Rural patients are at risk for increased stage at presentation and diminished overall survival in osteosarcoma

Barriers to care for musculoskeletal sarcoma patients: a public health perspective

Introduction

This study seeks to investigate the barriers to care that exist for patients presenting with sarcomas of musculoskeletal origin. Understanding the roots of delays in care for patients with musculoskeletal sarcoma is particularly important given the necessity of prompt treatment for oncologic diagnoses. Investigators reviewed relevant studies of publications reporting barriers to care in patients undergoing diagnosis and treatment of musculoskeletal tumors.

Methods

A comprehensive literature search was conducted using Scopus, Embase, Web of Science, and PubMed-MEDLINE. Twenty publications were analyzed, including a total of 114,056 patients.

Results

Four barrier subtypes were identified: Socioeconomic Status, Geographic Location, Healthcare Quality, Sociocultural Factors. Socioeconomic status included access to health insurance and income level. Geographic location included distance traveled by patients, access to referral centers, type of hospital system and resource-challenged environments. Healthcare quality included substandard imaging, access to healthcare resources, and healthcare utilization prior to diagnosis. Sociocultural factors included psychological states, nutrition, education and social support.

Conclusion

After identifying the most significant barriers in this study, we can target specific public health issues within our community that may reduce delays in care. The assessment of barriers to care is an important first step for improving the delivery of oncologic patient care to this patient population.

Socioeconomic disparities in musculoskeletal oncology

Musculoskeletal oncology is a clinical specialty dealing with a diverse population of patients with metastatic bone disease, hematological malignancies with musculoskeletal manifestations, primary bone malignancies and soft tissue sarcomas. There are wide-spread disparities including socioeconomic (SES) and insurance-related disparities reported in the literature. In this review, we'll summarize the disparities surrounding the musculoskeletal oncology.

County Rurality is Associated with Increased Tumor Size and Decreased Survival in Patients with Ewing Sarcoma

Background

Ewing Sarcoma (ES) is an aggressive tumor affecting adolescents and young adults. Prior studies investigated the association between rurality and outcomes, although there is a paucity of literature focusing on ES.

Objective

This study aims to determine whether ES patients in rural areas are subject to adverse outcomes.

Methods

This study utilized the Surveillance, Epidemiology, and End Results (SEER) database. A Poisson regression model was used with controls for race, sex, median county income, and age to determine the association between rurality and tumor size. A multivariate Cox Proportional Hazard Model was utilized, controlling for age, race, gender, income, and tumor size.

Results

There were 868 patients eligible for analysis, with a mean age of 14.14 years. Of these patients, 97 lived in rural counties (11.18%). Metropolitan areas had a 9.50% smaller tumor size (p<0.0001), compared to non-metropolitan counties. Patients of Black race had a 14.32% larger tumor size (p<0.0001), and male sex was associated with a 15.34% larger tumor size (p<0.0001). The Cox Proportional Hazard model estimated that metropolitan areas had a 36% lower risk of death over time, compared to non-metropolitan areas (HR: 0.64, p ≤ 0.04).

Conclusion

Patients in metropolitan areas had a smaller tumor size at time of diagnosis and had a more favorable survival rate for cancer-specific mortality compared to patients residing in rural areas. Further work is needed to examine interventions to reduce this discrepancy and investigate the effect of extremely rural and urban settings and why racial disparities occur.

Is the Number of National Database Research Studies in Musculoskeletal Sarcoma Increasing, and Are These Studies Reliable?

BACKGROUND

Large national databases have become a common source of information on patterns of cancer care in the United States, particularly for low-incidence diseases such as sarcoma. Although aggregating information from many hospitals can achieve statistical power, this may come at a cost when complex variables must be abstracted from the medical record. There is a current lack of understanding of the frequency of use of the Surveillance, Epidemiology, and End Results (SEER) database and the National Cancer Database (NCDB) over the last two decades in musculoskeletal sarcoma research and whether their use tends to produce papers with conflicting findings.

QUESTIONS/PURPOSES

(1) Is the number of published studies using the SEER and NCDB databases in musculoskeletal sarcoma research increasing over time? (2) What are the author, journal, and content characteristics of these studies? (3) Do studies using the SEER and the NCDB databases for similar diagnoses and study questions report concordant or discordant key findings? (4) Are the administrative data reported by our institution to the SEER and the NCDB databases concordant with the data in our longitudinally maintained, physician-run orthopaedic oncology dataset?

METHODS

To answer our first three questions, PubMed was searched from 2001 through 2020 for all studies using the SEER or the NCDB databases to evaluate sarcoma. Studies were excluded from the review if they did not use these databases or studied anatomic locations other than the extremities, nonretroperitoneal pelvis, trunk, chest wall, or spine. To answer our first question, the number of SEER and NCDB studies were counted by year. The publication rate over the 20-year span was assessed with simple linear regression modeling. The difference in the mean number of studies between 5-year intervals (2001-2005, 2006-2010, 2011-2015, 2016-2020) was also assessed with Student t-tests. To answer our second question, we recorded and summarized descriptive data regarding author, journal, and content for these studies. To answer our third question, we grouped all studies by diagnosis, and then identified studies that shared the same diagnosis and a similar major study question with at least one other study. We then categorized study questions (and their associated studies) as having concordant findings, discordant findings, or mixed findings. Proportions of studies with concordant, discordant, or mixed findings were compared. To answer our fourth question, a coding audit was performed assessing the concordance of nationally reported administrative data from our institution with data from our longitudinally maintained, physician-run orthopaedic oncology dataset in a series of patients during the past 3 years. Our orthopaedic oncology dataset is maintained on a weekly basis by the senior author who manually records data directly from the medical record and sarcoma tumor board consensus notes; this dataset served as the gold standard for data comparison. We compared date of birth, surgery date, margin status, tumor size, clinical stage, and adjuvant treatment.

RESULTS

The number of musculoskeletal sarcoma studies using the SEER and the NCDB databases has steadily increased over time in a linear regression model (β = 2.51; p < 0.001). The mean number of studies per year more than tripled during 2016-2020 compared with 2011-2015 (39 versus 13 studies; mean difference 26 ± 11; p = 0.03). Of the 299 studies in total, 56% (168 of 299) have been published since 2018. Nineteen institutions published more than five studies, and the most studies from one institution was 13. Orthopaedic surgeons authored 35% (104 of 299) of studies, and medical oncology journals published 44% (130 of 299). Of the 94 studies (31% of total [94 of 299]) that shared a major study question with at least one other study, 35% (33 of 94) reported discordant key findings, 29% (27 of 94) reported mixed key findings, and 44% (41 of 94) reported concordant key findings. Both concordant and discordant groups included papers on prognostic factors, demographic factors, and treatment strategies. When we compared nationally reported administrative data from our institution with our orthopaedic oncology dataset, we found clinically important discrepancies in adjuvant treatment (19% [15 of 77]), tumor size (21% [16 of 77]), surgery date (23% [18 of 77]), surgical margins (38% [29 of 77]), and clinical stage (77% [59 of 77]).

CONCLUSION

Appropriate use of databases in musculoskeletal cancer research is essential to promote clear interpretation of findings, as almost two-thirds of studies we evaluated that asked similar study questions produced discordant or mixed key findings. Readers should be mindful of the differences in what each database seeks to convey because asking the same questions of different databases may result in different answers depending on what information each database captures. Likewise, differences in how studies determine which patients to include or exclude, how they handle missing data, and what they choose to emphasize may result in different messages getting drawn from large-database studies. Still, given the rarity and heterogeneity of sarcomas, these databases remain particularly useful in musculoskeletal cancer research for nationwide incidence estimations, risk factor/prognostic factor assessment, patient demographic and hospital-level variable assessment, patterns of care over time, and hypothesis generation for future prospective studies.

LEVEL OF EVIDENCE

Level III, therapeutic study.

Geographic Access to High-Volume Care Providers and Survival in Patients with Bone Sarcomas: Nationwide Patterns in the United States

BACKGROUND

Clinical practice guidelines recommend centralized care for patients with bone sarcoma. However, the relationship between the distance that patients travel to obtain care, institutional treatment volume, and survival is unknown.

METHODS

We used the National Cancer Database to examine associations between travel distance and survival among 8,432 patients with bone sarcoma diagnosed from 2004 to 2015. Associations were identified using multivariable Cox regression analyses that controlled for sociodemographic, clinical, and hospital-level factors; subgroup analyses stratified patients by histological diagnosis, tumor stage, and pediatric or adult status.

RESULTS

Mortality risk was lower among patients who traveled ≥50 miles (≥80.5 km) than among patients who traveled ≤10 miles (≤16.1 km) (hazard ratio [HR], 0.69 [95% confidence interval (CI), 0.63 to 0.76]). Among hospital-level factors, facility volume independently affected survival: mortality risk was lower among patients at high-volume facilities (≥20 cases per year) than at low-volume facilities (≤5 cases per year), with an HR of 0.72 (95% CI, 0.66 to 0.80). The proportion of patients who received care at high-volume facilities varied by distance traveled (p < 0.001); it was highest among patients who traveled ≥50 miles (53%) and lower among those who traveled 11 to 49 miles (17.7 to 78.9 km) (32%) or ≤10 miles (18%). Patients who traveled ≥50 miles to a high-volume facility had a lower risk of mortality (HR, 0.65 [95% CI, 0.56 to 0.77]) than those who traveled ≤10 miles to a low-volume facility. In subgroup analyses, this association was evident among patients with all 3 major histological subtypes; those with stage-I, II, and IV tumors; and adults.

CONCLUSIONS

This national study showed that greater travel burden was associated with higher survival rates in adults, a finding attributable to patients traveling to receive care at high-volume facilities. Despite the burdens associated with travel, modification of referral pathways to specialized centers may improve survival for patients with bone sarcoma.

LEVEL OF EVIDENCE

Prognostic Level III . See Instructions for Authors for a complete description of levels of evidence.

How Should We Measure Social Deprivation in Orthopaedic Patients?

BACKGROUND

Social deprivation negatively affects a myriad of physical and behavioral health outcomes. Several measures of social deprivation exist, but it is unclear which measure is best suited to describe patients with orthopaedic conditions.

QUESTIONS/PURPOSES

(1) Which measure of social deprivation, defined as "limited access to society's resources due to poverty, discrimination, or other disadvantage," is most strongly and consistently correlated with patient-reported physical and behavioral health in patients with orthopaedic conditions? (2) Compared with the use of a single measure alone, how much more variability in patient-reported health does the simultaneous use of multiple social deprivation measures capture?

METHODS

Between 2015 and 2017, a total of 79,818 new patient evaluations occurred within the orthopaedic department of a single, large, urban, tertiary-care academic center. Over that period, standardized collection of patient-reported health measures (as described by the Patient-reported Outcomes Measurement Information System [PROMIS]) was implemented in a staged fashion throughout the department. We excluded the 25% (19,926) of patient encounters that did not have associated PROMIS measures reported, which left 75% (59,892) of patient encounters available for analysis in this cross-sectional study of existing medical records. Five markers of social deprivation were collected for each patient: national and state Area Deprivation Index, Medically Underserved Area Status, Rural-Urban Commuting Area code, and insurance classification (private, Medicare, Medicaid, or other). Patient-reported physical and behavioral health was measured via PROMIS computer adaptive test domains, which patients completed as part of standard care before being evaluated by a provider. Adults completed the PROMIS Physical Function version 1.2 or version 2.0, Pain Interference version 1.1, Anxiety version 1.0, and Depression version 1.0. Children ages 5 to 17 years completed the PROMIS Pediatric Mobility version 1.0 or version 2.0, Pain Interference version 1.0 or version 2.0, Upper Extremity version 1.0, and Peer Relationships version 1.0. Age-adjusted partial Pearson correlation coefficients were determined for each social deprivation measure and PROMIS domain. Coefficients of at least 0.1 were considered clinically meaningful for this purpose. Additionally, to determine the percentage of PROMIS score variability that could be attributed to each social deprivation measure, an age-adjusted hierarchical regression analysis was performed for each PROMIS domain, in which social deprivation measures were sequentially added as independent variables. The model coefficients of determination (r2) were compared as social deprivation measures were incrementally added. Improvement of the r2 by at least 10% was considered clinically meaningful.

RESULTS

Insurance classification was the social deprivation measure with the largest (absolute value) age-adjusted correlation coefficient for all adult and pediatric PROMIS physical and behavioral health domains (adults: correlation coefficient 0.40 to 0.43 [95% CI 0.39 to 0.44]; pediatrics: correlation coefficient 0.10 to 0.19 [95% CI 0.08 to 0.21]), followed by national Area Deprivation Index (adults: correlation coefficient 0.18 to 0.22 [95% CI 0.17 to 0.23]; pediatrics: correlation coefficient 0.08 to 0.15 [95% CI 0.06 to 0.17]), followed closely by state Area Deprivation Index. The Medically Underserved Area Status and Rural-Urban Commuting Area code each had correlation coefficients of 0.1 or larger for some PROMIS domains but neither had consistently stronger correlation coefficients than the other. Except for the PROMIS Pediatric Upper Extremity domain, consideration of insurance classification and the national Area Deprivation Index together explained more of the variation in age-adjusted PROMIS scores than the use of insurance classification alone (adults: r2 improvement 32% to 189% [95% CI 0.02 to 0.04]; pediatrics: r2 improvement 56% to 110% [95% CI 0.01 to 0.02]). The addition of the Medically Underserved Area Status, Rural-Urban Commuting Area code, and/or state Area Deprivation Index did not further improve the r2 for any of the PROMIS domains.

CONCLUSION

To capture the most variability due to social deprivation in orthopaedic patients' self-reported physical and behavioral health, insurance classification (categorized as private, Medicare, Medicaid, or other) and national Area Deprivation Index should be included in statistical analyses. If only one measure of social deprivation is preferred, insurance classification or national Area Deprivation Index are reasonable options. Insurance classification may be more readily available, but the national Area Deprivation Index stratifies patients across a wider distribution of values. When conducting clinical outcomes research with social deprivation as a relevant covariate, we encourage researchers to consider accounting for insurance classification and/or national Area Deprivation Index, both of which are freely available and can be obtained from data that are typically collected during routine clinical care.

LEVEL OF EVIDENCE

Level III, therapeutic study.

Associations between geographic residence and US adolescent and young adult cancer stage and survival

BACKGROUND

Multiple studies have indicated that place of residence can influence cancer survival; however, few studies have specifically focused on geographic factors and outcomes in adolescents and young adults (AYAs) with cancer. The objective of this study was to evaluate evidence for geographic disparities in cancer diagnosis stage and overall survival in AYAs and to examine whether stage mediated survival associations.

METHODS

National Cancer Database data on AYAs aged 15 to 39 years who were diagnosed with cancer from 2010 to 2014 were obtained. Residence in Metropolitan (metro), urban, or rural counties at the time of diagnosis was defined using Rural-Urban Continuum Codes. Distance between the patient's residence and the reporting hospital was classified as short (≤2.5 miles), intermediate (>12.5 to <50 miles), or long (≥50 miles). Logistic and Cox proportional hazards regression models were used for analyses.

RESULTS

The stage and survival analyses included 146,418 and 178,688 AYAs, respectively. The odds of a late versus early stage at diagnosis (stages III and IV vs I and II) were 1.16 (95% CI, 1.05-1.29) times greater for AYAs living in rural versus metro counties and 1.20 (95% CI, 1.16-1.25) times greater for AYAs living at long versus short distances to the reporting hospital. The hazard of death was 1.17 (95% CI, 1.05-1.31) and 1.30 (95% CI, 1.25-1.36) times greater for those living in rural versus metro counties, respectively, and for long versus short distances to the reporting hospital, respectively. Disease stage mediated 54% and 31% of the associations between metro, urban, or rural residence and residential distance categories and survival.

CONCLUSIONS

Rural residence and living long distances from the reporting hospital were associated with later stage diagnoses and lower survival in AYAs with cancer. Further research is needed to understand mechanisms.

LAY SUMMARY

Adolescents and young adults (AYAs) with cancer are a vulnerable population because cancer is of low suspicion in this population and may not be diagnosed in a timely manner. The authors evaluated evidence for geographic disparities in cancer stage at diagnosis and survival in the AYA population. The findings indicate that AYAs living in rural versus metropolitan US counties and those living farther from the diagnosis reporting hospital are more likely to be diagnosed at a later cancer stage, when it is generally less treatable, and have lower survival compared with AYAs living in metropolitan counties.

Greater travel distance to specialized facilities is associated with higher survival for patients with soft-tissue sarcoma: US nationwide patterns

Purpose

The survival impact of geographic access to specialized care remains unknown in patients with soft-tissue sarcomas (STS). This study aimed to clarify the association between the patient travel distance and survival outcome and investigate the factors lying behind it.

Methods

A total of 34 528 patients with STS registered in the National Cancer Data Base, diagnosed from 2004–2016, were investigated.

Results

Tumor stage correlated with travel distance: patients with metastatic disease stayed closer to home. However, the type of facility showed greatest variation: 37.0%, 51.0%, 73.5%, and 75.9% of patients with ≤10 miles, 10.1–50 miles, 50.1–100 miles, and >100 miles, respectively (P<0.001), had a sarcoma care at academic/research centers. On a multivariable analysis, reduced mortality risk was associated with longer (versus short) travel distance (>100 miles: HR = 0.877; P = 0.001) and management at academic/research (versus non-academic/research) centers (HR = 0.857; P<0.001). The greatest divergence was seen in patients traveling very long distance (>100 miles) to an academic/research center, with a 26.9% survival benefit (HR = 0.731; P<0.001), compared with those traveling short distance (≤10 miles; 95.4% living in metropolitan area) to a non-academic/research center. There was no significant correlation between travel distance and survival in patients who had care at academic/research centers, whereas a survival benefit of management at academic/research centers was observed in every group of travel distance, regardless of tumor stage.

Conclusions

This national study demonstrated that increased travel distance was associated with superior survival, attributable to a higher proportion of patients receiving sarcoma care at distant academic/research centers. These data support centralized care for STS. Overcoming referral and travel barriers may enable more patients to be treated at specialized centers and may further improve survival rates for patients with STS, even when it imposes an increased travel burden.

Is increased symptom interval associated with advanced stage and poorer outcome? A prospective multicenter study of 220 patients with osteosarcoma around the knee

OBJECTIVE

Osteosarcoma is rare disease and there is a strong controversy about the potential impact of symptom interval on the stage of disease and patients' outcomes. We want to assess whether increased symptom interval (SI) is associated with advanced tumor stage and poor prognosis for patients with osteosarcoma.

METHODS

We analyzed prospectively collected data of 220 patients younger than 40 years who had osteosarcoma around the knee. Symptom interval was analyzed to evaluate its impact on metastases at diagnosis, tumor volume, chemotherapy response and overall survival.

RESULTS

The median of SI was 64.5 (Q1-Q3: 42-88) days. The 5-year overall survival rate for patients with different length of symptom interval (<42 days, 42-64 days, 65-87 days, > = 88 days) were 0.78 (95 %CI: 0.67-0.89), 0.49 (95 %CI: 0.35-0.63), 0.52 (95 %CI:0.39-0.65), and 0.65 (95 %CI:0.53-0.77) respectively(p = 0.013). Nonparametric test showed increased SI was associated with metastases at diagnosis (p = 0.008), but not associated with large tumor volume or poor chemotherapy response. Cox regression mode test showed that patient with increased SI had higher hazard ratio (42-64 days HR: 2.586 (95 %CI:1.360-4.915); 65-87 days, HR: 2.225 (95 %CI:1.170-4.233)) for poor outcomes compared to short SI (<42 days), though it was not significant in multivariate analysis (p = 0.182).

CONCLUSION

Increased SI but not the longest SI is associated with higher incidence of metastases at diagnosis; patients can benefit from an earlier diagnosis in terms of survival.