Poverty, race, ethnicity, and survival in pediatric nonmetastatic osteosarcoma: a Children’s Oncology Group report

Lenka Ilcisin; Ruxu Han; Mark Krailo; David S Shulman; Brent R Weil; Christopher B Weldon; Puja Umaretiya; Rahela Aziz-Bose; Katie A Greenzang; Richard Gorlick; Damon R Reed; R Lor Randall; Helen Nadel; Odion Binitie; Steven G Dubois; Katherine A Janeway; Kira Bona

doi:10.1093/jnci/djae103

. 2024 Jun 26;116(10):1664–1674. doi: 10.1093/jnci/djae103

Poverty, race, ethnicity, and survival in pediatric nonmetastatic osteosarcoma: a Children’s Oncology Group report

Lenka Ilcisin ^1,², Ruxu Han ³, Mark Krailo ^4,⁵, David S Shulman ⁶, Brent R Weil ⁷, Christopher B Weldon ⁸, Puja Umaretiya ⁹, Rahela Aziz-Bose ¹⁰, Katie A Greenzang ¹¹, Richard Gorlick ¹², Damon R Reed ¹³, R Lor Randall ¹⁴, Helen Nadel ¹⁵, Odion Binitie ¹⁶, Steven G Dubois ¹⁷, Katherine A Janeway ¹⁸, Kira Bona ^19,^✉

¹ Department of Pediatric Oncology, Division of Population Sciences, Dana-Farber/Boston Children’s Cancer and Blood Disorders Center, Harvard Medical School, Boston, MA, USA

² Department of Surgery, Boston Children’s Hospital, Harvard Medical School, Boston, MA, USA

³ Children’s Oncology Group, Monrovia, CA, USA

⁴ Children’s Oncology Group, Arcadia, CA, USA

⁵ Department of Population and Public Health Sciences Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA

⁶ Department of Pediatric Oncology, Division of Population Sciences, Dana-Farber/Boston Children’s Cancer and Blood Disorders Center, Harvard Medical School, Boston, MA, USA

⁷ Department of Surgery, Boston Children’s Hospital, Harvard Medical School, Boston, MA, USA

⁸ Department of Surgery, Boston Children’s Hospital, Harvard Medical School, Boston, MA, USA

⁹ Department of Pediatrics, University of Texas Southwestern Medical Center, Dallas, TX, USA

¹⁰ Department of Pediatric Oncology, Division of Population Sciences, Dana-Farber/Boston Children’s Cancer and Blood Disorders Center, Harvard Medical School, Boston, MA, USA

¹¹ Department of Pediatric Oncology, Division of Population Sciences, Dana-Farber/Boston Children’s Cancer and Blood Disorders Center, Harvard Medical School, Boston, MA, USA

¹² Division of Pediatrics, University of Texas MD Anderson Cancer Center, Houston, TX, USA

¹³ Division of Pediatric Solid Tumors, Memorial Sloan Kettering Cancer Center, New York, NY, USA

¹⁴ Department of Orthopaedic Surgery, University of California Davis Health, Sacramento, CA, USA

¹⁵ Division of Radiology, Lucille Packard Children’s Hospital at Stanford University, Stanford, CA, USA

¹⁶ Department of Surgery, Moffitt Cancer Center, Tampa, FL, USA

¹⁷ Department of Pediatric Oncology, Division of Population Sciences, Dana-Farber/Boston Children’s Cancer and Blood Disorders Center, Harvard Medical School, Boston, MA, USA

¹⁸ Department of Pediatric Oncology, Division of Population Sciences, Dana-Farber/Boston Children’s Cancer and Blood Disorders Center, Harvard Medical School, Boston, MA, USA

¹⁹ Department of Pediatric Oncology, Division of Population Sciences, Dana-Farber/Boston Children’s Cancer and Blood Disorders Center, Harvard Medical School, Boston, MA, USA

^✉

Correspondence to: Kira Bona, MD, MPH, Department of Pediatric Oncology, Dana-Farber Cancer Institute, 450 Brookline Ave, Boston, MA 02115, USA (e-mail: kira.bona@childrens.harvard.edu).

Roles

Lenka Ilcisin: MD, MPH, Conceptualization, Investigation, Writing - original draft, Writing - review & editing

Ruxu Han: MS, Data curation, Formal analysis, Methodology, Writing - review & editing

Mark Krailo: PhD, Data curation, Formal analysis, Investigation, Methodology, Project administration, Supervision, Writing - original draft, Writing - review & editing

David S Shulman: MD, Writing - review & editing

Brent R Weil: MD, MPH, Writing - review & editing

Christopher B Weldon: MD, PhD, Writing - review & editing

Puja Umaretiya: MD, MS, Writing - review & editing

Rahela Aziz-Bose: MD, Writing - review & editing

Katie A Greenzang: MD, EDM, Writing - review & editing

Richard Gorlick: MD, Investigation, Writing - review & editing

Damon R Reed: MD, Investigation, Writing - review & editing

R Lor Randall: MD, Writing - review & editing

Helen Nadel: MD, Investigation, Writing - review & editing

Steven G Dubois: MD, MS, Methodology, Writing - review & editing

Katherine A Janeway: MD, MMSc, Investigation, Methodology, Writing - review & editing

Kira Bona: MD, MPH, Conceptualization, Investigation, Methodology, Writing - original draft, Writing - review & editing

PMCID: PMC12116299 PMID: 38926133

Abstract

Background

Children living in poverty and those of marginalized race or ethnicity experience inferior disease outcomes across many cancers. Whether survival disparities exist in osteosarcoma is poorly defined. We investigated the association between race, ethnicity, and proxied poverty exposures and event-free and overall survival for children with nonmetastatic osteosarcoma receiving care on a cooperative group trial.

Methods

We conducted a retrospective cohort study of US patients with nonmetastatic, osteosarcoma aged 5-21 years enrolled on the Children’s Oncology Group trial AOST0331. Race and ethnicity were categorized to reflect historically marginalized populations, as Hispanic, non-Hispanic Black, non-Hispanic Other, and non-Hispanic White. Poverty was proxied at the household and neighborhood levels. Overall survival and event-free survival functions of time from trial enrollment were estimated using the Kaplan–Meier method. Hypotheses of associations between risks for event-free survival, death, and postrelapse death with race and ethnicity were assessed using log-rank tests.

Results

Among 758 patients, 25.6% were household-poverty and 28.5% neighborhood-poverty exposed. Of the patients, 21% of children identified as Hispanic, 15.4% non-Hispanic Black, 5.3% non-Hispanic Other, and 54.0% non-Hispanic White. Neither household or neighborhood poverty nor race and ethnicity were statistically significantly associated with risks for event-free survival or death. Postrelapse risk for death differed statistically significantly across race and ethnicity with non-Hispanic Black patients at greatest risk (4-year postrelapse survival 35.7% Hispanic vs 13.0% non-Hispanic Black vs 43.8% non-Hispanic Other vs 38.9% non-Hispanic White; P = .0046).

Conclusions

Neither proxied poverty exposures or race and ethnicity were associated with event-free survival or overall survival, suggesting equitable outcomes following frontline osteosarcoma trial-delivered therapy. Non-Hispanic Black children experienced statistically significant inferior postrelapse survival. Investigation of mechanisms underlying postrelapse disparities are paramount.

Osteosarcoma is the most common primary bone malignancy in childhood (1), and survival outcomes remain poor with limited improvement since the introduction of multi-agent chemotherapy 4 decades ago (2-5). Although established risk factors for disease relapse are well delineated, including tumor site and histologic response to neoadjuvant chemotherapy (6-8), efforts to improve outcomes with risk-adapted therapy have been unsuccessful (3,9,10). Identification of novel, modifiable risk factors is critical to improving outcomes in tandem with development and evaluation of new therapeutics.

Adverse social determinants of health (SDOH) including poverty, unmet material needs, and structural inequalities underlie profound health disparities in adult and pediatric populations (11-13). Childhood cancer is no exception, and population-based studies have identified racial, ethnic, and socioeconomic disparities in relapse and survival across multiple diseases (14-16). Strikingly, disparities for historically marginalized populations persist in the clinical trial setting for common childhood malignancies including leukemia, lymphoma, and neuroblastoma despite access to highly standardized care (17-20). SDOH are thus emerging as important targets for intervention to improve outcomes across pediatric specialties (21-24).

Although the contribution of SDOH to osteosarcoma outcomes remains poorly defined, the question of whether SDOH contribute to relapse and survival is of particular importance in a disease that has seen limited treatment improvements over the past decades. Approximately 1 in 6 US children lives in poverty (25), and approximately half identify as a race or ethnicity other than non-Hispanic White (26). US children who identify as Black or Hispanic are respectively 2 and 3 times as likely to live in poverty—a key health-related adverse SDOH—compared with their non-Hispanic White counterparts (27), and socioeconomic status mediates a clinically significant proportion of observed outcome disparities in childhood cancer (28). Prior studies have demonstrated that children of Black race and Hispanic ethnicity experience a higher incidence of osteosarcoma (29,30) and present with more advanced osteosarcoma compared with non-Hispanic White children (31-33). Whether these findings translate to disparities in survival has not been conclusively determined, and no studies have examined the impact of socioeconomic status in the trial-based setting—where standardized care delivery may mitigate disparities observed at the population level (30,34,35). Identification of osteosarcoma survival disparities based on poverty exposures in the trial setting would provide opportunities for supportive care interventions to improve outcomes as the search for new therapeutics continues (5,36).

To address this gap, we used data from US patients enrolled on the Children’s Oncology Group (COG) trial AOST0331 (37) to investigate the relationship between race, ethnicity, and proxied poverty exposures and event-free survival and overall survival for children with nonmetastatic osteosarcoma receiving standardized care on a cooperative group clinical trial.

Methods

Data sources

Patients enrolled at US COG institutions on AOST0331 (also known as NCI-2009-01066 or European and American Osteosarcoma Study (EURAMOS-1), which opened November 2005 and closed June 2011) were considered for analysis. The analysis was conducted with data current to November 2014—the dataset used for previously published trial analyses (6). Trial design, therapy, and eligibility criteria have been described previously (37-39). Participants received two 5-week cycles of preoperative methotrexate, doxorubicin, and cisplatin (MAP) followed by week 11 surgical resection. Patients who fulfilled criteria for and consented to postsurgical random assignment were offered random assignment to MAP vs MAP with ifosfamide and etoposide for those with no more than 90% tumor necrosis or MAP vs MAP plus pegylated-interferon for those with greater than 90% tumor necrosis. As previously published, neither regimen was superior to MAP alone (2,3). AOST0331 was approved by each local COG institutional review board. Participants provided written informed consent and assent for trial enrollment and future use of data.

Cohort

The analytic cohort included patients with data available for at least 1 proxied poverty exposure measure as defined below. To minimize heterogeneity, the cohort was restricted to patients aged 5 years to younger than 21 years with nonmetastatic disease at enrollment to focus on pediatric outcomes (see Figure 1). Non-US participants were excluded because the primary exposure (see below) was not available.

Figure 1. — Consort diagram of patient selection and outcomes. EFS = event-free survival; IE = ifosfamide and etoposide; IFN = pegylated-interferon; MAP = methotrexate, doxorubicin, and cisplatin; SMN = second malignant neoplasm.

Exposures

Poverty was the primary exposure of interest and was defined at the household and neighborhood level to proxy SDOH that operate differentially at the family and area level (40). Household-poverty exposure was proxied by insurance at time of trial enrollment and dichotomized as sole coverage by means-tested public insurance (Medicaid or Children’s Health Insurance Program) vs private or other insurance (including commercial; dual commercial; and public, military, or other insurers) (41). Patients with public insurance were defined as household-poverty exposed, given that child eligibility for Medicaid insurance is based on low household income for a majority of participants. Neighborhood poverty was proxied by linkage of a child’s 5-digit residential zip code at time of trial enrollment to US Census data from the 2014 American Community Survey 5-year estimates. Zip codes were classified based on US Census definitions as high poverty (>20% of persons living below 100% federal poverty level) vs low poverty (≤20% persons below 100% federal poverty level), an area-based socioeconomic indicator associated with health outcomes that performs equivalently to multidimensional indices (42). Patients living in high-poverty zip codes were defined as neighborhood-poverty exposed.

Outcomes

Overall survival was the primary endpoint of interest and was defined as the time from AOST0331 enrollment until death or last follow-up. A patient who died was considered to have experienced a survival event; otherwise, the patient was considered censored for overall survival at last follow-up. Event-free survival was defined as time from AOST0331 enrollment until first occurrence of disease progression, second malignant neoplasm, death, or last follow-up. A patient who experienced disease progression, second malignant neoplasm, or died was considered to have experienced an event-free survival; otherwise, the patient was considered censored for event-free survival at last follow-up. For any patient who experienced disease progression as an event-free survival, postprogression survival was defined as the time from disease progression until death or last follow-up. A patient who died was considered to have experienced a postprogression survival event; otherwise, the patient was considered censored for postprogression survival at last follow-up. Patients who completed induction chemotherapy and had the primary tumor site resected were considered for histological response as graded by the treating institution. Good histological response was defined as greater than 90% necrosis. Standard histological response was defined as 90% or less tumor necrosis in the resected specimen.

Covariates

Patient and disease characteristics (predictor characteristics) evaluated in the analysis are described in Table 1 and included trial-collected age at diagnosis (categorized per prior EURAMOS-1 publications as child [male: 0-12 years; female: 0-11 years]; adolescent [male: 13-17 years; female: 12-16 years]; and adult [male: 18-20 years; female: 17-20 years]) (6,39), sex (male or female), race, and ethnicity. For each patient, we derived a 4-category race and ethnicity variable as 1) Hispanic (regardless of reported race); 2) non-Hispanic Black; 3) non-Hispanic White; and 4) non-Hispanic Other (includes American Indian and Alaskan Native, Asian, Hawaiian and Pacific Islander) 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 (31,43). Non-Hispanic Other was used as a composite category because of small sample sizes that precluded modeling of individual racial categories (31,43). Histological response and random treatment assignment were not determined at the time of study enrollment and thus were not included in the analysis assessing the relationship between predictor characteristics and risk for event-free survival or death.

Table 1.

Characteristics of study patients by household and neighborhood-poverty exposures

Patient and tumor characteristics	Overall cohort, No. (%)	Household poverty, yes, No. (%) of total	Household poverty, no, No. (%) of total	P across row variable	Neighborhood poverty, yes, No. (%) of total	Neighborhood poverty, no, No. (%) of total	P across row variable
Total	758	194	525		216	536
Patient demographics
Sex, No. (%)
Male	436 (58)	117 (60)	299 (57)		121 (56)	313 (58)
Female	322 (42)	77 (40)	226 (43)	.44	95 (44)	223 (42)	.5686
Age^a at enrollment, No. (%)
Median (IQR)	14 (5)	13 (6)	14 (5)		13 (6)	14 (5)
Child	257 (34)	80 (41)	159 (30)		84 (39)	170 (32)
Adolescent	400 (53)	95(49)	288 (55)		104 (48)	294 (55)
Adult	101 (13)	19 (10)	78 (15)	.0139	28 (13)	72 (13)	.1597
Race and ethnicity,^b No. (%)
Hispanic	158 (21)	68 (35)	80 (15)		73 (34)	84 (16)
Non-Hispanic Black	117 (15)	47 (24)	69 (13)		49 (23)	67 (13)
Non-Hispanic Other	40 (5)	9 (5)	27 (5)		13 (6)	26 (5)
Non-Hispanic White	419 (55)	69 (36)	334 (64)		76 (35)	340 (63)
Missing	24 (3)	1 (1)	15 (3)	<.0001	5 (2)	19 (4)	<.0001
Tumor characteristics
Primary site, No. (%)
Axial	31 (4)	9 (5)	20 (4)		11 (5)	20 (4)
Proximal humerus or femur	96 (13)	38 (20)	52 (10)		26 (12)	68 (13)
Other limb	631 (83)	147 (76)	453 (86)	.0022	179 (83)	448 (84)	.6656
Extent of involved bone, No. (%)
Less than one-third	318 (42)	71 (37)	230 (44)		82 (38)	235 (44)
Greater than one-third	289 (38)	89 (46)	180 (34)		91 (42)	195 (36)
Missing	151 (20)	34 (18)	115 (22)	.0151	43 (20)	106 (20)	.1253
Fracture at diagnosis, No. (%)
Yes	110 (15)	34 (18)	73 (14)		30 (14)	78 (15)
No	642 (85)	157 (81)	449 (86)		185 (86)	453(85)
Missing	6 (1)	3 (2)	3 (1)	.2361	1 (<1)	5 (1)	.9086

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Age categorized as per Smeland et al. (6): child (male: 0-12 years; female: 0-11 years); adolescent (male: 13-17 years; female: 12-16 years); adult (male: 18-20 years; female: 17-20 years). IQR = interquartile range.

Race and ethnicity categorized to highlight historically marginalized populations according to social constructs.

Statistical analysis

For each predictor characteristic, the hypotheses of independence of the characteristic and proxied household poverty, neighborhood poverty, or race and ethnicity were assessed using the exact conditional test of proportions. P values and confidence intervals (CIs) for odds ratios (ORs) were calculated using exact methods (44). Patients with missing values in any particular comparison were excluded from the analysis. Event-free survival and overall survival as a function of time from trial enrollment and postprogression survival as a function of the time from first disease progression were estimated using the Kaplan–Meier method (45). For the 5-year event-free survival and overall survival and the 4-year postprogression survival, 95% confidence intervals were estimated using the complementary log-log method (46). Hypotheses of associations between risks for event-free survival, death, and postprogression survival according to patient and tumor characteristics were assessed using log-rank tests (46). Confidence intervals were derived using the asymptotic distribution of the log-hazard rate coefficient with that characteristic as the only term in the model. For characteristics with 2 categories, we used 0.95 as the confidence coefficient. For characteristics with more than 2 categories, we adjusted the confidence coefficient using the Bonferroni approach (see Table 2 footnote). A multivariable proportional hazards regression model was constructed relating selected predictor characteristics and exposures with risk for event-free survival and death (46). Only participants with nonmissing values for all the candidate predictor variables were included in the multivariable model. A 2-sided P value of less than .05 was considered statistically significant. All analyses were performed in SAS v9.4.

Table 2.

Event-free survival and overall survival adjusted for sex, age, race and ethnicity, tumor site, tumor volume, pathologic fracture, and proxied household and neighborhood poverty^a

		Univariate analyses of outcome (n = 758)				Multivariable analyses of outcome (n= 553)
	No.	Event-free survival HR (CI^b)	P	Overall survival HR (CI^b)	P ^b	Event-free survival HR (CI^b)	P	Overall survival	P ^c
Sex			.1953		.0614		.0964		.0091
Male	758	1.162 (0.925 to 1.460)		1.332 (0.985 to 1.802)		1.248 (0.960 to 1.624)		1.590 (1.116 to 2.267)
Female		1		1		1		1
Age
Child	758	1	.0725	1	.1017	1	.1471	1	.1506
Adolescent		1.212 (0.906 to 1.622)		1.432 (0.975 to 2.105)		1.335 (0.947 to 1.882)		1.478 (0.933 to 2.343)
Adult		1.485 (0.998 to 2.210)		1.386 (0.800 to 2.401)		1.306 (0.802 to 2.126)		1.260 (0.643 to 2.469)
Race and ethnicity
Hispanic		1.072 (0.756 to 1.521)		1.129 (0.705 to 1.806)		1.115 (0.730 to 1.704)		1.239 (0.701 to 2.190)
Non-Hispanic Black		1.061 (0.717 to 1.571)		1.556 (0.972 to 2.490)		1.226 (0.790 to 1.902)		1.823 (1.062 to 3.129)
Non-Hispanic Other		0.928 (0.487 to 1.769)		1.296 (0.604 to 2.781)		1.239 (0.613 to 2.506)		1.699 (0.721 to 4.004)
Non-Hispanic White	734	1	.9325	1	.1490	1	.6678	1	.0536
Tumor site
Other limb	758	1	<.0001	1	<.0001	1	.0209	1	.002
Proximal humerus or femur		1.579 (1.108 to 2.252)		1.731 (1.107 to 2.708)		1.361 (0.891 to 2.078)		1.699 (1.013 to 2.850)00
Axial tumor		2.790 (1.691 to 4.603)		3.520 (1.975 to 6.273)		2.099 (1.22 to 3.925)		2.979 (1.449 to 6.125)
Tumor volume
Less than one-third involved bone	607	1	.0079	1	.0910	1	.062	1	.3311
More than one-third involved bone		1.392 (1.089 to 1.779)		1.320 (0.956 to 1.823)		1.291 (0.988 to 1.688)		1.192 (0.836 to 1.699)
Pathologic fracture
No	752	1	.1807	1	.8408	1	.1032	1	.9964
Yes		1.230 (0.908 to 1.665)		1.044 (0.693 to 1.572)		1.357 (0.950 to 1.938)		0.999 (0.609 to 1.637)
Neighborhood-poverty exposure
No	752	1	.6444	1	.9740	1	.1858	1	.0672
Yes		0.943 (0.733 to 1.212)		1.005 (0.727 to 1.390)		0.810 (0.590 to 1.111)		0.678 (0.443 to 1.039)
Household-poverty exposure
No	719	1	.3074	1	.0738	1	.6303	1	.5821
Yes		1.142 (0.885 to 1.474)		1.341 (0.971 to 1.853)		1.080 (0.790 to 1.477)		1.122 (0.746 to 1.688)

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Patients with missing or unknown values were excluded for analyses. Complete case analysis used for multivariable analysis, no imputation performed. Hazard ratios calculated from proportional hazard regression model, P values from log-rank for univariate, and Wald test for the particular term from the multivariable model with all characteristics included. CI = confidence interval; HR = hazard ratio.

Confidence intervals were calculated using the asymptotic distribution of the term associated with the particular category relative to the baseline category. To account for number of comparisons with the baseline category, the confidence coefficients were adjusted according to the Bonferroni approach: 1) 0.95 for a characteristic with 2 categories; 2) 0.975 for a characteristic with 3 categories; and 3) 0.983 for a characteristic with 4 categories.

P values for the null hypothesis that all relative hazard rate coefficients for the particular characteristic are 1.

Results

Characteristics of study patients

The analytic cohort consisted of 758 eligible patients aged younger than 21 years at trial enrollment with nonmetastatic osteosarcoma and known proxied household- or neighborhood-poverty status (Figure 1). Median follow-up for survival, calculated by the inverse Kaplan–Meier method (47), was 62.3 months. A total of 40 545.3 person-months of follow-up were contributed to the survival analysis. A total of 39 (5.1%) patients were missing household-level data, and 6 (0.8%) patients were missing neighborhood-level data. Among the patients, 194 (25.6%) lived in household poverty, and 216 (28.5%) lived in neighborhood poverty; 89 (11.7%) children were exposed to both household and neighborhood poverty. A total of 158 (20.8%) children were identified as Hispanic, 117 (15.4%) non-Hispanic Black, 40 (5.3%) non-Hispanic Other, and 419 (54.0%) non-Hispanic White. Detailed breakdowns of race and ethnicity per federal Office of Management and Budget guidelines are shown in Supplementary Table 1 (available online). Consistent with US national data, household-poverty exposure differed by age (adult reference, child OR = 2.1, 95% CI = 1.1 to 3.9; adolescent OR = 1.4, 95% CI = 0.76 to 2.5) and race and ethnicity. Specifically, compared with patients identified as non-Hispanic White, those of other race and ethnicities experienced a higher odds of both household-poverty exposure (Hispanic: OR = 4.1, 95% CI = 2.7 to 6.4; non-Hispanic Black: OR = 3.3, 95% CI = 2.0 to 5.3; non-Hispanic Other: OR = 1.6, 95% CI = 0.64 to 3.7) and neighborhood-poverty exposure (Hispanic: OR = 3.9, 95% CI = 2.6 to 5.9; non-Hispanic Black: OR = 3.3, 95% CI = 2.0 to 5.2; non-Hispanic Other: OR = 2.2, 95% CI = 1.0 to 4.8) (Table 1) (27).

There were no statistically significant differences in predictor characteristics by neighborhood-poverty exposure (Table 1). Children exposed to household poverty were more likely to present with large tumors (involving at least one-third of the affected bone) (OR = 1.6, 95% CI = 1.1 to 2.4; P = .015) and proximal humerus or femur tumors (OR = 2.3, 95% CI = 1.4 to 3.6; P = .002) as compared with unexposed children. There were no statistically significant differences in patient or tumor characteristics by race and ethnicity (Supplementary Table 2, available online).

Associations of proxied poverty exposures, race and ethnicity, and disease outcomes

In univariate analyses, neither neighborhood nor household poverty were associated with statistically significant differences in overall survival or event-free survival (Figure 2, Table 2). Race and ethnicity were also not associated with statistically significant differences in overall survival or event-free survival (Figure 2, Table 2). Similarly, neighborhood-poverty exposure, household-poverty exposure, or race or ethnicity were not associated with histologic response (neighborhood-poverty exposure: OR = 0.94, 95% CI = 0.66 to 1.3; household-poverty exposure: OR = 1.0, 95% CI = 0.72 to 1.5; compared with non-Hispanic White race and ethnicity, Hispanic: OR = 1.1, 95% CI = 0.70 to 1.6; non-Hispanic Black: OR =1.1, 95% CI = 0.70 to 1.8; and non-Hispanic Other: OR = 0.91, 95% CI = 0.42 to 2.0).

Figure 2. — Survival among children with osteosarcoma treated on Children’s Oncology Group AOST0331 from 2005 to 2011 at US centers. Data are shown for Kaplan–Meier estimates of event-free survival (EFS) and overall survival (OS) from time of trial enrollment. A) Data for EFS and OS stratified by neighborhood-poverty group. Five-year estimates: EFS no neighborhood poverty = 56.78%, 95% CI = 52.29% to 61.01% vs EFS neighborhood poverty = 62.11%, 95% CI = 55.05% to 68.39%; log-rank test P = .6444; OS no neighborhood poverty = 74.79%, 95% CI = 70.53% to 78.54% vs OS neighborhood poverty = 75%, 95% CI = 68.12% to 80.6%; log-rank test P = .9740). B) Data for EFS and OS stratified by household-poverty group. Five-year estimates (95% CI: EFS no household poverty = 59.51%, 95% CI = 55.03% to 63.70% vs EFS household poverty = 55.87%, 95% CI = 48.15% to 62.90%; log-rank test P = .3074; OS no household poverty = 75.83%, 95% CI = 71.59% to 79.53% vs OS household poverty = 71.60%, 95% CI = 64.05% to 77.84%; log-rank test P = .0738). C) Data for EFS and OS stratified by race and ethnicity group. Five-year estimates (95% CI: EFS non-Hispanic White = 59.50%, 95% CI = 54.49% to 64.14% vs EFS non-Hispanic Black = 56.25%, 95% CI = 45.82% to 65.43% vs EFS non-Hispanic Other = 60.90%, 95% CI = 43.60% to 74.36% vs EFS Hispanic = 58.09%, 95% CI = 49.72% to 65.56%; log-rank test P = .9325; OS non-Hispanic White = 76.95%, 95% CI = 72.23% to 80.96% vs OS non-Hispanic Black = 67.46%, 95% CI = 57.04% to 75.89% vs OS non-Hispanic Other = 72.96%, 95% CI = 55.27% to 84.56% vs OS Hispanic = 74.7%, 95% CI = 66.27% to 81.33%; log-rank test P = .1490).

In multivariable analysis of complete cases (n = 553) (Table 2), neither neighborhood- or household-poverty exposure nor race and ethnicity was associated with overall survival or event-free survival.

Exploratory associations of poverty exposures, race and ethnicity, and postrelapse survival

Of the patients, 290 patients in the analytic cohort experienced disease relapse as the first event-free survival. In exploratory analysis of an observed divergence in survival based on poverty exposure and race and ethnicity at approximately 18 months from time of relapse on Kaplan–Meier curves and nonpairwise comparisons of overall survival (Table 2), statistically significant differences in postrelapse risk of death were observed by race and ethnicity (log-rank P = .0046). Specifically, non-Hispanic Black children experienced the greatest risk of postrelapse death compared with others (Figure 3) (4-year postrelapse survival: 13.0% non-Hispanic Black [95% CI = 3.7% to 28.2%] compared with 35.7% Hispanic [95% CI = 21.4% to 50.2%], 43.8% non-Hispanic Other [95% CI = 11.9% to 72.6%], and 38.9% non-Hispanic White [95% CI = 30.4% to 47.3%]).

Figure 3. — Postrelapse survival among children with osteosarcoma treated on Children’s Oncology Group AOST0331 from 2005 to 2011 at US centers who experienced relapsed disease. A total of 290 patients in the analytic cohort experienced disease relapse as the first event-free survival. Data are shown for Kaplan–Meier estimates of overall survival from time of relapse. A) Data for overall survival stratified by neighborhood-poverty group. Four-year estimates (95% confidence interval [CI]: overall survival no neighborhood poverty = 36.30%, 95% CI = 28.97% to 43.65% vs overall survival neighborhood poverty = 33.54%, 95% CI = 21.97% to 45.51%; log-rank test P = .7140). B) Data for overall survival stratified by household-poverty group. Four-year estimates (95% CI: overall survival no household poverty = 36.83%, 95% CI = 29.30% to 44.36% vs overall survival household poverty = 30.43%, 95% CI = 18.87% to 42.80%; log-rank test P = .1904). C) Data for overall survival stratified by race and ethnicity group. Four-year estimates (95% CI: overall survival non-Hispanic White = 38.90%, 95% CI = 30.44% to 47.26% vs overall survival non-Hispanic Black = 12.96%, 95% CI = 3.68% to 28.23% vs overall survival non-Hispanic Other = 43.75%, 95% CI = 11.87% to 72.57% vs overall survival Hispanic = 35.66%, 95% CI = 21.40% to 50.17%; log-rank test P = .0046).

Discussion

Proxied household- or neighborhood-poverty exposures or race and ethnicity are not associated with disparities in overall survival or event-free survival among US patients with nonmetastatic osteosarcoma receiving clinical trial–directed care at the .05 significance level. That overall survival and event-free survival do not differ by poverty exposures or race and ethnicity suggests standardized care delivery in a clinical trial setting may achieve equity in outcomes for children with nonmetastatic osteosarcoma. These findings stand in contrast to recent evidence of statistically significant trial-based survival disparities in pediatric neuroblastoma (19), Hodgkin lymphoma (20), and acute lymphoblastic leukemia (48).

One possible explanation for this difference is that osteosarcoma—unlike leukemia or neuroblastoma—has seen few changes to the standard of care over past decades, and thus, access to specialized care delivery beyond successful administration of MAP chemotherapy may not improve outcome. Disparities in outcome are more likely to emerge in diseases for which social advantage (eg, education, income, lack of discrimination) facilitates access to more effective disease treatment (including novel therapies at limited institutions) and ability to adhere to complex medical regimens (49). Given that 90% of children will be treated at COG centers (50) highly adept in administering MAP chemotherapy—the standard of care since the 1980s—clinically significant variation in care delivery may not exist for nonmetastatic pediatric osteosarcoma. Consequently, wealth or social privilege cannot translate to improved access to cutting-edge frontline therapy that does not currently exist. Separately, as MAP chemotherapy is administered intravenously, often in an inpatient setting, the well-described risk of nonadherence to oral chemotherapy in pediatric cancers such as leukemia may similarly not exist (51,52). Alternatively, the absence of disparities in frontline osteosarcoma outcomes may reflect the reality that all children receive uniform treatment with MAP chemotherapy given a current inability to identify biologically based risk classification. A yet-to-be identified biological risk factor may theoretically supersede any signal from nonbiological risk factors like SDOH (5,53). Ongoing evaluation of emerging disparities will be warranted as our understanding of osteosarcoma disease biology and subsequent risk-adapted therapies evolve.

Notably, although there were no statistically significant differences in risk of first event or death by proxied poverty exposure or race and ethnicity, we identified a stark disparity in postrelapse survival among those children who experienced disease relapse—with only 13% of non-Hispanic Black children alive 4-years postrelapse compared with nearly 40% of children identified as other race and ethnicities. Inferior postrelapse survival may reflect as yet-to-be identified differences in tumor or host biology, including host immune responses, that require further investigation. Concurrently, this finding raises important questions regarding equity of postrelapse care—an inflection point in care during which variability in access to surgery and radiation as life-prolonging therapies may drive disparate survival. This finding echoes trial-based Hodgkin lymphoma (20) data identifying racial disparities in overall survival driven by differences in postrelapse survival—posited secondary to inferior access to relapse trials. Relapsed osteosarcoma is difficult to treat, and despite multiple early phase trials (54,55), no clear advantage in terms of life-prolongation is seen with chemotherapy. However, aggressive surgical management, especially of pulmonary metastases, is associated with clinically significantly improved disease-free survival (56). Children from historically marginalized populations experience inferior access to care overall because of adverse SDOH, including income poverty, household material hardship (transportation, housing, food, or utility insecurity), lower parental education, and lower health literacy (23,57-61). It is plausible that following completion of frontline clinical trial therapy, non-Hispanic Black children experience delays in relapse diagnosis corresponding to unresectable disease at relapse presentation—data not currently collected as part of standard COG trials. Concurrently, non-Hispanic Black children may be less likely to receive relapse treatment at highly resourced centers capable of aggressive multidisciplinary surgical and supportive care, and this may correspond to an earlier death.

Importantly, differences in access to postrelapse care are amenable to intervention, as evidenced by equitable frontline trial-based outcomes in this population. As such, this identified postrelapse disparity provides an immediate opportunity for interventions to address postrelapse care delivery with a goal of achieving equitable life prolongation. Health equity interventions targeting nonbiological determinants of health (eg, food and transportation insecurities) have been demonstrated feasible (62) and are being investigated for efficacy in improving patient-reported outcomes in upcoming clinical trials. Concurrently, efforts to systematically incorporate family-reported race and ethnicity and SDOH into future osteosarcoma trials alongside data on postrelapse management [eg, referral to Comprehensive Cancer Centers (63,64) or high-volume pediatric centers (65-67), receipt of postrelapse radiation, surgery, or novel therapeutics] are ongoing to inform future interventional research in the postrelapse setting.

There are important limitations to our data. First, we used public insurance to proxy household poverty because of lack of parent-reported data on income or other adverse SDOH. Although a majority of US children qualify for Medicaid and the Children’s Health Insurance Program based on low-household income, we may have misclassified children from low-income homes insured by private or other insurance or conversely wealthier children insured by Medicaid because of disability (68,69). Similarly, our assignment of neighborhood-poverty exposure may have misclassified children as zip codes do not define homogenous area–based populations. Geocoded measures may better correlate with health outcomes (70) but require residential address data not available for this analysis. We lacked data on parent-reported SDOH to more robustly identify household-level exposure to social deprivation (24,71,72). Concurrently, we used trial-collected race and ethnicity data, which may not be self-reported and risk misclassifying children. We identified disparities in postrelapse survival, however, we did not have access to data on burden of disease at relapse or postrelapse therapy with which to explore potential drivers of this finding. We identify overall equity in event-free survival and overall survival among trial-enrolled children with nonmetastatic osteosarcoma but were notably underpowered to perform pairwise comparisons of overall survival for non-Hispanic Black children with children of other race and ethnicity. Further, the small number of events in some patient subgroups precluded detecting moderate-sized effects on risk of event-free survival or death. It is key to recognize that data incontrovertibly demonstrate that adverse SDOH are associated with inferior access to care (67,73), ability to adhere to recommended therapy (51), and increased comorbidities among patients from historically marginalized backgrounds (74-77). Whether adverse SDOH impact other important patient outcomes in osteosarcoma—symptom burden, quality of life, wound healing, and functional limitations—is a question that will require systematic, prospective collection of family-reported SDOH and patient-reported outcome data, including measures of discrimination. Efforts are underway to integrate such data collection into upcoming COG trials, including in osteosarcoma.

Children with nonmetastatic osteosarcoma treated on a frontline COG trial experience equitable overall survival and event-free survival regardless of race and ethnicity or proxied socioeconomic status. Children of non-Hispanic Black race, however, experience statistically significant inferior postrelapse survival compared with others, a sobering reminder of stark inequities in pediatric osteosarcoma outcomes outside of the tightly controlled care delivery of clinical trials. These data demonstrate that equity in upfront outcomes is possible for children with nonmetastatic osteosarcoma and highlight the need to systematically evaluate modifiable SDOH in future trials to inform equity-based interventions across the cancer continuum for the patients we serve.

Supplementary Material

djae103_Supplementary_Data

djae103_supplementary_data.docx^{(23.9KB, docx)}

Acknowledgements

The authors gratefully acknowledge Dr Mark Bernstein’s contributions developing and leading the European and American Osteosarcoma Studies (EURAMOS) collaboration as well as the contributions of Dr Neyssa Marina leading the Children’s Oncology Group component of the clinical trial. We additionally acknowledge the patients and families who contributed to this study.

Preliminary data from this study were presented in part in Oral Abstract form at the 2022 ASCO Annual Meeting.

Contributor Information

Lenka Ilcisin, Department of Pediatric Oncology, Division of Population Sciences, Dana-Farber/Boston Children’s Cancer and Blood Disorders Center, Harvard Medical School, Boston, MA, USA; Department of Surgery, Boston Children’s Hospital, Harvard Medical School, Boston, MA, USA.

Ruxu Han, Children’s Oncology Group, Monrovia, CA, USA.

Mark Krailo, Children’s Oncology Group, Arcadia, CA, USA; Department of Population and Public Health Sciences Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.

David S Shulman, Department of Pediatric Oncology, Division of Population Sciences, Dana-Farber/Boston Children’s Cancer and Blood Disorders Center, Harvard Medical School, Boston, MA, USA.

Brent R Weil, Department of Surgery, Boston Children’s Hospital, Harvard Medical School, Boston, MA, USA.

Christopher B Weldon, Department of Surgery, Boston Children’s Hospital, Harvard Medical School, Boston, MA, USA.

Puja Umaretiya, Department of Pediatrics, University of Texas Southwestern Medical Center, Dallas, TX, USA.

Rahela Aziz-Bose, Department of Pediatric Oncology, Division of Population Sciences, Dana-Farber/Boston Children’s Cancer and Blood Disorders Center, Harvard Medical School, Boston, MA, USA.

Katie A Greenzang, Department of Pediatric Oncology, Division of Population Sciences, Dana-Farber/Boston Children’s Cancer and Blood Disorders Center, Harvard Medical School, Boston, MA, USA.

Richard Gorlick, Division of Pediatrics, University of Texas MD Anderson Cancer Center, Houston, TX, USA.

Damon R Reed, Division of Pediatric Solid Tumors, Memorial Sloan Kettering Cancer Center, New York, NY, USA.

R Lor Randall, Department of Orthopaedic Surgery, University of California Davis Health, Sacramento, CA, USA.

Helen Nadel, Division of Radiology, Lucille Packard Children’s Hospital at Stanford University, Stanford, CA, USA.

Odion Binitie, Department of Surgery, Moffitt Cancer Center, Tampa, FL, USA.

Steven G Dubois, Department of Pediatric Oncology, Division of Population Sciences, Dana-Farber/Boston Children’s Cancer and Blood Disorders Center, Harvard Medical School, Boston, MA, USA.

Katherine A Janeway, Department of Pediatric Oncology, Division of Population Sciences, Dana-Farber/Boston Children’s Cancer and Blood Disorders Center, Harvard Medical School, Boston, MA, USA.

Kira Bona, Department of Pediatric Oncology, Division of Population Sciences, Dana-Farber/Boston Children’s Cancer and Blood Disorders Center, Harvard Medical School, Boston, MA, USA.

Data availability

The merged, deidentified data underlying this article will be shared on reasonable request to the corresponding author in the context of appropriate institutional review board and Children’s Oncology Group approvals.

Author contributions

Lenka Ilcisin, MD, MPH (Conceptualization; Investigation; Writing—original draft; Writing—review & editing), Steven Dubois, MD, MS (Methodology; Writing—review & editing), Odion Binite, MD (Writing—review & editing), Helen Nadel, MD (Investigation; Writing—review & editing), R. Lor Randall, MD (Writing—review & editing), Damon Reed, MD (Investigation; Writing—review & editing), Richard Gorlick, MD (Investigation; Writing—review & editing), Katherine Janeway, MD, MMSc (Investigation; Methodology; Writing—review & editing), Katie A. Greenzang, MD, EdM (Writing—review & editing), Puja Umaretiya, MD, MS (Writing—review & editing), Christopher B. Weldon, MD, PhD (Writing—review & editing), Brent R. Weil, MD, MPH (Writing—review & editing), David S. Shulman, MD (Writing—review & editing), Mark Krailo, PhD (Data curation; Formal analysis; Investigation; Methodology; Project administration; Supervision; Writing—original draft; Writing—review & editing), Ruxu Han, MS (Data curation; Formal analysis; Methodology; Writing—review & editing), Rahela Aziz-Bose, MD, MPH (Writing—review & editing), and Kira Bona, MD, MPH (Conceptualization; Investigation; Methodology; Writing—original draft; Writing—review & editing).

Conflicts of interest

The authors have no conflicts of interest related to this study to disclose. Unrelated to this study, the authors report the following disclosures: SGD has received consulting fees for advisory board participation from Amgen, Bayer, InhibRx, and Jazz and travel expenses from Loxo, Roche, and Salarius. DR reports Data Safety Monitoring Committee work for Springworks and Eisai. MK reports consulting fees for Data Safety Monitoring Committee work for Merck. DS reports consulting for Boehringer Ingelheim and SAB work for Merlin biotech. KJ reports consulting for Ipsen, Illumina and Inhibrx. OB reports consulting for Onkos Surgical. RA, BW, KB, PU, LI, KG, RG, HN, CW and RH report no disclosures.

Funding

The following grants supported trial conduct: National Clinical Trials Network (NCTN) Operations Center Grant U10CA180886; NCTN Statistics & Data Center Grant U10CA180899; St Baldrick’s Foundation.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

djae103_Supplementary_Data

djae103_supplementary_data.docx^{(23.9KB, docx)}

Data Availability Statement

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[djae103-B77] 77. Keegan THM, Li Q, Steele A, et al. Sociodemographic disparities in the occurrence of medical conditions among adolescent and young adult Hodgkin lymphoma survivors. Cancer Causes Control. 2018;29(6):551-561. [DOI] [PMC free article] [PubMed] [Google Scholar]

PERMALINK

Poverty, race, ethnicity, and survival in pediatric nonmetastatic osteosarcoma: a Children’s Oncology Group report

Lenka Ilcisin, MD, MPH

Ruxu Han, MS

Mark Krailo, PhD

David S Shulman, MD

Brent R Weil, MD, MPH

Christopher B Weldon, MD, PhD

Puja Umaretiya, MD, MS

Rahela Aziz-Bose, MD

Katie A Greenzang, MD, EDM

Richard Gorlick, MD

Damon R Reed, MD

R Lor Randall, MD

Helen Nadel, MD

Odion Binitie, MD

Steven G Dubois, MD, MS

Katherine A Janeway, MD, MMSc

Kira Bona, MD, MPH

Roles

Abstract

Background

Methods

Results

Conclusions

Methods

Data sources

Cohort

Figure 1.

Exposures

Outcomes

Covariates

Table 1.

Statistical analysis

Table 2.

Results

Characteristics of study patients

Associations of proxied poverty exposures, race and ethnicity, and disease outcomes

Figure 2.

Exploratory associations of poverty exposures, race and ethnicity, and postrelapse survival

Figure 3.

Discussion

Supplementary Material

Acknowledgements

Contributor Information

Data availability

Author contributions

Conflicts of interest

Funding

References

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

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