Shorter survival has been associated with low socioeconomic status (SES) among elderly non-Hodgkin's lymphoma (NHL) patients; however it remains unknown whether the same relationship holds for younger patients. We explored the California Cancer Registry (CCR), to investigate this relationship in adolescent and young adult (AYA) NHL patients diagnosed from 1996 to 2005. A case-only survival analysis was conducted to examine demographic and clinical variables hypothesized to be related to survival. Included in the final analysis were 3,489 incident NHL cases. In the multivariate analyses, all-cause mortality (ACM) was higher in individuals who had later stage at diagnosis (
Lymphomas are among the most common cancers [
Recent attention has been given to investigating socioeconomic disparities in survival among cancer patient populations with diverse ethno-racial or socioeconomic backgrounds or with differential access to healthcare [
This study sought to examine whether socioeconomic factors beyond race/ethnicity and treatment differences influence survival in AYAs with NHL. The following research questions were investigated: Does neighborhood-level socioeconomic status (nSES) at diagnosis predict all-cause and lymphoma-specific mortality in AYAs diagnosed with NHL, after adjustment for race/ethnicity, gender, insurance status at diagnosis, marital status, stage at diagnosis, nodality, and first-course treatment? Is there a linear trend between decreasing nSES and shorter survival? Is the relationship between nSES and mortality modified by race/ethnicity?
A retrospective case-only analysis was performed of NHL cases diagnosed in California between 1996 and 2005 among individuals aged 15 to 39 years old using the California Cancer Registry (CCR) (
Seventy-eight cases were identified only through death certificate, obituary, or the Social Security Death Index, and an additional two were lost to follow-up. The remaining cases were identified through hospitals, inpatient/outpatient centers, oncology treatment centers, laboratories, or private practitioners.
Recorded variables in the CCR include age at diagnosis, demographic information, histology, first-course therapy (radiation, chemotherapy, and surgery status), neighborhood SES (nSES), vital status, treatment hospital type (pediatric or otherwise), and insurance status. For this analysis, health insurance status at diagnosis was categorized in one of the four following ways: (1) private insurance (including managed care, military and Veterans Administration, or other private); (2) government-funded insurance (including Medicare, Medicaid, or other state assistance programs); (3) no insurance; or (4) unknown insurance status. Individuals with government-provided insurance were not grouped with those who had private insurance because preliminary Kaplan-Meier analyses indicated that individuals with government-provided insurance had shorter survival than individuals without health insurance at diagnosis, corroborating previously published reports [
Cause of death was recorded according to the ICD criteria in effect at the time of death [
Demographic characteristics and clinical parameters were analyzed using Pearson’s
A total of 2,432 males and 1,330 females in California aged 15–39 at diagnosis with NHL between 1996 and 2005 comprised the study group. Table
Demographic and clinical characteristics of adolescents and young adults diagnosed with non-Hodgkin's
Characteristic | Non-Hispanic White | Non-Hispanic Black | Hispanic/ | Asian/Pacific Islander | Other | Total | |
---|---|---|---|---|---|---|---|
Age at Diagnosis | |||||||
15–29 | 613 (31.8) | 108 (38.4) | 461 (40.8) | 168 (44.2) | 10 (25) | 1360 (36.2) | |
30–39 | 1317 (68.2) | 173 (61.6) | 670 (59.2) | 212 (55.8) | 30 (75) | 2402 (63.9) | |
Mean Age (SD) | 31.5 (6.5) | 30.5 (6.7) | 30.2 (6.7) | 29.4 (7.0) | 32.4 (6.4) | 30.8 (6.6) | |
Year of Diagnosis | |||||||
1996–2000 | 1022 (53) | 138 (49.1) | 530 (46.9) | 173 (45.5) | 16 (40) | 1879 (50.0) | .0031 |
2001–2005 | 908 (47) | 143 (50.9) | 601 (53.1) | 207 (54.5) | 24 (60) | 1883 (50.0) | |
Gender | |||||||
Male | 1265 (65.5) | 181 (64.4) | 741 (65.5) | 222 (58.4) | 23 (57.5) | 2432 (64.7) | .078 |
Female | 665 (34.5) | 100 (35.6) | 390 (34.5) | 158 (41.6) | 17 (42.5) | 1330 (35.4) | |
Tumor stage | |||||||
Local | 553 (28.7) | 69 (24.6) | 346 (30.6) | 141 (37.1) | 18 (45) | 1127 (30.0) | |
Regional | 372 (19.3) | 47 (16.7) | 202 (17.9) | 89 (23.4) | 4 (10) | 714 (19.0) | |
Distant | 905 (46.9) | 146 (52) | 526 (46.5) | 132 (34.7) | 10 (25) | 1719 (45.7) | |
Unknown | 100 (5.2) | 19 (6.8) | 57 (5) | 18 (4.7) | 8 (20) | 202 (5.4) | |
Nodality | |||||||
Nodal | 1384 (71.7) | 187 (66.5) | 729 (64.5) | 227 (59.7) | 19 (47.5) | 2546 (67.7) | |
Extranodal | 546 (28.3) | 94 (33.5) | 402 (35.5) | 153 (40.3) | 21 (52.5) | 1216 (32.3) | |
First-course Chemotherapy | |||||||
Yes | 1560 (80.8) | 229 (81.5) | 946 (83.6) | 302 (79.5) | 21 (52.5) | 3058 (81.3) | |
No | 343 (17.8) | 51 (18.1) | 175 (15.5) | 74 (19.5) | 19 (47.5) | 662 (17.6) | |
Unknown | 27 (1.4) | 1 (0.4) | 10 (0.9) | 4 (1.1) | — | 42 (1.1) | |
First-course Radiation | |||||||
Yes | 669 (34.7) | 89 (31.7) | 317 (28) | 159 (41.8) | 11 (27.5) | 1245 (33.1) | |
No | 1261 (65.3) | 192 (68.3) | 814 (72) | 221 (58.2) | 29 (72.5) | 2517 (66.9) | |
nSES | |||||||
Highest | 548 (28.4) | 20 (7.1) | 95 (8.4) | 132 (34.7) | 16 (40) | 811 (21.6) | |
High | 489 (25.3) | 47 (16.7) | 144 (12.7) | 92 (24.2) | 8 (20) | 780 (20.7) | |
Middle | 425 (22) | 64 (22.8) | 201 (17.8) | 71 (18.7) | 10 (25) | 771 (20.5) | |
Low | 302 (15.6) | 76 (27) | 288 (25.5) | 43 (11.3) | 1 (2.5) | 710 (18.9) | |
Lowest | 166 (8.6) | 74 (26.3) | 403 (35.6) | 42 (11.1) | 5 (12.5) | 690 (18.3) | |
Insurance | |||||||
Managed Care or Private Insurance (including Military/Veterans Affairs) | 1376 (71.3) | 156 (55.5) | 539 (47.7) | 283 (74.5) | 27 (67.5) | 2381 (56.2) | |
Medicaid/Medicare/ Government Assistance | 333 (17.3) | 84 (29.9) | 356 (31.5) | 54 (14.2) | 4 (10) | 831 (19.6) | |
Not Insured | 65 (3.4) | 12 (4.3) | 98 (8.7) | 15 (3.9) | 1 (2.5) | 191 (4.5) | |
Unknown | 333 (17.3) | 84 (29.9) | 356 (31.5) | 54 (14.2) | 4 (10) | 831 (19.6) |
Abbreviations: SD: standard deviation; nSES: neighborhood socioeconomic status.
Figure
Racial/ethnic breakdown of frequency of neighborhood-level socioeconomic status (nSES).
During the follow-up period through December 2005, 1,081 deaths occurred among the total 3,489 patients included in this analysis. The majority of deaths were due to lymphoma-related causes (
Table
Multivariate hazard
ACM | LSM | |||
Characteristic | Unadjusted HR (95% CI) | Adjusted HR | Unadjusted HR (95% CI) | Adjusted HR |
Sex | ||||
Male | 1.00 (Ref) | 1.00 (Ref) | 1.00 (Ref) | 1.00 (Ref) |
Female | 0.54 (0.47–0.63)* | 0.65 (0.57–0.75)* | 0.79 (0.66-0.93)* | 0.93 (0.78–1.11) |
Age at Diagnosis | ||||
By year | 1.01 (1.00–1.02)* | 1.02 (1.01–1.03)* | 0.99 (0.98–1.00) | 1.00 (0.99–1.01) |
Race/Ethnicity | ||||
Non-Hispanic White | 1.00 (Ref) | 1.00 (Ref) | 1.00 (Ref) | 1.00 (Ref) |
Non-Hispanic Black | 1.50 (1.20–1.86)* | 1.13 (0.90–1.41) | 1.38 (1.03–1.86)* | 1.11 (0.82–1.51) |
Hispanic/Latino | 1.30 (1.13–1.49)* | 1.07 (0.92–1.25) | 1.27 (1.06–1.53) | 1.08 (0.88–1.32) |
Asian/Pacific Islander | 0.86 (0.68–1.08) | 0.99 (0.78–1.26) | 1.35 (1.04–1.74)* | 1.52 (1.17–1.98)* |
Stage | ||||
Local | 1.00 (Ref)† | 1.00 (Ref)† | 1.00 (Ref)† | 1.00 (Ref)† |
Regional | 1.16 (0.93–1.45) | 1.28 (1.02–1.62)* | 1.85 (1.39–2.47)* | 1.62 (1.21–2.18)* |
Distant | 2.94 (2.50–3.46) | 3.16 (2.63–3.81)* | 3.68 (2.91–4.65)* | 3.14 (2.42–4.06)* |
Nodality | ||||
Nodal | 1.00 (Ref) | 1.00 (Ref) | 1.00 (Ref) | 1.00 (Ref) |
Extranodal | 1.03 (0.90–1.17) | 1.29 (1.11–1.50)* | 0.71 (0.59–0.86)* | 0.99 (0.81–1.22) |
First-course Chemotherapy | ||||
Yes | 1.00 (Ref) | 1.00 (Ref) | 1.00 (Ref) | 1.00 (Ref) |
No | 0.75 (0.62–0.91)* | 1.27 (1.02-1.57)* | 0.24 (0.16–0.36)* | 0.37 (0.24–0.57)* |
First-course Radiation | ||||
Yes | 1.00 (Ref) | 1.00 (Ref) | 1.00 (Ref) | 1.00 (Ref) |
No | 1.31 (1.15–1.50) | 0.94 (0.82–1.09) | 1.43 (1.19–1.71)* | 1.01 (0.83–1.22) |
nSES | ||||
Highest | 1.00 (Ref)† | 1.00 (Ref)† | 1.00 (Ref)† | 1.00 (Ref)† |
High | 1.22 (0.98–1.50) | 1.15 (0.93–1.42) | 1.07 (0.81–1.41) | 1.08 (0.81–1.41) |
Middle | 1.33 (1.08–1.63)* | 1.20 (0.97–1.48) | 1.27 (0.98–1.66) | 1.21 (0.93–1.59) |
Low | 1.67 (1.37–2.05)* | 1.39 (1.12–1.71)* | 1.62 (1.26–2.10)* | 1.49 (1.14–1.96)* |
Lowest | 1.97 (1.62–2.40)* | 1.40 (1.13–1.75)* | 1.70 (1.31–2.20)* | 1.38 (1.04–1.84)* |
Insurance | ||||
None | 1.00 (Ref) | 1.00 (Ref) | 1.00 (Ref) | 1.00 (Ref) |
Managed or Private | 0.62 (0.47–0.82)* | 0.82 (0.62–1.08) | 0.74 (0.52–1.07) | 0.96 (0.66–1.39) |
Government | 1.41 (1.07–1.87)* | 1.32 (1.00–1.75) | 1.24 (0.85–1.81) | 1.16 (0.79–1.70) |
Unknown | 0.87 (0.63–1.21) | 0.96 (0.69–1.33) | 0.88 (0.57–1.37) | 0.89 (0.65–1.20) |
Source: California Cancer Registry. Individuals diagnosed between January 1, 1996 and December 31, 2005. Abbreviations: nSES: neighborhood socioeconomic status, ACM: all-cause mortality, LSM: lymphoma-specific mortality, HR: hazard ratio, CI: confidence interval, Ref: reference.
*Test for significance at
†Test for trend significant at
Compared to earlier stages, later stage at diagnosis appeared to have a slightly stronger effect on ACM after adjustment (adj HR: 3.16, 95% CI: 2.63–3.81) and the adjusted HR for later stage at diagnosis remained high for LSM (adj HR: 3.14, 95% CI: 2.42–4.06). Extranodal involvement appeared to increase risk of overall death, but only after adjustment (adj HR: 1.29, 95% CI: 1.11–1.50). For LSM, extranodal involvement appeared to have a protective effect (HR: 0.71, 95% CI: 0.59–0.86), but there was almost no effect after adjustment (adj HR: 0.99, 95% CI: 0.81–1.22).
Not having received chemotherapy as a first-course treatment appeared protective in the unadjusted ACM analysis (HR: 0.75, 95% CI: 0.62–0.91), but in the full model conferred shorter ACM (adj HR: 1.27, 95% CI: 1.02–1.57). On the contrary, not having first-course chemotherapy yielded protective LSM effects for both the unadjusted (HR: 0.24, 95% CI: 0.16–0.36) and adjusted HR (adj HR: 0.37, 95% CI 0.24–0.57). Results were stratified by stage at diagnosis, and it appears that only in patients with distant-staged NHL was adjusted ACM significantly higher than in patients that did not receive first-course chemotherapy (adj HR: 1.69, 95% CI 1.28–2.24). For patients who did not receive first-course chemotherapy, LSM was improved both in those with localized disease (adj HR: 0.16, 95% CI 0.07–0.38) and those with regional disease (adj HR: 0.11, 95% CI 0.01–0.76). Not receiving first-course radiation therapy yielded significantly worse hazard ratios for the unadjusted ACM (HR: 1.31, 95% CI 1.15–1.50) and LSM (HR: 1.43, 95% CI: 1.19–1.71) estimates, but did not have a significant effect after adjustment.
The effects of decreasing nSES on ACM and LSM significantly worsened with every decreasing quintile both before and after adjustment, with the strongest effects evident at the lowest quintile (
Unadjusted Kaplan-Meier survival curves (
A subgroup analysis was conducted to examine whether marital status, as a means of social support, conferred longer survival among individuals aged 18 and over at diagnosis. After adjustment for the other demographic and clinical parameters in the full model, individuals who were married at diagnosis had 23% lower ACM (adj HR: 0.67, 95% CI: 0.58–0.78) as compared to those who were single, separated, divorced, or widowed at diagnosis. There was no significant difference in lymphoma-specific survival for individuals who were married at diagnosis, as compared to other marital statuses (adj HR: 1.00, 95% CI: 0.83–1.20).
Overall survival analysis was next stratified by the four racial/ethnic groups: NHW, NHB, HL, and API (Table
Multivariate adjusted hazard
Race/Ethnicity | ||||||||||||
Non-Hispanic White | Non-Hispanic | Hispanic/Latino | Asian/Pacific Islander | |||||||||
Characteristic | HR | 95% CI | HR | 95% CI | HR | 95% CI | HR | 95% CI | ||||
Sex | ||||||||||||
Males | 1,178 | 1.00† (Ref) | — | 169 | 1.00† (Ref) | — | 701 | 1.00† (Ref) | — | 209 | 1.00† (Ref) | — |
Females | 627 | 0.66 | 0.54–0.82 | 92 | 0.77 | 0.48–1.23 | 364 | 0.54 | 0.42–0.70 | 149 | 0.73 | 0.45–1.20 |
Age at Diagnosis | ||||||||||||
By year | 1,805 | 1.02 | 1.01–1.04 | 261 | 1.01 | 0.97–1.04 | 1,065 | 1.02* | 1.01–1.04 | 358 | 1.02 | 0.99–1.05 |
Tumor Stage | ||||||||||||
Local | 538 | 1.00† (Ref) | — | 68 | 1.00† (Ref) | — | 341 | 1.00† (Ref) | — | 139 | 1.00† (Ref) | — |
Regional | 367 | 1.21 | 0.86–1.71 | 47 | 0.80 | 0.36–1.79 | 202 | 1.46 | 0.99–2.16 | 88 | 1.01 | 0.47–2.19 |
Distant | 900 | 3.41* | 2.60–4.47 | 146 | 1.89* | 1.02–3.49 | 522 | 3.16* | 2.28–4.39 | 131 | 3.08* | 1.65–5.77 |
Nodality | ||||||||||||
Nodal | 1,319 | 1.00 (Ref) | — | 180 | 1.00 (Ref) | — | 691 | 1.00 (Ref) | — | 216 | 1.00 (Ref) | — |
Extranodal | 486 | 1.51* | 1.21–1.87 | 81 | 0.66 | 0.37–1.16 | 374 | 1.14 | 0.88–1.47 | 142 | 1.43 | 0.85–2.40 |
First-course Chemotherapy | ||||||||||||
Yes | 1,513 | 1.00 (Ref) | — | 222 | 1.00 (Ref) | — | 915 | 1.00 (Ref) | — | 295 | 1.00 (Ref) | — |
No | 292 | 1.24 | 0.90–1.71 | 39 | 2.02* | 1.09–3.71 | 150 | 1.71* | 1.19–2.46 | 63 | 0.25* | 0.08–0.74 |
First-course Radiation | ||||||||||||
Yes | 644 | 1.00 (Ref) | — | 86 | 1.00 (Ref) | — | 309 | 1.00 (Ref) | — | 155 | 1.00 (Ref) | — |
No | 1,161 | 0.90 | 0.74–1.11 | 175 | 0.80 | 0.50–1.29 | 756 | 0.98 | 0.76–1.27 | 203 | 126 | 0.77–2.07 |
nSES | ||||||||||||
Highest | 517 | 1.00 (Ref)† | — | 18 | 1.00 (Ref) | — | 88 | 1.00 (Ref) | — | 125 | 1.00 (Ref) | — |
High | 454 | 1.19 | 0.91–1.55 | 43 | 0.86 | 0.33–2.24 | 138 | 1.14 | 0.69–1.88 | 87 | 0.54 | 0.25–1.17 |
Middle | 388 | 1.33* | 1.01–1.75 | 60 | 0.63 | 0.24–1.65 | 188 | 0.94 | 0.59–1.50 | 69 | 0.90 | 0.46–1.74 |
Low | 287 | 1.62* | 1.22–2.14 | 71 | 0.68 | 0.27–1.71 | 273 | 1.06 | 0.68–1.64 | 40 | 1.06 | 0.51–2.24 |
Lowest | 159 | 2.25* | 1.64–3.08 | 69 | 0.51 | 0.20–1.33 | 378 | 0.97 | 0.63–1.50 | 37 | 1.17 | 0.59–2.33 |
Insurance | ||||||||||||
None | 61 | 1.00 (Ref) | — | 12 | 1.00 (Ref) | — | 93 | 1.00 (Ref) | — | 14 | 1.00 (Ref) | — |
Managed or Private | 1,290 | 0.87 | 0.54–1.38 | 144 | 1.65 | 0.38–7.11 | 508 | 0.64* | 0.43–0.95 | 267 | 0.91 | 0.31–2.71 |
Government | 317 | 1.27 | 0.78–2.05 | 78 | 5.97* | 1.41–25.24 | 340 | 1.00 | 0.68–1.47 | 53 | 1.47 | 0.48–4.56 |
Unknown | 137 | 0.80* | 0.45–1.40 | 27 | 1.72 | 0.35–8.48 | 124 | 0.98 | 0.62–1.53 | 24 | 0.80 | 0.17–3.78 |
Source: California Cancer Registry. Individuals diagnosed between January 1, 1996–December 31, 2005. Abbreviations: nSES: neighborhood socioeconomic status, HR: hazard ratio, CI: confidence interval, Ref: reference.
*Test for significance at
†Test for trend significant at
Not receiving first-course chemotherapy was a significant adverse risk factor in NHBs (adj HR: 2.02, 95% CI: 1.09–3.71) and HLs (adj HR: 1.71, 95% CI: 1.19–2.46), but interestingly, a significant protective factor in APIs (adj HR: 0.25, 95% CI: 0.08–0.74). Not receiving first-course radiation therapy was not a significant hazard for any of the racial/ethnic groups. After stratification by race/ethnicity, decreasing nSES was associated with worse ACM in NHWs, with the middle (adj HR: 1.33, 95% CI: 1.01–1.75), low (adj HR: 1.62, 95% CI: 1.22–2.14), and lowest (adj HR: 2.25, 95% CI: 1.64–3.08) quintiles having significantly higher hazard of overall death than the highest. A linear trend test was significant (
This study is one of the first to examine the impact of socioeconomic status on survival in adolescents and young adults with non-Hodgkin's lymphoma. Our analyses indicate that nSES and treatment variables attenuate much of the racial/ethnic-specific differences in survival and that, after adjustment for demographic and clinical variables, both NHBs and HLs tend to show similar survival patterns to NHWs. Asian/Pacific Islanders, however, showed significantly poorer lymphoma-specific survival than NHWs. Being married at diagnosis, a possible indicator of social support [
Furthermore, when examined across racial/ethnic groups, a significant gradient in survival by nSES was only evident in NHWs. Although not significant, there was a suggestion of lower survival in APIs as nSES decreased, but the low numbers of APIs in the study likely contributed to wide confidence intervals. For HLs, having private insurance contributed to better survival, but for NHB, having government-provided insurance was associated with worse survival.
Similar findings were reported in a cohort of elderly NHL patients (age at diagnosis
A Brazilian study of Hodgkin's lymphoma patients also found higher mortality associated with lower SES that was unexplained by treatment regimen [
However, two other studies of SES impacts on lymphoma survival failed to find a significant association. A hospital-based study in Austria that investigated relapse-free survival (RFS) in a cohort of 218 Hodgkin's lymphoma patients (average age at diagnosis = 35.9
An investigation on survival in NHL patients in Scotland and Wales found 10% and 19% shorter survival in intermediate and most deprived areas, respectively, [
Not finding an SES-mortality gradient in the non-White patients in our study raises several questions about the cancer experience in these populations. First, it is important to reiterate that for NHBs and HLs, although the unadjusted hazard ratios for both ACM and LSM were significantly higher than for NHWs, adjustment for the other factors in the model—including nSES, stage at diagnosis, and first-course treatment—attenuated these risks. As evident in Figure
The lack of a consistent association between health insurance status and survival after adjustment was surprising, given the widely-documented increased vulnerability of patients lacking health insurance. Finding higher all-cause mortality among those with government-provided insurance compared to those without insurance suggests that there may be important disparities in access to care among Medicaid recipients. Approximately double the percentage (17.8%) of those without health insurance compared to those with government-provided health insurance (9.4%) resided in the highest nSES quintile at diagnosis. A paper analyzing the relationship of health insurance status and cancer outcomes across US demographic groups found striking disparities in cancer screening, stage at diagnosis, and survival for those uninsured or insured by Medicare or Medicaid [
One of the strengths of this study is the use of CCR data with a large, heterogeneous, and population-based cohort with almost complete patient ascertainment and follow-up. Registry-based explorations of factors that contribute to longer survival are important to help identify groups that are particularly vulnerable to premature cancer mortality. Because social determinants affect health outcomes along several pathways, it is important to document the existence of persistent health disparities, particularly for understudied groups such as AYAs.
The limitations of this study include the estimation of SES based on the residence at diagnosis, which may not accurately capture some factors that contribute to healthy living environments and adequate medical care. Transitioning through developmental life stages can make AYAs a heterogeneous group; some are dependent on parents and relatives while others provide for families of their own. As such, measuring SES as a one-time neighborhood composite variable may inadequately summarize an individual patient’s social and financial circumstances [
Our study is one of the first to examine socioeconomic impacts on survival in AYAs with NHL. We determined that as neighborhood SES at diagnosis increases, overall- and lymphoma-specific survival improves, after adjustment for demographic and treatment variables, and a linear trend persists. The impact of SES on mortality appeared to be independent of health insurance status at diagnosis. However, when stratified by race/ethnicity, the effects of nSES on mortality were only significant in Non-Hispanic Whites.
This research was supported by the Don and Marty Schmid Adolescent and Young Adult Cancer Fund. The authors would like to thank and acknowledge the members of the LiveSTRONG Young Adult Alliance for helping to generate ideas expressed in this paper. Two anonymous reviewers provided helpful comments in an earlier version of this paper. This study was presented in part at the following two meetings: Kent, E. E., Morris, R. A., Largent, J. A., Sender, L., & Anton-Culver, H. (2009) Socioeconomic disparities in survival vary by race/ethnicity for adolescents and young adults (AYAs) with non-Hodgkin's lymphoma. Poster for the 3rd International Symposium of Childhood and Adolescent Non-Hodgkin's Lymphoma (Frankfurt, Germany, June 11–13) and Kent, E. E., Morris, R. A., Largent, J. A., Sender, L., & Anton-Culver, H. (2009) Socioeconomic influences on survival in adolescents and young adults diagnosed with lymphoma in California. Poster for the American Association for Cancer Research Science of Cancer Health Disparities Conference (Carefree, AZ, February 2–6).