003cem\u003eBone Marrow Transplant\u003c/em\u003e. Jul 2019;54(7):1013-1021. doi:10.1038/s41409-018-0371-6\u003c/li\u003e\n\u003cli\u003eSolh MM, Speckhart D, Solomon SR, et al. The Transplant Evaluation Rating Scale predicts overall survival after allogeneic hematopoietic stem cell transplantation. \u003cem\u003eBlood Advances\u003c/em\u003e. 2020;4(19):4812-4821. doi:10.1182/bloodadvances.2020002204\u003c/li\u003e\n\u003cli\u003eFoster LW, McLellan L, Rybicki L, Dabney J, Visnosky M, Bolwell B. Utility of the psychosocial assessment of candidates for transplantation (PACT) scale in allogeneic BMT. \u003cem\u003eBone Marrow Transplantation\u003c/em\u003e. 2009/09/01 2009;44(6):375-380. doi:10.1038/bmt.2009.37\u003c/li\u003e\n\u003cli\u003eBroers S, Hengeveld MW, Kaptein AA, Le Cessie S, van de Loo F, de Vries T. Are pretransplant psychological variables related to survival after bone marrow transplantation? A prospective study of 123 consecutive patients. \u003cem\u003eJ Psychosom Res\u003c/em\u003e. Oct 1998;45(4):341-51. doi:10.1016/s0022-3999(98)00003-8\u003c/li\u003e\n\u003cli\u003eCooper RS, Nadkarni GN, Ogedegbe G. Race, Ancestry, and Reporting in Medical Journals. \u003cem\u003eJama\u003c/em\u003e. Oct 16 2018;320(15):1531-1532. doi:10.1001/jama.2018.10960\u003c/li\u003e\n\u003cli\u003eFlanagin A, Frey T, Christiansen SL. Updated Guidance on the Reporting of Race and Ethnicity in Medical and Science Journals. \u003cem\u003eJama\u003c/em\u003e. Aug 17 2021;326(7):621-627. doi:10.1001/jama.2021.13304\u003c/li\u003e\n\u003cli\u003eIntroduction to the NIS. Healthcare Cost and Utilization Project (HCUP). April 2021. Agency for Healthcare Research and Quality, Rockville, MD. www.hcup-us.ahrq.gov/db/nation/nis/NIS_Introduction_2018.jsp Last modified 4/5/21. Last accessed 11/21/2023. \u003c/li\u003e\n\u003cli\u003eKind AJH, Buckingham WR. Making Neighborhood-Disadvantage Metrics Accessible - The Neighborhood Atlas. \u003cem\u003eN Engl J Med\u003c/em\u003e. Jun 28 2018;378(26):2456-2458. doi:10.1056/NEJMp1802313\u003c/li\u003e\n\u003cli\u003eClay A, Peoples B, Zhang Y, et al. Population-Based Analysis of Hematologic Malignancy Referrals to a Comprehensive Cancer Center, Referrals for Blood and Marrow Transplantation, and Participation in Clinical Trial, Survey, and Biospecimen Research by Race. \u003cem\u003eBiol Blood Marrow Transplant\u003c/em\u003e. Aug 2015;21(8):1488-94. doi:10.1016/j.bbmt.2015.04.017\u003c/li\u003e\n\u003cli\u003eCosta LJ, Huang JX, Hari PN. Disparities in utilization of autologous hematopoietic cell transplantation for treatment of multiple myeloma. \u003cem\u003eBiol Blood Marrow Transplant\u003c/em\u003e. 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Oct 15 2005;106(8):2912-9. doi:10.1182/blood-2005-05-2004\u003c/li\u003e\n\u003cli\u003eWHO Housing and Health Guidelines. Geneva: World Health Organization; 2018. 3, Household crowding. Available from: https://www.ncbi.nlm.nih.gov/books/NBK535289/. \u003c/li\u003e\n\u003cli\u003eApplebaum AJ, Bevans M, Son T, et al. A scoping review of caregiver burden during allogeneic HSCT: lessons learned and future directions. \u003cem\u003eBone Marrow Transplant\u003c/em\u003e. Nov 2016;51(11):1416-1422. doi:10.1038/bmt.2016.164\u003c/li\u003e\n\u003cli\u003eGragert L, Eapen M, Williams E, et al. HLA match likelihoods for hematopoietic stem-cell grafts in the U.S. registry. \u003cem\u003eN Engl J Med\u003c/em\u003e. Jul 24 2014;371(4):339-48. doi:10.1056/NEJMsa1311707\u003c/li\u003e\n\u003cli\u003eLewandowski AN, Skillings JL. Who gets a lung transplant? Assessing the psychosocial decision-making process for transplant listing. \u003cem\u003eGlob Cardiol Sci Pract\u003c/em\u003e. Sep 30 2016;2016(3):e201626. doi:10.21542/gcsp.2016.26\u003c/li\u003e\n\u003cli\u003eD\u0026apos;Souza A, Fretham C, Lee SJ, et al. Current Use of and Trends in Hematopoietic Cell Transplantation in the United States. \u003cem\u003eBiol Blood Marrow Transplant\u003c/em\u003e. Aug 2020;26(8):e177-e182. doi:10.1016/j.bbmt.2020.04.013\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1. Distribution of patients assessed for transplant by receipt of HCT\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"666\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.426426426426428%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eFactor\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.02102102102102%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal\u003cbr\u003e\u0026nbsp;(N=1,102)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.37237237237237%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eDid not receive HCT\u003cbr\u003e\u0026nbsp;(N=446)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.62162162162162%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eReceived HCT\u003cbr\u003e\u0026nbsp;(N=656)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.426426426426428%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.02102102102102%\"\u003e\n \u003cp\u003e60.6 [50.5, 67.0]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.37237237237237%\"\u003e\n \u003cp\u003e62.7 [53.1, 68.8]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.62162162162162%\"\u003e\n \u003cp\u003e59.3 [49.4, 66.1]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026lt;0.001\u003csup\u003ea\u003c/sup\u003e\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.426426426426428%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSex\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.02102102102102%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.37237237237237%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.62162162162162%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\"\u003e\n \u003cp\u003e0.26\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.426426426426428%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Female\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.02102102102102%\"\u003e\n \u003cp\u003e449 (40.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.37237237237237%\"\u003e\n \u003cp\u003e172 (38.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.62162162162162%\"\u003e\n \u003cp\u003e277 (42.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.426426426426428%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Male\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.02102102102102%\"\u003e\n \u003cp\u003e650 (59.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.37237237237237%\"\u003e\n \u003cp\u003e271 (61.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.62162162162162%\"\u003e\n \u003cp\u003e379 (57.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.426426426426428%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eRace\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.02102102102102%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.37237237237237%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.62162162162162%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.426426426426428%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Black\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.02102102102102%\"\u003e\n \u003cp\u003e97 (9.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.37237237237237%\"\u003e\n \u003cp\u003e44 (10.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.62162162162162%\"\u003e\n \u003cp\u003e53 (8.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\" rowspan=\"2\"\u003e\n \u003cp\u003e0.20\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.89983579638752%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Non-Black, known\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.988505747126435%\"\u003e\n \u003cp\u003e981 (91.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.46633825944171%\"\u003e\n \u003cp\u003e381 (81.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.645320197044335%\"\u003e\n \u003cp\u003e600 (91.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.426426426426428%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; White\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.02102102102102%\"\u003e\n \u003cp\u003e943 (87.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.37237237237237%\"\u003e\n \u003cp\u003e365 (85.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.62162162162162%\"\u003e\n \u003cp\u003e578 (88.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\" rowspan=\"2\"\u003e\n \u003cp\u003e0.20\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.89983579638752%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Non-White\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.988505747126435%\"\u003e\n \u003cp\u003e135 (12.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.46633825944171%\"\u003e\n \u003cp\u003e60 (14.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.645320197044335%\"\u003e\n \u003cp\u003e75 (11.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.426426426426428%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eEthnicity\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.02102102102102%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.37237237237237%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.62162162162162%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\"\u003e\n \u003cp\u003e0.24\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.426426426426428%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Hispanic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.02102102102102%\"\u003e\n \u003cp\u003e25 (2.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.37237237237237%\"\u003e\n \u003cp\u003e7 (1.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.62162162162162%\"\u003e\n \u003cp\u003e18 (2.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.426426426426428%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Non-Hispanic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.02102102102102%\"\u003e\n \u003cp\u003e1,049 (97.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.37237237237237%\"\u003e\n \u003cp\u003e416 (98.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.62162162162162%\"\u003e\n \u003cp\u003e633 (97.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.426426426426428%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePayor\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.02102102102102%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.37237237237237%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.62162162162162%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026lt;0.001\u003csup\u003eb\u003c/sup\u003e\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.426426426426428%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Medicaid\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.02102102102102%\"\u003e\n \u003cp\u003e42 (4.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.37237237237237%\"\u003e\n \u003cp\u003e13 (3.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.62162162162162%\"\u003e\n \u003cp\u003e29 (4.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.426426426426428%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Medicare\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.02102102102102%\"\u003e\n \u003cp\u003e322 (32.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.37237237237237%\"\u003e\n \u003cp\u003e164 (43.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.62162162162162%\"\u003e\n \u003cp\u003e158 (25.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.426426426426428%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Other\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.02102102102102%\"\u003e\n \u003cp\u003e30 (3.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.37237237237237%\"\u003e\n \u003cp\u003e7 (1.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.62162162162162%\"\u003e\n \u003cp\u003e23 (3.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.426426426426428%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Private\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.02102102102102%\"\u003e\n \u003cp\u003e595 (60.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.37237237237237%\"\u003e\n \u003cp\u003e191 (50.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.62162162162162%\"\u003e\n \u003cp\u003e404 (65.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.426426426426428%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePatient Deceased\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.02102102102102%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.37237237237237%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.62162162162162%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026lt;0.001\u003csup\u003eb\u003c/sup\u003e\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.426426426426428%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; No\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.02102102102102%\"\u003e\n \u003cp\u003e623 (56.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.37237237237237%\"\u003e\n \u003cp\u003e209 (47.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.62162162162162%\"\u003e\n \u003cp\u003e414 (63.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.426426426426428%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Yes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.02102102102102%\"\u003e\n \u003cp\u003e473 (43.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.37237237237237%\"\u003e\n \u003cp\u003e232 (52.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.62162162162162%\"\u003e\n \u003cp\u003e241 (36.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.426426426426428%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eZip code median income quartile (Q)\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.02102102102102%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.37237237237237%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.62162162162162%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e0.02\u003csup\u003ea\u003c/sup\u003e\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.426426426426428%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Q1 ($1-45,999)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.02102102102102%\"\u003e\n \u003cp\u003e233 (22.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.37237237237237%\"\u003e\n \u003cp\u003e113 (26.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.62162162162162%\"\u003e\n \u003cp\u003e120 (19.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.426426426426428%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Q2 ($46,000-58,999)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.02102102102102%\"\u003e\n \u003cp\u003e330 (31.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.37237237237237%\"\u003e\n \u003cp\u003e128 (29.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.62162162162162%\"\u003e\n \u003cp\u003e202 (32.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.426426426426428%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Q3 ($59,000-78,999)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.02102102102102%\"\u003e\n \u003cp\u003e335 (31.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.37237237237237%\"\u003e\n \u003cp\u003e133 (30.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.62162162162162%\"\u003e\n \u003cp\u003e202 (32.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.426426426426428%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Q4 ($79,000+)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.02102102102102%\"\u003e\n \u003cp\u003e157 (14.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.37237237237237%\"\u003e\n \u003cp\u003e56 (13.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.62162162162162%\"\u003e\n \u003cp\u003e101 (16.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"5\" valign=\"top\"\u003e\n \u003cp\u003eStatistics\u0026nbsp;presented\u0026nbsp;as Median\u0026nbsp;[P25,\u0026nbsp;P75],\u0026nbsp;N\u0026nbsp;(column\u0026nbsp;%).\u003cbr\u003e\u0026nbsp;p-values: a=Wilcoxon Rank Sum test, b=Pearson\u0026apos;s chi-square test\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2. Median times from consultation to initial transplant for those who received HCT\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.58426966292135%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.099518459069021%\" valign=\"top\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.903691813804173%\" valign=\"top\"\u003e\n \u003cp\u003eMedian Time (days), 95% confidence interval (CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.335473515248797%\" valign=\"top\"\u003e\n \u003cp\u003e25\u003csup\u003eth\u003c/sup\u003e percentile (days), 95% CI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\" valign=\"top\"\u003e\n \u003cp\u003eLog rank test p-value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.520064205457464%\" valign=\"top\"\u003e\n \u003cp\u003eWilcoxon rank sum p-value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.58426966292135%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eOverall\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.099518459069021%\" valign=\"top\"\u003e\n \u003cp\u003e656\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.903691813804173%\" valign=\"top\"\u003e\n \u003cp\u003e110 (106, 114)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.335473515248797%\" valign=\"top\"\u003e\n \u003cp\u003e84 (79, 86)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.520064205457464%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;--\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.58426966292135%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSex\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.099518459069021%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.903691813804173%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.335473515248797%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\"\u003e\n \u003cp\u003e0.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.520064205457464%\"\u003e\n \u003cp\u003e0.42\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.58426966292135%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Female\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.099518459069021%\" valign=\"top\"\u003e\n \u003cp\u003e277\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.903691813804173%\" valign=\"top\"\u003e\n \u003cp\u003e109 (101, 113) \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.335473515248797%\" valign=\"top\"\u003e\n \u003cp\u003e84 (78, 87)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.520064205457464%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.58426966292135%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Male\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.099518459069021%\" valign=\"top\"\u003e\n \u003cp\u003e378\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.903691813804173%\" valign=\"top\"\u003e\n \u003cp\u003e111 (106, 120)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.335473515248797%\" valign=\"top\"\u003e\n \u003cp\u003e83 (77, 89)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.520064205457464%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.58426966292135%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eRace\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.099518459069021%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.903691813804173%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.335473515248797%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.520064205457464%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.58426966292135%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Black\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.099518459069021%\" valign=\"top\"\u003e\n \u003cp\u003e53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.903691813804173%\" valign=\"top\"\u003e\n \u003cp\u003e109 (94, 155)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.335473515248797%\" valign=\"top\"\u003e\n \u003cp\u003e85 (72, 94)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\" rowspan=\"2\"\u003e\n \u003cp\u003e0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.520064205457464%\" rowspan=\"2\"\u003e\n \u003cp\u003e0.39\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.91754756871036%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Non-Black\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.033826638477802%\" valign=\"top\"\u003e\n \u003cp\u003e599\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.21564482029598%\" valign=\"top\"\u003e\n \u003cp\u003e110 (106, 114)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.832980972515855%\" valign=\"top\"\u003e\n \u003cp\u003e84 (79, 87)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.58426966292135%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;White\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.099518459069021%\" valign=\"top\"\u003e\n \u003cp\u003e577\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.903691813804173%\" valign=\"top\"\u003e\n \u003cp\u003e109 (105, 113)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.335473515248797%\" valign=\"top\"\u003e\n \u003cp\u003e82 (79, 86)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e0.02\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.520064205457464%\" rowspan=\"2\"\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.91754756871036%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Non-White\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.033826638477802%\" valign=\"top\"\u003e\n \u003cp\u003e75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.21564482029598%\" valign=\"top\"\u003e\n \u003cp\u003e126 (100, 142)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.832980972515855%\" valign=\"top\"\u003e\n \u003cp\u003e88 (76, 97)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.58426966292135%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eEthnicity\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.099518459069021%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.903691813804173%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.335473515248797%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.520064205457464%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.58426966292135%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Hispanic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.099518459069021%\" valign=\"top\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.903691813804173%\" valign=\"top\"\u003e\n \u003cp\u003e141.5 (87, 199)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.335473515248797%\" valign=\"top\"\u003e\n \u003cp\u003e87 (49, 121)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\" rowspan=\"2\"\u003e\n \u003cp\u003e0.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.520064205457464%\" rowspan=\"2\"\u003e\n \u003cp\u003e0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.91754756871036%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Non-Hispanic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.033826638477802%\" valign=\"top\"\u003e\n \u003cp\u003e632\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.21564482029598%\" valign=\"top\"\u003e\n \u003cp\u003e110 (106, 114)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.832980972515855%\" valign=\"top\"\u003e\n \u003cp\u003e84 (79, 86)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.58426966292135%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePayor\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.099518459069021%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.903691813804173%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.335473515248797%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.520064205457464%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.58426966292135%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Medicaid\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.099518459069021%\" valign=\"top\"\u003e\n \u003cp\u003e29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.903691813804173%\" valign=\"top\"\u003e\n \u003cp\u003e102 (87, 138)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.335473515248797%\" valign=\"top\"\u003e\n \u003cp\u003e84 (75, 94)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\" rowspan=\"4\"\u003e\n \u003cp\u003e0.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.520064205457464%\" rowspan=\"4\"\u003e\n \u003cp\u003e0.44\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.91754756871036%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Medicare\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.033826638477802%\" valign=\"top\"\u003e\n \u003cp\u003e158\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.21564482029598%\" valign=\"top\"\u003e\n \u003cp\u003e114 (106, 121)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.832980972515855%\" valign=\"top\"\u003e\n \u003cp\u003e91 (82, 97)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.91754756871036%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Other\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.033826638477802%\" valign=\"top\"\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.21564482029598%\" valign=\"top\"\u003e\n \u003cp\u003e119 (88, 183)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.832980972515855%\" valign=\"top\"\u003e\n \u003cp\u003e87 (56, 99)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.91754756871036%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Private\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.033826638477802%\" valign=\"top\"\u003e\n \u003cp\u003e403\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.21564482029598%\" valign=\"top\"\u003e\n \u003cp\u003e109 (105, 114)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.832980972515855%\" valign=\"top\"\u003e\n \u003cp\u003e81 (77, 85)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.58426966292135%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eDiagnosis\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.099518459069021%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.903691813804173%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.335473515248797%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.520064205457464%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.58426966292135%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Leukemia/Lymphoma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.099518459069021%\" valign=\"top\"\u003e\n \u003cp\u003e345\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.903691813804173%\" valign=\"top\"\u003e\n \u003cp\u003e110 (102, 117)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.335473515248797%\" valign=\"top\"\u003e\n \u003cp\u003e83 (78, 87)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\" rowspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e0.02\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.520064205457464%\" rowspan=\"3\"\u003e\n \u003cp\u003e0.35\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.91754756871036%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; MDS/MPN/Myelofibrosis/ Solid tumor/Other\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.033826638477802%\" valign=\"top\"\u003e\n \u003cp\u003e90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.21564482029598%\" valign=\"top\"\u003e\n \u003cp\u003e121.5 (106, 139)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.832980972515855%\" valign=\"top\"\u003e\n \u003cp\u003e82 (70, 95)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.91754756871036%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Myeloma/amyloidosis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.033826638477802%\" valign=\"top\"\u003e\n \u003cp\u003e220\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.21564482029598%\" valign=\"top\"\u003e\n \u003cp\u003e108.5 (105, 113)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.832980972515855%\" valign=\"top\"\u003e\n \u003cp\u003e85 (77, 91)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.58426966292135%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHCT type\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.099518459069021%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.903691813804173%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.335473515248797%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.520064205457464%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.58426966292135%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Allogeneic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.099518459069021%\" valign=\"top\"\u003e\n \u003cp\u003e255\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.903691813804173%\" valign=\"top\"\u003e\n \u003cp\u003e104 (97, 112)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.335473515248797%\" valign=\"top\"\u003e\n \u003cp\u003e79 (76, 84)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\" rowspan=\"3\"\u003e\n \u003cp\u003e0.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.520064205457464%\" rowspan=\"3\"\u003e\n \u003cp\u003e0.56\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.91754756871036%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Autologous\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.033826638477802%\" valign=\"top\"\u003e\n \u003cp\u003e384\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.21564482029598%\" valign=\"top\"\u003e\n \u003cp\u003e113 (107, 118)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.832980972515855%\" valign=\"top\"\u003e\n \u003cp\u003e86.5 (81, 91)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.91754756871036%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Other\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.033826638477802%\" valign=\"top\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.21564482029598%\" valign=\"top\"\u003e\n \u003cp\u003e136 (55, 249)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.832980972515855%\" valign=\"top\"\u003e\n \u003cp\u003e61.5 (27, 125)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.58426966292135%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eZip code median income quartile\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.099518459069021%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.903691813804173%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.335473515248797%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.520064205457464%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.58426966292135%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Q1 ( $1-45,999)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.099518459069021%\" valign=\"top\"\u003e\n \u003cp\u003e120\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.903691813804173%\" valign=\"top\"\u003e\n \u003cp\u003e111.5 (99, 141)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.335473515248797%\" valign=\"top\"\u003e\n \u003cp\u003e84.5 (77, 94)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.556982343499197%\" rowspan=\"4\"\u003e\n \u003cp\u003e0.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.520064205457464%\" rowspan=\"4\"\u003e\n \u003cp\u003e0.91\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.91754756871036%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Q2 ($46,000-58,999)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.033826638477802%\" valign=\"top\"\u003e\n \u003cp\u003e202\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.21564482029598%\" valign=\"top\"\u003e\n \u003cp\u003e113 (106, 120)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.832980972515855%\" valign=\"top\"\u003e\n \u003cp\u003e88 (83, 92)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.91754756871036%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Q3 ($59,000-78,999)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.033826638477802%\" valign=\"top\"\u003e\n \u003cp\u003e201\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.21564482029598%\" valign=\"top\"\u003e\n \u003cp\u003e112 (104, 120)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.832980972515855%\" valign=\"top\"\u003e\n \u003cp\u003e85 (79, 91)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.91754756871036%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Q4 ($79,000+)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.033826638477802%\" valign=\"top\"\u003e\n \u003cp\u003e101\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.21564482029598%\" valign=\"top\"\u003e\n \u003cp\u003e107 (98, 122)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.832980972515855%\" valign=\"top\"\u003e\n \u003cp\u003e82 (76, 89)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3. Characteristics of patients who received HCT by non-White vs. White race\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"666\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.42942942942943%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eFactor\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.01801801801802%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal\u003cbr\u003e\u0026nbsp;(N=653)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.37237237237237%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eNon-White\u003cbr\u003e\u0026nbsp;(N=75)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.62162162162162%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eWhite\u003cbr\u003e\u0026nbsp;(N=578)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.42942942942943%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHCT type\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.01801801801802%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.37237237237237%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.62162162162162%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\"\u003e\n \u003cp\u003e0.65\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.42942942942943%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Allogenic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.01801801801802%\"\u003e\n \u003cp\u003e254 (38.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.37237237237237%\"\u003e\n \u003cp\u003e27 (36.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.62162162162162%\"\u003e\n \u003cp\u003e227 (39.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.42942942942943%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Autologous\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.01801801801802%\"\u003e\n \u003cp\u003e383 (58.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.37237237237237%\"\u003e\n \u003cp\u003e47 (62.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.62162162162162%\"\u003e\n \u003cp\u003e336 (58.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.42942942942943%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Other\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.01801801801802%\"\u003e\n \u003cp\u003e16 (2.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.37237237237237%\"\u003e\n \u003cp\u003e1 (1.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.62162162162162%\"\u003e\n \u003cp\u003e15 (2.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.42942942942943%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eDiagnosis\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.01801801801802%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.37237237237237%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.62162162162162%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026lt;0.01\u003csup\u003ec\u003c/sup\u003e\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.42942942942943%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Leukemia/Lymphoma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.01801801801802%\"\u003e\n \u003cp\u003e344 (52.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.37237237237237%\"\u003e\n \u003cp\u003e27 (36.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.62162162162162%\"\u003e\n \u003cp\u003e317 (54.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.42942942942943%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Myeloma/Amyloidosis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.01801801801802%\"\u003e\n \u003cp\u003e219 (33.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.37237237237237%\"\u003e\n \u003cp\u003e36 (48.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.62162162162162%\"\u003e\n \u003cp\u003e183 (31.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.42942942942943%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; MDS/MPN/Myelofibrosis/ Solid tumor/Other\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.01801801801802%\"\u003e\n \u003cp\u003e90 (13.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.37237237237237%\"\u003e\n \u003cp\u003e12 (16.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.62162162162162%\"\u003e\n \u003cp\u003e78 (13.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.42942942942943%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eKarnofsky scale\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.01801801801802%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.37237237237237%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.62162162162162%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\"\u003e\n \u003cp\u003e0.29\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.42942942942943%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Karnofsky\u0026gt;80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.01801801801802%\"\u003e\n \u003cp\u003e475 (73.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.37237237237237%\"\u003e\n \u003cp\u003e50 (68.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.62162162162162%\"\u003e\n \u003cp\u003e425 (74.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.42942942942943%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Karnofsky \u0026lt;=80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.01801801801802%\"\u003e\n \u003cp\u003e170 (26.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.37237237237237%\"\u003e\n \u003cp\u003e23 (31.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.62162162162162%\"\u003e\n \u003cp\u003e147 (25.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"29.42942942942943%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHCT-CI scores\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.01801801801802%\"\u003e\n \u003cp\u003e3.0 [1.0, 4.0]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.37237237237237%\"\u003e\n \u003cp\u003e3.0 [1.0, 4.0]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.62162162162162%\"\u003e\n \u003cp\u003e3.0 [1.0, 4.0]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.558558558558559%\"\u003e\n \u003cp\u003e0.17\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"5\" valign=\"top\"\u003e\n \u003cp\u003eStatistics\u0026nbsp;presented\u0026nbsp;as\u0026nbsp;N\u0026nbsp;(column\u0026nbsp;%), Median\u0026nbsp;[P25,\u0026nbsp;P75]\u003cbr\u003e\u0026nbsp;p-values: b=Wilcoxon Rank Sum test, c=Pearson\u0026apos;s chi-square test.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bone-marrow-transplantation","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"bmt","sideBox":"Learn more about [Bone Marrow Transplantation](http://www.nature.com/bmt/)","snPcode":"41409","submissionUrl":"https://mts-bmt.nature.com/cgi-bin/main.plex","title":"Bone Marrow Transplantation","twitterHandle":"@bmtjournal","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"hematopoietic cell transplant, disparities, access, socioeconomic, race","lastPublishedDoi":"10.21203/rs.3.rs-3845742/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3845742/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eRace, ethnicity, and socioeconomic status impact access to hematopoietic cell transplant (HCT). Whether differences in accessibility occur within HCT centers remains unknown. \u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eWe performed a single-center retrospective review of 1,102 patients who underwent HCT consultation. We examined the association between race (Black vs. non-Black and White vs. non-White), ethnicity (Hispanic vs. non-Hispanic) and socioeconomic status (defined by zip code median household income quartiles) with receipt of HCT, time to HCT, and Psychosocial Assessment of Candidates for Transplantation (PACT) scores.\u003c/p\u003e\n\u003cp\u003eRace and ethnicity were not associated with receipt of HCT (p\u0026gt;0.20 for all comparisons). Those living in higher income quartiles and those with private insurance were more likely to receive HCT (p=0.02 and p\u0026lt;0.001, respectively). \u0026nbsp;Among HCT recipients, patients of White race had a shorter time to transplant than those of non-White race (p=0.0175). There was a strong association between lower PACT scores and poorer income quartiles (p\u0026lt;0.001).\u003c/p\u003e\n\u003cp\u003eSocioeconomic status impacts receipt of HCT and PACT scores among patients evaluated at an HCT center. Race and ethnicity did not affect receipt of HCT. However, non-White patients waited longer from consultation to transplant. Further investigation as to whether the psychosocial eligibility evaluation impedes access to HCT in vulnerable populations is warranted.\u003c/p\u003e","manuscriptTitle":"Disparities in Access to Hematopoietic Cell Transplant Persist at a Transplant Center","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-01-12 17:45:21","doi":"10.21203/rs.3.rs-3845742/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"revise","date":"2024-02-12T12:31:45+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"This content is not available.","date":"2024-02-07T14:54:33+00:00","index":2,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2024-01-25T16:19:48+00:00","index":2,"fulltext":"This content is not available."},{"type":"editorInvitedReview","content":"This content is not available.","date":"2024-01-25T06:26:24+00:00","index":1,"fulltext":"This content is not available."},{"type":"reviewerAgreed","content":"This content is not available.","date":"2024-01-25T00:32:46+00:00","index":1,"fulltext":"This content is not available."},{"type":"reviewersInvited","content":"","date":"2024-01-10T14:56:12+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-01-09T11:17:39+00:00","index":"","fulltext":""},{"type":"submitted","content":"Bone Marrow Transplantation","date":"2024-01-08T15:18:18+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-01-08T15:18:18+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bone-marrow-transplantation","isNatureJournal":false,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"bmt","sideBox":"Learn more about [Bone Marrow Transplantation](http://www.nature.com/bmt/)","snPcode":"41409","submissionUrl":"https://mts-bmt.nature.com/cgi-bin/main.plex","title":"Bone Marrow Transplantation","twitterHandle":"@bmtjournal","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"08ecc9dd-4fda-451a-95e4-505d83b5e345","owner":[],"postedDate":"January 12th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":28064013,"name":"Health sciences/Health care/Health services"},{"id":28064014,"name":"Health sciences/Health care/Public health"}],"tags":[],"updatedAt":"2024-06-14T07:07:32+00:00","versionOfRecord":{"articleIdentity":"rs-3845742","link":"https://doi.org/10.1038/s41409-024-02327-x","journal":{"identity":"bone-marrow-transplantation","isVorOnly":false,"title":"Bone Marrow Transplantation"},"publishedOn":"2024-06-13 04:00:00","publishedOnDateReadable":"June 13th, 2024"},"versionCreatedAt":"2024-01-12 17:45:21","video":"","vorDoi":"10.1038/s41409-024-02327-x","vorDoiUrl":"https://doi.org/10.1038/s41409-024-02327-x","workflowStages":[]},"version":"v1","identity":"rs-3845742","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3845742","identity":"rs-3845742","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}