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. 2019 Jul 31;478(3):527–536. doi: 10.1097/CORR.0000000000000889

Is There an Association Between Insurance Status and Survival and Treatment of Primary Bone and Extremity Soft-tissue Sarcomas? A SEER Database Study

Anne A Smartt 1, Eugene S Jang 1, Wakenda K Tyler 1,✉
PMCID: PMC7145069  PMID: 31390340

Abstract

Background:

Several recently published population-based studies have highlighted the association between insurance status and survival in patients with various cancers such as breast, head and neck, testicular, and lymphoma [22, 24, 38, 41]. Generally, these studies demonstrate that uninsured patients or those with Medicaid insurance had poorer survival than did those who had non-Medicaid insurance. However, this discrepancy has not been studied in patients with primary bone and extremity soft-tissue sarcomas, a unique oncological population that typically presents late in the disease course and often requires referral and complex treatment at tertiary care centers–issues that health insurance coverage disparities could aggravate.

Questions/purposes

(1) What is the relationship between insurance status and cause-specific mortality? (2) What is the relationship between insurance status and the prevalence of distant metastases? (3) What is the relationship between insurance status and the proportion of limb salvage surgery versus amputation?

Methods

The Surveillance, Epidemiology, and End Results database (SEER) was used to identify a total of 12,008 patients: 4257 patients with primary bone sarcomas and 7751 patients with extremity soft-tissue sarcomas, who were diagnosed and treated between 2007 and 2014. Patients were categorized into one of three insurance groups: insured with non-Medicaid insurance, insured with Medicaid, and uninsured. Patients without information available regarding insurance status were excluded (2.7% [113 patients] with primary bone sarcomas and 3.1% [243 patients] with extremity soft-tissue sarcomas.) The association between insurance status and survival was assessed using a Cox proportional hazards regression analysis adjusted for patient age, sex, race, ethnicity, extent of disease (lymph node and metastatic involvement), tumor grade, tumor size, histology, and primary tumor site.

Results

Patients with primary bone sarcomas with Medicaid insurance had reduced disease-specific survival than did patients with non-Medicaid insurance (hazard ratio 1.3 [95% confidence interval 1.1 to 1.6]; p = 0.003). Patients with extremity soft-tissue sarcomas with Medicaid insurance also had reduced disease-specific survival compared with those with non-Medicaid insurance (HR 1.2 [95% CI 1.0 to 1.5]; p = 0.019). Patients with primary bone sarcomas (relative risk 1.8 [95% CI 1.3 to 2.4]; p < 0.001) and extremity soft-tissue sarcomas (RR 2.4 [95% CI 1.9 to 3.1]; p < 0.001) who had Medicaid insurance were more likely to have distant metastases at the time of diagnosis than those with non-Medicaid insurance. Patients with primary bone sarcomas (RR 1.8 [95% CI 1.4 to 2.1]; p < 0.001), and extremity soft-tissue sarcomas (RR 2.4 [95% CI 1.9 to 3.0]; p < 0.001) that had Medicaid insurance were more likely to undergo amputation than patients with non-Medicaid insurance. Patients with primary bone and extremity soft-tissue sarcomas who were uninsured were not more likely to have distant metastases at the time of diagnosis and did not have a higher proportion of amputation surgery as compared with patients with non-Medicaid insurance. However, uninsured patients with extremity soft-tissue sarcomas still displayed reduction in disease-specific survival (HR 1.6 [95% CI 1.2 to 2.1]; p = 0.001).

Conclusions

Disparities manifested by differences in insurance status were correlated with an increased risk of metastasis at the time of diagnosis, reduced likelihood of treatment with limb salvage procedures, and reduced disease-specific survival in patients with primary bone or extremity soft-tissue sarcomas. Although several potentially confounding variables were controlled for, unmeasured confounding played a role in these results. Future studies should seek to identify what factors drive the finding that substandard insurance status is associated with poorer survival after a cancer diagnosis. Candidate variables might include medical comorbidities, treatment delays, time to first presentation to medical care and time to diagnosis, type of treatment received, distance travelled to treatments and transportation barriers, out-of-pocket payment burden, as well as educational and literacy status. These variables are almost certainly associated with socioeconomic deprivation in a vulnerable patient population, and once identified, treatment can become targeted to address these systemic inequities.

Level of Evidence

Level III, therapeutic study.

Introduction

In 2017, 8.8% of the US population, or 28.5 million people, did not have health insurance at any point during the year [6]. The Affordable Care Act has expanded access to care, primarily through Medicaid expansion [28]. In 2017, Medicaid insurance covered 19.3% of the population (62.5 million people), an increase from 15.8% (48.5 million) in 2010 [6,10]. It is estimated that Medicaid will cover 93 million individuals by 2024 [32]. Therefore, assessing outcomes associated with Medicaid compared with non-Medicaid insurance is of the utmost importance for millions of individuals from disadvantaged communities now gaining access to care.

Previous database studies have highlighted the association between Medicaid insurance status and worse survival outcomes in patients with various forms of cancer [13, 22, 38]. A study of more than 10,200 men with testicular cancer diagnoses showed that patients who were uninsured or on Medicaid were 26% and 62% more likely to have metastatic disease, respectively, than those with private insurance [22]. A similar database study performed by Walker et al. [38] of 474,000 non-elderly patients who were diagnosed with the top 10 most deadly cancers found that those with Medicaid coverage were 44% more likely to die as a result of their disease compared with patients with non-Medicaid insurance.

We wished to investigate the association of insurance status on presentation, treatment, and survival of patients with primary bone and extremity soft-tissue sarcomas. This is a unique oncologic population, as bone and extremity soft-tissue sarcomas are rare events accounting for 1% of all cancer diagnoses and are therefore often overlooked by healthcare professionals [26]. This is a particularly at-risk population susceptible to diagnosis delays because of systemic barriers to care caused by health insurance status. To date, no study has attempted to investigate this association.

Therefore, we asked the following questions about patients with bone and soft-tissue sarcomas of the extremities recorded in the SEER database: (1) What is the relationship between insurance status and cause-specific mortality? (2) What is the relationship between insurance status and the prevalence of distant metastases? (3) What is the relationship between insurance status and the proportion of limb salvage surgery versus amputation?

Patients and Methods

Study Design and Setting

This study is a retrospective database study, and the SEER database (1973-2014) of the National Cancer Institute was the data source. The SEER database collects cancer survival and incidence information from population-based cancer registries, encompassing 26% of the US population [25]. We chose this database because it is useful in the investigation of rare disease (such as sarcomas), providing statistics about diagnosis, treatment and outcome of cancer [40]. We included data from the SEER 18 registry (Incidence – SEER 18 Regs Research data + Hurricane Katrina-impacted Louisiana Cases Nov 2016). We restricted the time period to between January 1, 2007 and December 31, 2014 because the SEER database began collecting information on insurance status in 2007.

Participants

Using the SEER database, we identified 12,008 patients; 4257 patients had primary bone sarcomas at all sites (International Classification of Diseases for Oncology, 3rd Edition histology codes 9180-9269) and 7751 patients had extremity soft-tissue sarcomas (International Classification of Diseases for Oncology, 3rd Edition codes 8000-8119, 8140-8429, 8680-8719, 8800-8999, 9040-9049, 9060-9099, 9120-9169, 9350-9529, and 9540-9589). We excluded from the study patients with no insurance information (2.7% [113] with primary bone sarcomas and 3.1% [243] with extremity soft-tissue sarcomas), resulting in the final sample size of 4144 patients with primary bone sarcoma and 7508 with extremity soft-tissue sarcoma included in our analysis.

Description of Experiment, Treatment, or Surgery

We obtained patient- and treatment-specific variables from the SEER data set and reviewed them to ascertain their correlation with insurance status.

Variables, Outcome Measures, Data Sources, and Bias

The variables collected from the SEER database were age at the time of diagnosis, sex, marital status, insurance status, race, ethnicity, month and year of diagnosis, primary site of tumor, histology, tumor size and extension, lymph node involvement, metastasis at diagnosis, type of surgery, cause of death (cancer or other causes) and survival months. SEER determines the variables race and ethnicity using the highest priority source available, which in order are as follows: the patient’s self-declared identification, documentation in the medical record, and death certificate [2]. Patients were categorized into one of three insurance groups: insured with non-Medicaid insurance, insured with Medicaid, and uninsured. If patients on Medicare had Medicaid eligibility, they were identified as insured with Medicaid, otherwise they were included in the non-Medicaid insurance group. Our primary endpoint was cause-specific mortality, which was documented in the SEER data as “death (attributed to this cancer dx).” Survival time was calculated as the interval in months from the date the primary bone sarcoma or extremity soft-tissue sarcoma was diagnosed to the date of tumor-associated death. Patients were right censored to the date they were last known to be alive or until their death attributed to other diseases.

Demographics, Description of Study Population

In the SEER registries, 4257 patients were recorded as having a primary bone sarcoma at all sites between 2007 and 2014. After excluding patients without provided insurance information (113), we included 4144 patients in our analysis. Within this population, 3.9% [162] were uninsured, 21.3% [884] had Medicaid insurance, and 74.8% [3098] had non-Medicaid insurance. A greater percentage of patients with Medicaid or no insurance were single, black or Hispanic than those with non-Medicaid insurance (Table 1).

Table 1.

Variations in demographics in patients with primary bone sarcoma by insurance status

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In the SEER registries, 7751 patients were recorded as having extremity soft-tissue sarcomas between 2007 and 2014. After excluding patients without provided insurance information (243), we included 7508 patients in our analysis. Within this population, 312 (4%) were uninsured, 904 (12%) had Medicaid insurance, and 6292 (83%) had non-Medicaid insurance. As with patients with primary bone sarcomas, a greater percentage of patients with extremity soft-tissue sarcomas with Medicaid insurance or no insurance were single, black or Hispanic than those with non-Medicaid insurance. (Table 2)

Table 2.

Variations in demographics in patients with extremity soft tissue sarcoma by insurance status

graphic file with name abjs-478-527-g002.jpg

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Statistical Analysis, Study Size

Baseline characteristics are summarized and presented as the number of patients and percentages for categorial variables and the means with SDs for continuous variables. Chi-square statistics were calculated for each variable with respect to the three insurance status categories. Survival analysis was performed using Kaplan-Meier and log-rank tests. The association between insurance status and survival was assessed using a Cox proportional hazards regression that adjusted for patient age; sex; race; ethnicity; extent of disease at presentation (lymph node and metastatic involvement); and tumor grade, size, histology, and primary site. All p values were reported as two-sided, with a level of significance of p < 0.05. The analysis was performed using Stata statistical software (version 15.0; StataCorp LP, College Station, TX, USA).

Results

Relationship Between Insurance Status and Cause-specific Mortality

Our primary endpoint of interest was time to death. Estimates of disease-specific survival for the primary bone sarcoma cohort were calculated using the Kaplan-Meier method (Fig. 1), comparing those with Medicaid insurance, non-Medicaid insurance, and without insurance. A log-rank test comparing the three insurance groups was conducted and there was no evidence found for an association (chi2 = 4.70; p = 0.095). At 45 months, the estimates of survival were 0.76 (95% confidence interval 0.72 to 0.79) for those with Medicaid, 0.81 (95% CI 0.80 to 0.83) for those with non-Medicaid insurance, and 0.85 (95% CI 0.77 to 0.91) for those without insurance. A simple Cox regression model comparing the three insurance groups had an unadjusted hazard ratio of 1.2 (95% CI 1.0 to 1.4; p = 0.065) comparing patients with Medicaid versus non-Medicaid insurance. The unadjusted HR was 0.81 (95% CI 0.53 to 1.26; p = 0.35) comparing patients without insurance versus non-Medicaid. We then fit a multivariable Cox regression model, adjusting for patient and tumor-specific characteristics. The adjusted HR was 1.3 (95% CI 1.1 to 1.6; p = 0.003) for comparing patients with Medicaid versus non-Medicaid insurance, the adjusted HR was 0.8 (95% CI 0.52 to 1.28; p = 0.35) for comparing patients without insurance versus non-Medicaid insurance, and the adjusted HR was 0.61 (95% CI 0.38 to 0.96; p = 0.034) for comparing patients without insurance versus Medicaid.

Fig. 1.

Fig. 1

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The figure shows Kaplan-Meier survival estimates for primary bone sarcomas as a function of insurance status.

We calculated estimates of disease-specific survival for the extremity soft-tissue sarcoma cohort using the Kaplan-Meier method (Fig. 2), comparing those with Medicaid insurance, non-Medicaid insurance, and without insurance. There was evidence for an association between variables using a log-rank test comparing the three insurance groups (chi square = 31.08; p < 0.001). At 60 months, the estimates of survival were 0.70 (95% CI 0.66 to 0.74) for those with Medicaid, 0.80 (95% CI 0.78 to 0.81) for those with non-Medicaid insurance, and 0.74 (95% CI 0.67 to 0.80). A simple Cox regression model comparing the three insurance groups had an unadjusted HR of 1.5 (95% CI 1.3 to 1.8; p < 0.001) comparing patients with Medicaid versus non-Medicaid insurance. The unadjusted HR was 1.3 (95% CI 1.0 to 1.7; p = 0.065) comparing patients without insurance versus non-Medicaid insurance. We then fit the same multivariable Cox regression model, accounting for patient and tumor characteristics. The adjusted HR was 1.1 (95% CI 1.0 to 1.5; p = 0.019) when comparing patients with Medicaid versus non-Medicaid insurance, it was 1.6 (95% CI 1.2 to 2.1; p = 0.001) when comparing patients without insurance versus non-Medicaid insurance, and 1.3 (95% CI 1.0 to 1.8; p = 0.092) when comparing patients without insurance versus Medicaid insurance.

Fig. 2.

Fig. 2

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This figure shows Kaplan-Meier survival estimates for extremity soft-tissue sarcomas as a function of insurance status.

Relationship Between Insurance Status and Distant Metastases

Patients with Medicaid insurance were more likely than patients with non-Medicaid insurance to present with a distant metastasis at the time of diagnosis for both those with primary bone sarcomas (Medicaid, 14% [124 of 884 patients], non-Medicaid, 9% [279 of 3098 patients]; relative risk, 1.7 [95% CI 1.3 to 2.1]; p < 0.001) and extremity soft-tissue sarcomas (Medicaid, 11% [101 of 904 patients], non-Medicaid, 4.9% [309 of 6292 patients]; RR, 2.4 [95% CI 1.9 to 3.1]; p < 0.001). With the numbers we had, we found no association between uninsured status and increased likelihood of presenting with distant metastasis compared with those with non-Medicaid insurance for either primary bone sarcomas (uninsured, 10% [17 of 162 patients]), non-Medicaid, 279 of 3098 [9%]; RR 1.2 [95% CI 0.71 to 2.99]; p = 0.18) or extremity soft-tissue sarcomas (uninsured, 5.8% [18 of 312], non-Medicaid, 4.9% [309 of 6292]; RR, 1.2; 95% CI, 0.73 to 1.93; p = 0.5).

Relationship Between Insurance Status and Limb Salvage Surgery Versus Amputation

Patients with Medicaid insurance were more likely than patients with non-Medicaid insurance to undergo amputation for treatment of primary bone sarcomas (Medicaid, 21% [185 of 884 patients]; non-Medicaid, 13% [407 of 3098 patients]; RR 1.8 [95% CI 1.4 to 2.1]; p < 0.001) and extremity soft-tissue sarcomas (Medicaid, 12% [105 of 904 patients]; non-Medicaid, 5.3% [335 of 6292 patients]; RR 2.4 [95% CI 1.9 to 3.0]; p < 0.001). Uninsured patients were also more likely to undergo amputation surgery than patients with non-Medicaid insurance for the treatment of primary bone sarcomas (uninsured, 19% [31 of 162 patients]; non-Medicaid, 13% [407 of 3098 patients]; RR 1.6 [95% CI 1.1 to 2.3]; p = 0.032). With the numbers we had in the extremity soft-tissue sarcoma cohort, we found no association between uninsured status and an increased likelihood to be treated with amputation surgery than those with non-Medicaid insurance (uninsured, 6.7% [21 of 312 patients]; non-Medicaid, 5.3% [335 of 6292]; RR 1.3 [95% CI 0.81 to 2.03]; p = 0.29).

Discussion

Previous studies have consistently found that insurance status was associated with advanced cancer stage and higher mortality in other cancers [3, 13, 31]. However, they were not specific to the field of orthopaedic oncology, an oncologic population beset even in the best circumstances with delays in diagnosis and therefore uniquely susceptible to systemic barriers that poor health insurance could pose. Therefore, we assessed the association between insurance status and survival among patients with primary bone sarcomas and extremity soft-tissue sarcomas. We found that patients who had Medicaid insurance had an increased risk of distant metastasis at the time of diagnosis, of undergoing amputation instead of limb-salvage surgery, and of reduced cause-specific survival compared with those with non-Medicaid insurance.

Limitations

This study had a number of limitations mainly pertaining to the data set used. SEER does not provide information about when patients first obtained insurance coverage. Studies have shown that patients who enroll in Medicaid around the time of their initial diagnosis are more likely to present with advanced disease and have worse survival than those who have been stably insured by Medicaid before their diagnosis [7, 18]. Therefore, those patients who initially were uninsured and then qualified for Medicaid after their diagnosis may not have been adequately characterized in this data set, effectively attenuating discrepancies that might have existed between the Medicaid and the uninsured group. This is further supported by the fact that the uninsured population included in the study was only 4% of the total sample size, while the overall uninsured rate in the United States in 2017 was 8.8% [6]. This may explain why many differences in outcomes were not observed to be significant when comparing uninsured and non-Medicaid patients.

The SEER dataset was missing other key variables. SEER does not contain information on comorbid physical conditions such as hypertension, heart failure, peripheral arterial disease and angina, or comorbid mental health conditions such as depression and anxiety. This omission is particularly pertinent for this population as patients with soft-tissue sarcomas have been found to be more likely to present with comorbidities at the time of diagnosis than patients who are cancer-free [36]. Comorbidities could affect survival time and treatment options. Our inability to control for comorbidities leaves our analysis open to possible bias. SEER does not further subdivide within their variable “insurance” into the subgroups private, Medicare, or Veterans Affairs insurance. Therefore, we were unable to make specific conclusions about the elderly population insured with Medicare. Additionally, the SEER database does not include information about chemotherapy or radiation rates, which are important cofounders for disease-specific survival and may proportionately differ according to insurance status.

In total, 3% of the total primary bone and extremity soft-tissue sarcomas groups were excluded from statistical analysis because they were missing insurance information. Although there is no established statistical cutoff from the previous reports regarding an acceptable percentage of missing data for valid statistical inference, Schafer et al. [33] asserted that a missing proportion of 5% or less is inconsequential. Therefore, this exclusion is unlikely to have biased the results of our analysis.

What is the Relationship Between Insurance Status and Cause-Specific Mortality?

The results of the current study demonstrate that for primary bone sarcoma and extremity soft-tissue sarcoma, patients with non-Medicaid insurance had longer survival compared with patients with Medicaid insurance. Poorer survival in Medicaid patients may be a result of advanced disease at the time of presentation; however, even after accounting for patient- and tumor-specific factors on multivariable analysis, Medicaid insurance status continued to be associated with a bleaker prognosis. This suggests that there are factors that went unaccounted, such as comorbidities, social support, performance status, socioeconomic and transportation barriers, or education, that may contribute to worse survival for these patients. These observations are consistent with the reported findings that poorer insurance status is associated with poorer survival after a cancer diagnosis [18, 22, 29, 38]. While the focus has largely centered on the survival discrepancies between the uninsured population and those with private insurance, accumulating evidence has suggested that patients with Medicaid coverage only have marginally improved cancer survival compared with those uninsured [7, 24, 38, 41]. One study found that compared with being uninsured, Medicaid insurance was only associated with a modest benefit in cancer survival for patients living in disadvantaged communities but not for those in more advantaged communities [1]. Even with legislation like the Breast and Cervical Cancer Prevention and Treatment Act of 2000, which expanded Medicaid coverage to women diagnosed with breast or cervical cancer through federally funded screening programs, disease-specific survival among patients with breast cancer with Medicaid was similar to those who were uninsured [38].

Several factors can explain this pervasive discrepancy. Medicaid is a safety net program as individuals enroll in the insurance plan upon or after diagnosis with cancer, and these patients are more likely to be diagnosed with an advanced-stage disease than those enrolled in Medicaid before cancer diagnosis [7, 18]. There are wide geographic differences in Medicaid use and expansion, based off of varying qualification levels used by different states [35]. Medicaid patients constitute a socioeconomically disadvantaged subgroup of the general population. Poor survival associated with Medicaid may be a factor of the increased vulnerability of this population as adults enrolled in Medicaid are more likely to be disabled, with multiple physical or psychiatric comorbidities, than those who are not enrolled [18, 29]. Financial barriers remain substantial even when covered with Medicaid insurance; out-of-pocket expenses have been growing faster for those with Medicaid than those with private health insurance—at a rate about twice as fast as their incomes [19]. The association between treatment delays and Medicaid insurance has been demonstrated in other cancer care [20, 24]. For breast cancer patients, Medicaid insurance is associated with a 50% to 60% risk of both adjuvant chemotherapy and surgery delay compared with privately insured patients, and this delay is associated with lower breast cancer survival rates [20]. Treatment delays are particularly salient in this study population as referral of patients with possible sarcomas to specialist care remains poor and often results in delays [12]. Medicaid has played a key role in providing access to care for millions of low-income people for decades [27]. On a global scale, Medicaid has been associated with improved access to care and reduced all-cause mortality [34]. Therefore, further research must be undertaken to explore the survival discrepancy seen in patients with Medicaid insurance with primary bone sarcoma and extremity soft-tissue sarcomas.

What is the Relationship Between Insurance Status and the Prevalence of Distant Metastases?

Patients with Medicaid insurance diagnosed with primary bone sarcomas and extremity soft-tissue sarcomas were more likely to present with distant metastasis at the time of diagnosis than those with non-Medicaid health insurance. Sarcomas are relatively rare tumors, accounting for only 1% of all cancer diagnoses [26]. Delays in diagnosis and treatment are common because there is often a low clinical suspicion of malignancy. Healthcare providers have consistently been found to confer the greatest source of delay of diagnosis of primary bone and extremity soft-tissue sarcomas with a median range of 5.1 months [12] to 7.5 months [4]. In one study, only 4% of the patients with extremity soft-tissue sarcoma and 10% of the patients with primary bone sarcoma were directly referred to a sarcoma unit at first presentation [12]. Prolonged delays (4 months) were seen in reaching specialist care and by this time patients were more likely to have had progression of their tumor size and symptoms [12]. These delays are further exacerbated for patients with Medicaid insurance. Compared with referrals for privately insured patients, referrals for patients with Medicaid insurance to orthopaedic specialists are less likely to result in appointments and are more likely to have long wait times for appointments [5, 11, 15-17, 39]. These systematic barriers for patients with Medicaid insurance must be addressed to reverse the current trend of patients with Medicaid insurance presenting with worse disease progression at time of diagnosis.

What is the Relationship Between Insurance Status and the Proportion of Limb Salvage Surgery Versus Amputation?

In our analysis, we found that patients with Medicaid insurance with primary bone and extremity soft-tissue sarcomas were more likely to undergo amputation surgery as opposed to limb salvage than those with non-Medicaid health insurance. In the past, most sarcomas were treated by limb amputation; however, now most patients with primary bone and extremity soft-tissue sarcomas are treated with limb-salvage procedures [9, 30, 37] because they are associated with better functional outcomes than amputation [14]. Only about 5% of patients with extremity soft-tissue sarcoma are expected to undergo amputation due to anatomic concerns [8]. In our study, a similar proportion of patients with non-Medicaid insurance underwent amputation surgery (5.3%); however, twice as many patients with Medicaid insurance were treated with amputation (12%). Overall in our cohort, patients with Medicaid insurance were more likely than patients with other types of insurance to present to care when their disease was already at a more advanced stage, and this may have influenced the choice of amputation over limb-salvage surgery. However, barriers to healthcare access due to insurance status may also play a role here. Medicaid patients are less likely to receive care at a high-volume hospital equipped to offer complex procedures like limb preservation than Medicare patients [21]. Racial and ethnic disparities have already been identified in the treatment of extremity soft-tissue sarcomas; Martinez et al. [23] found that Hispanic patients had lower rates of limb-sparing surgery relative to white patients.

Conclusions

We observed that differences in insurance status were correlated with metastasis risk at the time of diagnosis, reduced likelihood of treatment with a limb-salvage procedure, and reduced disease-specific survival in patients with primary bone and extremity soft-tissue sarcomas. Although patient demographics and tumor-specific factors were controlled for in the multivariable analysis, there are undoubtedly confounding variables associated with insurance status that influenced these results. Possible contributors are mental and physical comorbidities, educational status and literacy levels, financial burden and out-of-pocket payments, distance travelled to treatment centers and transportation barriers; most correlated with socioeconomic deprivation. Further identification and analysis of socioeconomic disparities in the diagnosis and treatment of primary bone and extremity soft-tissue sarcomas is imperative in the efforts to minimize systemic inequities in patient care.

Acknowledgments

We thank Jimmy Duong for help with statistical analysis.

Footnotes

Each author certifies that neither he or she, nor any member of his or her immediate family, have funding or commercial associations (consultancies, stock ownership, equity interest, patent/licensing arrangements, etc.) that might pose a conflict of interest in connection with the submitted article.

All ICMJE Conflict of Interest Forms for authors and Clinical Orthopaedics and Related Research® editors and board members are on file with the publication and can be viewed on request.

Clinical Orthopaedics and Related Research® neither advocates nor endorses the use of any treatment, drug, or device. Readers are encouraged to always seek additional information, including FDA approval status, of any drug or device before clinical use.

Each author certifies that his or her institution approved the human protocol for this investigation and that all investigations were conducted in conformity with ethical principles of research.

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