Impact of race, ethnicity and socioeconomic status over time on the long-term survival of adolescent and young adult Hodgkin lymphoma survivors

Abstract

Background:

While there are growing numbers of adolescent and young adult (AYA) Hodgkin’s lymphoma (HL) survivors, long-term overall survival (OS) patterns and disparities in this population are underreported. The aim of the current study was to assess the impact of race/ethnicity, socioeconomic status (SES), rurality, diagnosis age, sex, and HL stage over time on long-term survival in AYA HL survivors.

Methods:

The authors used the Surveillance, Epidemiology, and End Results (SEER) registry to identify survivors of HL diagnosed as AYAs (ages 15–39 years) between the years 1980 and 2009 and who were alive 5 years after diagnosis. An accelerated failure time model was used to estimate survival over time and compare survival between groups.

Results:

There were 15,899 5-year survivors of AYA HL identified with a median follow-up of 14.4 years and range up to 33.9 years from diagnosis. Non-Hispanic Black survivors had inferior survival compared with non-Hispanic White survivors (Survival Time Ratio (STR): 0.71, p=0.002). Male survivors, older age at diagnosis, those diagnosed at higher stages and those living in areas of higher SES deprivation had unfavorable long-term survival. There was no evidence of racial or sex-based survival disparities changing over time.

Conclusions:

Racial, SES, and sex-based disparities persist well into survivorship among AYA HL survivors.

Impact:

Disparities in long-term survival among AYA HL survivors show no evidence of improving over time. Studies investigating specific factors associated with survival disparities are needed to identify opportunities for intervention.

INTRODUCTION

There are approximately 90,000 new cancer diagnoses in adolescents and young adults (AYAs; those aged 15–39 years) in the United States each year, and overall cancer incidence in this age group is rising.¹ Recent data show improvements in cure rates, with 5-year overall survival (OS) rate of greater than 80% among AYA cancer patients.^{2, 3} A small number of studies that have begun to investigate long-term mortality outcomes among AYA cancer survivors have consistently found that, compared with the general population, AYA survivors experience higher mortality rates that persist well into survivorship.^4–6 As the AYA cancer survivor population continues to grow, more data is needed on long-term outcomes, specifically factors associated with inferior long-term survival.

Hodgkin lymphoma (HL) is one of the more prevalent cancers among AYA patients and has favorable 5-year survival of about 94% based on recent data from the Surveillance, Epidemiology, and End Results (SEER) database.² In both childhood and AYA cancer survivor populations, those with HL have increased risks of long-term, non-cancer mortality compared with other cancer types,^{7, 8} making investigation of demographic factors associated with long-term mortality especially important in this population. Socioeconomic status (SES), rurality, race and ethnicity are known to impact 5-year survival in AYA cancer patients, with low SES neighborhood, rural area residence, and Black race associated with worse 5-year survival compared with high SES neighborhood metropolitan residence, and White race, respectively.^9–13 Initial studies have noted racial disparities in 10-year survival of AYA HL patients, however, more comprehensive long-term survivorship studies and those including recent diagnosis time periods are needed.¹⁴

In the current large-scale retrospective analysis of SEER data, we sought to characterize long-term mortality patterns among 5-year survivors of AYA HL and determine the impact of race, SES, rurality, diagnosis age, sex, and HL stage on long-term survival in this population over time. In addition to its focus on disparities in long-term mortality, the current study utilizes a United States population-based registry. Much of the current long-term survivorship data in adolescent HL in the United States comes from the Childhood Cancer Survivorship Study, which is not a population-based cohort,¹⁵ while AYA survivorship data in the European population is drawn from population-based datasets such as the Teenage and Young Adult Cancer Survivor Study and national datasets including those from Nordic countries.^16–18

METHODS

Hodgkin lymphoma data extracted from SEER for the years 1975–2011 included data for 21,081 patients who were alive 5 years after initial diagnosis. The following exclusions were made: 1) Missing race/origin code or classified as American Indian (n=218); 2) Missing county-level statistics (n=5); 3) Missing Rural-Urban Continuum code (n=226); 4) Those diagnosed prior to 1980 or after 2009 (n=3,045); and 5) Missing Ann Arbor Stage data (n=1,688).

A county-level socioeconomic deprivation index (SES index) was defined based upon county-level variables previously defined by Truong et al.¹⁹ County-level variables used in defining the SES index included the level of poverty (P) based upon percentage with income below the 200^th percentile of the poverty line, low educational attainment (E) per the percentage obtaining less than a high school education, crowding (C) per the percentage with room crowding with greater than one person per room, unemployment (U) per the percentage unemployed, levels of immigration (I) per the percentage of foreign-born, and language isolation (L) per the county percentage of language isolation. The variables P, E, C, U, I, L, were each standardized as the difference from the mean divided by the standard deviation. The county SES index was then calculated as (((P + E + C + U)/4) + ((I + L)/2))/2. Note that since this is defined as a socioeconomic deprivation index, higher values are indicative of greater deprivation.

Continuous variables were summarized by decade and overall (all decades pooled) as mean, standard deviation, median, minimum, and maximum. Discrete variables were summarized by decade and overall as count, percentage, mortality count, and mortality percentage. A time-to-event model was used to model the time (following 5 years overall survival) to death with relation to diagnosis decade (1980s, 1990s, 2000s), potential covariates including age at diagnosis (numeric years), rurality (numeric integer 0–8), race and origin (Non-Hispanic White, Hispanic (All Races), Non-Hispanic Black, Non-Hispanic Asian or Pacific Islander), sex (female versus male), Lymphoma Ann Arbor Stage (I-IV), Lymphoma subtype recode per WHO 2008 [1(a)1.1 Lymphocyte-rich, 1(a)1.2 Mixed cellularity, 1(a)1.3 Lymphocyte-depleted, 1(a)2 Nodular sclerosis, 1(a)3 Classical Hodgkin lymphoma, NOS, 1(b) Nodular lymphocyte-predominant Hodgkin lymphoma], and SES index. Interactions with decade of diagnosis were also explored. A Cox proportional hazards model was considered,²⁰ but due to extensive violations of the proportionality of hazards assumption, an accelerated failure time (AFT) model was selected instead; note that an advantage of utilizing accelerated failure time models is that, instead of hazard ratios, comparable interpretation is based upon intuitive survival time ratios. The Weibull distribution was chosen as optimal for analysis due to lower Akaike Information Criterion (AIC) together with good fit of a Kaplan-Meier plot of model residuals to the model distribution. Based upon the AIC and beginning with a model including all variables and interactions with diagnosis decade, an exhaustive reverse process of model selection excluded first interactions followed by main effects variables where the exclusion yielded an improved model with lower AIC. The selection process retained the interactions between decade of diagnosis with Lymphoma Ann Arbor Stage and SES index, as well as the main effects variables.

The optimal model covariates resulting from the selection process included diagnosis decade, age at diagnosis, race and origin, sex, Lymphoma Ann Arbor Stage, lymphoma subtype, and SES index, with interactions of diagnosis decade with Lymphoma Ann Arbor Stage and SES index. Due to investigator interest, the final model included these variables and interactions, plus rurality, and the diagnosis decade interactions with sex and race and origin. The final time-to-event accelerated failure time model of overall survival time (following 5 years survival) to death included the variables diagnosis decade, age at diagnosis, race and origin, sex, Lymphoma Ann Arbor Stage, lymphoma subtype, rurality, and SES index, with interactions of diagnosis decade with sex, race and origin, Lymphoma Ann Arbor Stage, and SES index. Differences among discrete variable levels were assessed by contrasts Tukey-adjusted p-values. Between-decade changes in discrete variable levels were estimated by contrasts with Hommel-adjusted p-values. In the accelerated failure time model, follow-up time was taken into account when comparing survival between diagnosis decade.

An additional AFT model was implemented, which excluded decade interactions in order to allow overall assessment of effects across all decades for variables involved in interactions in the above model. This model was otherwise the same as that described above. Differences among discrete levels of these variables were pooled with those from the prior model, and Hommel-adjusted p-values for the pooled estimates were derived from the pooled unadjusted p-values. Reported p-values reflect these adjustments.

Statistical analyses were performed using R statistical software (R Core Team, 2020, version 3.6.3).²¹ In all statistical tests, two-sided alpha=0.05. Survival modeling was performed using the “survival” package.^{22, 23} Assessment of differences among discrete variable levels in the accelerated failure time model were estimated using the “emmeans” package;²⁴ this includes adjusted means weighted proportionally to covariate marginal frequencies. Catseye plots were produced using the “catseyes” package.^{25, 26}

RESULTS

Patient Characteristics

The characteristics of 15,899 5-year survivors of HL included in the analysis are shown in Table 1. Fifty percent of the cohort was female. Ten percent were Black, 12% were Hispanic (all races), 4% were non-Hispanic Asian or Pacific Islander, and 74% were non-Hispanic White. The median age of diagnosis was 27 years and the median follow-up time (from 5-year survival) was 9.4 years (range 0.1 to 28.9 years). Among survivors, 14% were diagnosed in the 1980s, 27% in the 1990s, and 58% in the 2000s. When considering stage, 20% of diagnoses were stage I, 49% were stage II, 19% were stage III, and 13% were stage IV. Overall mortality rate was 11%, and mortality rates (unadjusted for differential follow-up time) for those diagnosed in the 1980s, 1990s, and 2000s were 30%, 13%, and 5%, respectively (these raw mortality rates are unadjusted for differential follow-up times among the decades). The county-level SES index as well as the county-level variables which informed the SES index are summarized in Table 1, where the median SES index was −0.2. Accelerated failure time model results are summarized separately by variable below.

Table 1.

Survivor Characteristics

	No. (%)
Characteristic	n=15,899
Sex
Female	7,911 (49.8)
Male	7,988 (50.2)
Age at Diagnosis
Mean ± STD	26.9 ± 6.7
Median(range)	27 (15–39)
Follow-up Time
Mean ± STD	10.9 ± 7.1
Median(range)	9.4 (0.1–28.9)
Race/Ethnicity
Non-Hispanic White	11,803 (74.2)
Non-Hispanic Black	1643 (10.3)
Hispanic (All Races)	1848 (11.6)
Non-Hispanic Asian or Pacific Islander	605 (3.8)
Decade of Diagnosis
1980s	2,303 (14.5)
1990s	4,319 (27.2)
2000s	9,277 (58.3)
Stage
I	3,198 (20.1)
II	7,728 (48.6)
III	2,943 (18.5)
IV	2,030 (12.8)
Rurality Index, Mean ± STD	0.7 ± 1.5
County % <200% Poverty
Mean ± STD	30.5 ± 8.9
Median(range)	28.2 (10.0–71.9)
County % HS Education
Mean ± STD	12.6 ± 5.5
Median(range)	11.2 (2.1–37.0)
County % Housed >1 per Room
Mean ± STD	4.4 ± 3.4
Median(range)	2.9 (0.0–13.0)
County % Unemployed
Mean ± STD	6.9 ± 2.1
Median(range)	6.7 (1.3–17.2)
County % Foreign Born
Mean ± STD	17.7 ± 11.0
Median(range)	15.4 (0.0–43.0)
County % Language Isolated
Mean ± STD	5.8 ± 4.0
Median(range)	4.9 (0.0–21.9)
SES Index
Mean ± STD	0.0 ± 0.8
Median(range)	−0.2 (−1.4–2.8)

Survival by Race/Ethnicity

Overall, non-Hispanic Black 5-year AYA HL survivors had significantly worse long-term survival compared with non-Hispanic White survivors, and while not reaching statistical significance, long-term survival of Hispanic survivors was also worse than that of non-Hispanic White survivors (Table 2). Non-Hispanic Black survival was 66% that of non-Hispanic Whites (Survival Time Ratio (STR): 0.66, p <.0001) and survival of the Hispanic (all races) patients was 78% that of non-Hispanic Whites (STR: 0.78, p=0.09), though not significant. There were no other significant differences in survival by race/ethnicity in the overall population. When stratifying by decade of diagnosis, racial/ethnic disparities in survival were significant for those non-Hispanic Blacks diagnosed in the 2000s, attaining 54% (STR: 0.54, p=<.0001) of the survival attained by non-Hispanic Whites; this trend was similar during the 1990s (STR: 0.66, p=.021). Hispanics of all races attained 69% (STR: 0.69, p=0.20) of the survival attained by non-Hispanic Whites diagnosed in the 2000s, though the trend lacked significance.

Table 2.

Differences in Survival by Race and Ethnicity. These are estimated from the accelerated failure time survival model which included the covariates diagnosis decade, age at diagnosis, race and origin, sex, Lymphoma Ann Arbor Stage, lymphoma subtype, rurality, and SES index, with interactions of diagnosis decade with Sex, race and origin, Lymphoma Ann Arbor Stage, and SES index. Hommel-adjusted p-values are shown.

Race/Ethnicity Comparison	Decade of Diagnosis Comparison	Survival Time Ratio (95% CI)	p-value
Non-Hispanic Black - Non-Hispanic White
Overall		0.66 (0.57–0.76)	<.0001
1980s		0.79 (0.60–1.05)	1
1990s		0.66 (0.52–0.85)	0.021
2000s		0.54 (0.42–0.70)	<.0001
Hispanic (All Races) - Non-Hispanic White
Overall		0.78 (0.66–0.93)	0.09
1980s		1.00 (1.00–1.00)	1
1990s		0.73 (0.55–0.95)	0.38
2000s		0.69 (0.53–0.92)	0.20
Non-Hispanic Black - Hispanic (All Races)
Overall		0.84 (0.69–1.03)	0.82
1980s		0.79 (0.52–1.21)	0.99
1990s		0.91 (0.66–1.27)	0.99
2000s		0.78 (0.56–1.09)	0.99
Change in Survival by Diagnosis Decade
Non-Hispanic White	1990s – 1980s	1.91 (1.66–2.20)	<.0001
Non-Hispanic White	2000s – 1980s	2.75 (2.29–3.31)	<.0001
Non-Hispanic White	2000s – 1990s	1.44 (1.22–1.70)	0.0001
Hispanic (All Races)	1990s – 1980s	1.38 (0.91–2.10)	0.28
Hispanic (All Races)	2000s – 1980s	1.91 (1.25–2.92)	0.008
Hispanic (All Races)	2000s – 1990s	1.38 (0.96–1.97)	0.18
Non-Hispanic Black	1990s – 1980s	1.60 (1.13–2.26)	0.023
Non-Hispanic Black	2000s – 1980s	1.89 (1.32–2.70)	0.002
Non-Hispanic Black	2000s – 1990s	1.18 (0.86–1.63)	0.56
Change in Racial/Ethnic Disparities Over Time
Non-Hispanic White - Hispanic	2000s – 1990s	1.04 (0.71–1.54)	0.97
Non-Hispanic White - Non-Hispanic Black	2000s – 1990s	1.22 (0.86–1.73)	0.97
Hispanic - Non-Hispanic Black	2000s – 1990s	1.17 (0.73–1.86)	0.97
Non-Hispanic White - Hispanic	2000s – 1980s	1.44 (0.97–2.24)	0.93
Non-Hispanic White - Non-Hispanic Black	2000s – 1980s	1.46 (1.00–2.13)	0.68
Hispanic - Non-Hispanic Black	2000s – 1980s	1.01 (0.59–1.73)	0.97
Non-Hispanic White - Hispanic	1990s – 1980s	1.38 (0.89–2.14)	0.97
Non-Hispanic White - Non-Hispanic Black	1990s – 1980s	1.20 (0.83–1.73)	0.97
Hispanic - Non-Hispanic Black	1990s – 1980s	0.87 (0.51–1.48)	0.97

When assessing survival of 5-year AYA HL survivors over time, non-Hispanic Blacks, Hispanics, and non-Hispanic Whites each had improvements in survival for those diagnosed in the 2000s compared with those diagnosed in the 1980s (Table 2). Non-Hispanic Blacks diagnosed in the 2000s had nearly twice the survival time as those diagnosed in the 1980s (STR: 1.89, p=0.002), which was similar to Hispanics diagnosed in the 2000s compared with those diagnosed in the 1980s (STR: 1.91, p=0.008). Non-Hispanic White 5-year survivors of AYA HL diagnosed in the 2000s had survival times of almost three times as long as those diagnosed in the 1980s (STR: 2.75, p<0.0001). The survival disparity by race/ethnicity showed no evidence of change over time, with the non-Hispanic White to non-Hispanic Black and Hispanic gap not significantly different between those diagnosed in the 2000s and those diagnosed in the 1980s (Table 2, p=0.68 and 0.93, respectively).

Survival by SES

Survival time decreased as the county socioeconomic deprivation index (SES index) increased with higher index values indicating higher levels of social deprivation and thus lower SES. Overall, each additional unit increase on the SES index was associated with an 8% reduction in survival time (STR: 0.92, p=0.002, Table 3). When looking at SES disparities by decade, higher SES index was associated with decreased survival for AYA HL survivors diagnosed in the 1980s (STR: 0.761, p=0.001). There were no significant differences in long-term survival by SES level for AYA HL survivors diagnosed in the 1990s or 2000s (p= 0.56 and p=0.09, respectively). There was significant evidence of improving survival between the 1980s and 1990s (p=.003), however significant evidence of this improvement was absent between the 1980s and 2000s (p=.32).

Table 3.

Rates of Change in Survival by Age, Rurality, and county SES index. These are estimated from the accelerated failure time survival model which included the covariates diagnosis decade, age at diagnosis, race and origin, sex, Lymphoma Ann Arbor Stage, lymphoma subtype, rurality, and SES index, with interactions of diagnosis decade with Sex, race and origin, Lymphoma Ann Arbor Stage, and SES index. Hommel-adjusted p-values are shown for SES index, except for the difference between decades which shows Tukey-adjusted p-values. Age at diagnosis and rurality p-values are unadjusted since these variables were not part of an interaction leading to multiple comparisons.

Continuous Variable	Survival Time Ratio (95% CI)	p-value
Age at Diagnosis	0.964 (0.957–0.972)	<0.0001
Rurality	0.976 (0.943–1.011)	0.18
SES Index
Overall	0.920 (0.853–0.992)	0.002
1980s	0.761 (0.651–0.889)	0.001
1990s	1.033 (0.926–1.153)	0.56
2000s	0.882 (0.853–0.992)	0.09
SES Index (difference between decades)
1990s – 1980s	1.358 (1.129–1.635)	0.003
2000s – 1980s	1.159 (0.948–1.416)	0.32
2000s – 1990s	0.853 (0.720–1.010)	0.07

Survival by Rurality, Age at Diagnosis, and Sex

Age at diagnosis impacted long-term survival in 5-year AYA HL survivors (Table 3), with each additional year of age at diagnosis associated with a 4% reduction in survival time (STR: 0.964, p<0.0001). There was no significant change in survival by rurality (p=0.18) in our population (Table 3).

Female 5-year AYA HL survivors had significantly longer survival time than males, overall and when stratified by decade of diagnosis (Table 4). Overall, males attained 68% of females’ survival time (STR: 0.68, p<0.0001). Males diagnosed in the 1980s, 1990s, and 2000s attained 72% (STR: 0.72, p<0.0001), 68% (STR: 0.68, p<0.0001), and 60% (STR: 0.60, p<0.0001), respectively, of the survival of females diagnosed in those same decades. Both female and male 5-year survivors of AYA HL had significantly improved survival over time. Female survivors diagnosed in the 2000s had nearly three times the survival time as those diagnosed in the 1980s (STR: 2.89, p<0.0001). Male survivors diagnosed in the 2000s had over two times the survival time as those diagnosed in the 1980s (STR: 2.23, p<0.0001). The survival disparity by sex did not change significantly over time (Table 4), with the female to male survival gap not significantly different between those diagnosed in the 2000s and those diagnosed in the 1980s (p=0.43).

Table 4.

Differences in Survival by Sex. These are estimated from the accelerated failure time survival model which included the covariates diagnosis decade, age at diagnosis, race and origin, sex, Lymphoma Ann Arbor Stage, lymphoma subtype, rurality, and SES index, with interactions of diagnosis decade with Sex, race and origin, Lymphoma Ann Arbor Stage, and SES index. Hommel-adjusted p-values are shown.

Sex Comparison	Decade of Diagnosis Comparison	Survival Time Ratio (95% CI)	p-value
Male - Female
Overall		0.68 (0.61–0.75)	<.0001
1980s		0.72 (0.62–0.84)	<.0001
1990s		0.68 (0.57–0.80)	<.0001
2000s		0.60 (0.49–0.73)	<.0001
Change in Survival by Diagnosis Decade
Female	1990s – 1980s	1.80 (1.50–2.17)	<.0001
	2000s – 1980s	2.89 (2.14–3.38)	<.0001
	2000s – 1990s	1.49 (1.21–1.85)	0.0007
Male	1990s – 1980s	1.69 (1.44–1.98)	<.0001
	2000s – 1980s	2.23 (1.85–2.70)	<.0001
	2000s – 1990s	1.32 (1.11–1.57)	0.004
Change in Sex Disparities Over Time
Female - Male	2000s – 1990s	1.13 (0.87–1.46)	0.56
	2000s – 1980s	1.21 (0.94–1.55)	0.43
	1990s – 1980s	1.07 (0.85–1.34)	0.56

Survival by HL Stage

As expected, a higher stage at diagnosis was associated with worse long-term survival compared with those 5-year AYA HL survivors diagnosed at earlier stages (Table 5a). Focusing on overall changes, there was no difference in long-term survival among those diagnosed at stage II, compared with those diagnosed at stage I (p=0.13). However, those diagnosed at stage III (STR: 0.68, p<0.0001) and stage IV (STR: 0.59, p<0.0001) had significantly worse survival than those diagnosed at stage I. Additionally, 5-year AYA HL survivors diagnosed at stage III attained 81% the survival time attained by those diagnosed at stage II (STR: 0.81, p=0.012), and those diagnosed at stage IV attained 70% the survival time of those diagnosed at stage II (STR: 0.70, p<0.0001). There were no significant differences in long-term survival between 5-year AYA HL survivors diagnosed at stage IV and stage III. There was no evidence that the between-stage differences in survival changed between decades (Table 5b).

Table 5a and 5b.

Differences in Survival by Lymphoma Stage at Diagnosis. These are estimated from the accelerated failure time survival model which included the covariates diagnosis decade, age at diagnosis, race and origin, sex, Lymphoma Ann Arbor Stage, lymphoma subtype, rurality, and SES index, with interactions of diagnosis decade with Sex, race and origin, Lymphoma Ann Arbor Stage, and SES index. Hommel-adjusted p-values are shown. There was no significant evidence that between-stage differences changed between decades.

5a.
Stage Comparison	Survival Time Ratio (95% CI)	p-value
Stage II - Stage I
Overall	0.84 (0.74–0.96)	0.13
1980s	0.83 (0.69–1.01)	0.31
1990s	0.84 (0.67–1.05)	0.49
2000s	0.78 (0.58–1.06)	0.45
Stage III - Stage I
Overall	0.68 (0.59–0.79)	<.0001
1980s	0.79 (0.63–0.98)	0.20
1990s	0.67 (0.52–0.85)	0.020
2000s	0.54 (0.39–0.75)	0.004
Stage III - Stage II
Overall	0.81 (0.71–0.92)	0.012
1980s	0.94 (0.77–1.15)	0.78
1990s	0.79 (0.64–0.98)	0.22
2000s	0.69 (0.54–0.88)	0.047
Stage IV - Stage I
Overall	0.59 (0.50–0.69)	<.0001
1980s	0.76 (0.60–0.97)	0.20
1990s	0.52 (0.40–0.69)	<.0001
2000s	0.43 (0.31–0.60)	<.0001
Stage IV - Stage II
Overall	0.70 (0.61–0.80)	<.0001
1980s	0.91 (0.73–1.14)	0.78
1990s	0.62 (0.49–0.79)	0.002
2000s	0.55 (0.43–0.71)	<.0001
Stage IV - Stage III
Overall	0.86 (0.74–1.00)	0.25
1980s	0.97 (0.76–1.23)	0.78
1990s	0.78 (0.61–1.02)	0.31
2000s	0.80 (0.60–1.06)	0.49
5b.
Comparison	Survival Time Ratio (95% CI)	p-value
Difference between Diagnosis Decade
Stage I
1990s – 1980s	1.88 (1.47 – 2.4)	<0.0001
2000s – 1980s	2.91 (2.11 – 4.02)	<0.0001
2000s – 1990s	1.55 (1.12 – 2.14)	0.022
Stage II
1990s – 1980s	1.89 (1.57 – 2.28)	<0.0001
2000s – 1980s	2.74 (2.2 – 3.41)	<0.0001
2000s – 1990s	1.45 (1.18 – 1.77)	0.001
Stage III
1990s – 1980s	1.59 (1.25 – 2.02)	0.0004
2000s – 1980s	2 (1.51 – 2.63)	<0.0001
2000s – 1990s	1.25 (0.96 – 1.65)	0.23
Stage IV
1990s – 1980s	1.3 (0.98 – 1.72)	0.16
2000s – 1980s	1.66 (1.23 – 2.23)	0.002
2000s – 1990s	1.28 (0.95 – 1.71)	0.23

DISCUSSION

We found that racial, ethnic and SES disparities in mortality persist for decades after diagnosis among 5-year survivors of HL diagnosed as AYAs. We also found that demographic and cancer-related factors, including age at diagnosis, sex, and HL stage impact long-term OS in this population. Specifically, Black race or Hispanic ethnicity, higher county-level SES deprivation level, male sex, older age at diagnosis, and later HL stage were all associated with inferior long-term survival. While previous studies have focused on early survival, the current study included only 5-year survivors of AYA HL and extends follow-time for up to 30 years. We found no evidence that these disparities, particularly racial/ethnic disparities, improved over time.

The findings in the current study are consistent with and expand on previous findings that race, ethnicity, and SES factors impact short-term survival in AYA HL patients. We found that racial/ethnic disparities persist long-term among 5-year HL survivors, with both non-Hispanic Black and Hispanic survivors having inferior long-term OS compared with non-Hispanic White survivors. This is consistent with previous data reporting decreases in both 5-year survival and longer-term survival among Black AYA HL survivors, compared with White survivors, however previous studies have found no differences in longer-term survival between non-Hispanic Whites and Hispanics.^{14, 27, 28} Recent data have found race/ethnicity based disparities among AYA HL survivors that likely contribute to the long-term survival disparities found in the current study. Compared with non-Hispanic White AYA HL survivors, non-Hispanic Black survivors were more likely to have cardiovascular disease and both non-Hispanic Black and Hispanic survivors were more likely to have endocrine disease, with any late effect doubling the risk of mortality in this population.²⁹ Among adult cancer survivors, it has been shown that Hispanic and non-Hispanic Black cancer survivors, compared with non-Hispanic White cancer survivors are less likely to report consistent and comprehensive follow-up care, such as seeing a specialist, adherence to preventive health services guidelines, and adherence to prescribed medications.^30–34 Additionally, compared with non-Hispanic White cancer survivors, non-Hispanic Black and Hispanic cancer survivors are more likely to be obese, not meet physical activity guidelines, and not meet dietary guidelines.^35–38 Taken together, these factors could place non-Hispanic Black and Hispanic cancer survivors at increased risk of late mortality, compared with White cancer survivors and represent opportunities for focused intervention. Structural racism is also likely to be contributing to the persistent racial/ethnic disparities seen in the current study, particularly as it relates to healthcare access and SES disparities.³⁹

When assessing survival differences by decade of diagnosis, we found that there were no significant racial/ethnic differences in long-term survival for 5-year AYA HL survivors diagnosed in the 1980s. Overall, there has been significant improvement in long-term survival for AYA HL patients diagnosed in more recent decades compared with those diagnosed in the 1980s.⁴ In this same timeframe the toxicity profile of chemotherapeutic agents and radiation techniques has improved significantly.⁴⁰ It is possible that the high long-term toxicity associated with HL treatments in the 1980s affected long-term mortality for those diagnosed in this decade to a greater extent than the aforementioned factors contributing to racial/ethnic differences in long-term survival, thus reducing racial/ethnic disparities in long-term mortality for those AYA HL survivors diagnosed in the 1980s. This study was also likely underpowered to assess racial and ethnic disparities within the cohort diagnosed in the 1980s.

The current study found that higher SES index (lower SES status) was associated with inferior survival compared with those AYA HL survivors with lower SES index (higher SES status). Previous studies have also shown that lower SES, compared with higher SES negative impacts survival at up to 15 years among AYA HL patients.¹² Low SES has been shown to impact access to care including findings of an increased likelihood of diagnosis delays and decreased use of subspecialty care, treatment, and survivorship care which likely contribute to disparities in both short-term and long-term mortality.^41–44 Specific to late-effects of treatment, AYA cancer survivors living in low SES neighborhoods have a higher risk of cardiovascular disease compared with AYA cancer survivors residing in higher SES neighborhoods, which in turn, increases risk of long-term mortality.⁴⁵ This risk is likely compounded for AYA HL survivors, who have higher risk of death after development of cardiovascular disease compared with most other AYA cancer types.⁴⁵ Additionally, education level on its own significantly impacts survivorship care, with lower education levels less likely to receive written survivorship care plans, and education less than high school associated with declining levels of medical care throughout survivorship.^{43, 46}

For cancer patients, living in a rural or non-metropolitan area compared with living in an urban or metropolitan area can affect both short and long term mortality through multiple pathways including increased symptom to treatment time interval, lower likelihood of being insured and receiving recommended therapies, decreased access to cancer specialty and support services, and higher prevalence of behavioral risk factors that increase the risk of mortality including smoking and lack of physical activity.^47–52 Among AYA cancer patients, data on differences in mortality by urban versus rural location is limited and mixed.^{53, 54} In the current study, we found that long-term survival was not impacted by rurality. However, rurality data was captured at the time of diagnosis, and the AYA age group tends to be highly mobile. According to the US Census Bureau 2005–2010 data, overall 5-year moving rates were highest (65.5%) among those aged 25 to 29 years. Those age 18 to 24 years had a 48% 5-year moving rate and those aged 30 to 44 years had a 45.5% moving rate. However, a large proportion of these moves were within county. Overall, among those aged 18 to 24, 25 to 29, and 30 to 44, 27.9%, 37.5%, and 27.6%, respectfully, moved to a different location within the same county.⁵⁵ Thus it is plausible that some of the population included in the current study could have moved locations throughout the follow-up period, and the challenges of survivorship care in rural areas have not been captured.

The current study also found that higher stage at diagnosis, male sex, and older age at diagnosis, all known risk factors for early mortality, also increase the risk of long-term mortality among AYA HL survivors. Higher stage at diagnosis may require more intense chemotherapy, mediastinal radiation, and even allogeneic hematopoietic stem cell transplant, all increasing the risks of long-term morbidity and mortality.⁵⁶ Older ages at diagnosis will naturally accrue age related morbidities earlier in survivorship compared with those diagnosed at young ages. Similar to data from the childhood HL survivor population,⁵⁷ dramatic sex based differences in long-term survival among AYA HL survivors were seen, which may reflect this trend in the general population,⁵⁸ as risks of major treatment-related causes of late morbidity in HL survivors including secondary neoplasms and cardiovascular disease do not differ by sex.^{59, 60} Despite similar incidence of cardiovascular disease in HL survivors, males survivors do have increased risk of cardiovascular mortality compared with female survivors, which likely contributes to the sex based survival differences seen in the current study.⁶¹ Given that breast cancer is one of the most common secondary malignancies after HL treatment, it could be expected that women would have worse long-term survival, though studies have reported similar prevalence of second malignancies and mortality from solid tumors in male and female HL survivors.^{59, 61–63} Studies have also shown that there are no sex differences in receipt of recommended late-effects screening in AYA HL survivors;⁶⁴ however, among AYA cancer survivors in general, male sex has been associated with less frequent engagement in survivorship care.⁶⁵

Importantly, the current study did not find any evidence of disparities in long-term survival in AYA HL survivors changing over time. This is an expected finding in age and stage at diagnosis disparities. However, it is a discouraging trend, particularly in race/ethnicity disparities, though this is consistent with recent data showing stable to worsening race/ethnicity disparities over time in 5-year survival among AYA cancer patients.^{1, 10} Additionally, AYA HL survivors are at increased risk of cardiac mortality, in which racial disparities in mortality have also increased over time.^{66, 67} While the relationship between SES and race/ethnicity could not be fully resolved as SES was defined on the county level and race/ethnicity on the individual level, the findings in the current study are particularly striking given that race is an independent factor in the statistical model, thus minimizing the complex interplay between SES and race often found when assessing survival disparities. We also found that sex-based survival differences in AYA HL survivors did not change over time.

While the SEER registries are widely considered as a definitive source of cancer data in the U.S., some limitations come with using this dataset. The SEER dataset does contain some treatment information, however, data on specific chemotherapy and radiation regimens are not available, thus the extent to which treatment variables contributed to the disparities found in the current study is unknown. Rural populations are underrepresented in this dataset, which could have limited our ability to capture rural-urban disparities in long-term mortality of AYA HL survivors. Finally, this data describes sociodemographic variables associated with survival disparities, but cannot elucidate the reasons behind these differences. Socioeconomic data collected from SEER is not collected on an individual patient basis and SES status and patient location are not tracked over time, limiting conclusions that can be drawn. Census tract data in SEER is unavailable prior to the year 2000, and thus could not be utilized to study long-term survivors. We utilized these data to create a county level SES deprivation index, and while an imperfect substitute for individual level data, broadly, we found that county SES status impacts long-term mortality in AYA HL survivors. The extent to which SES impacts racial/ethnic survival disparities needs to be studied further and analyses including more refined SES data are needed to provide clarity on the impact of patient level SES status on long-term survival. A strength of this study is the large sample size that allows examination of each sociodemographic factor and analysis of changes in disparities over time. Follow-up time is also a strength.

The findings in the current study have demonstrated that race/ethnicity, SES, sex, age, and stage at diagnosis impact mortality outcomes in AYA HL 5-year survivors at up to 3 decades of follow-up. This data is unique in its focus on 5-year survivors and extends follow-up time beyond that previously assessed in this population. With improved cure rates for AYAs with HL, additional attention is needed to improve long-term outcomes for specific high-risk populations. Treatment-related modifications that have been implemented in the overall HL population, including decreasing utilization of mediastinal radiation and limiting exposure to toxic agents such as bleomycin, will likely continue to lead to improved long-term outcomes for AYAs, however, further studies are needed to understand why racial, ethnic, SES, and sex disparities persist years after cancer treatment has been completed. Identification of factors associated with long-term mortality among 5-year survivors of AYA HL may allow for targeted screening and follow-up by clinicians as well as the development of early interventions on known risk factors.