Comparison of overall survival of adult and pediatric osteosarcoma patients using the National Cancer Database

Comparison of overall survival of adult and pediatric osteosarcoma patients using the National Cancer Database | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Comparison of overall survival of adult and pediatric osteosarcoma patients using the National Cancer Database Ryan Boyland, Saber Amin, Valerie Shostrom, Cheng Zheng, Jenna Allison, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5085447/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 18 Feb, 2025 Read the published version in BMC Cancer → Version 1 posted 4 You are reading this latest preprint version Abstract Background: Differences in overall survival (OS) between children and adult patients diagnosed with osteosarcoma are poorly understood. The objective of this study is to compare the OS of pediatric and adult patients diagnosed with osteosarcoma, identify prognostic factors associated with OS, and explore factors specifically associated with pediatric patients with osteosarcoma using data gathered from the National Cancer Database (NCDB). Methods: Patients >=1 years old and diagnosed with osteosarcoma between 2004 and 2017 were included in the study. Multivariable Cox regression analysis adjusted for gender, race, income, education, place of living, health insurance status, year of diagnosis, stage of cancer, surgery, chemotherapy, radiation therapy (RT), and immunotherapy was used to assess the association of age with the OS of the patients. Results: The analysis included 7,890 patients among whom 2,972 (37.7%) were between 1-17 years old. In the multivariable Cox regression analysis, adult patients had worse OS compared with pediatric patients (HR: 1.90; p<.01). When stratified by treatment type, pediatric patients had better OS in several groups. This includes those who received chemotherapy alone (HR: 0.58, p < .01), surgery alone (HR: 0.48, p < .01), surgery plus chemotherapy (HR: 0.55, p < .01), and those who received no treatment (HR: 0.25, p < .01). There was no significant difference in OS between pediatric and adult patients receiving a combination of chemotherapy, surgery, and RT (HR: 0.66, p = 0.11). In analysis stratified by cancer stage, pediatric patients had better OS compared to adult patients at each stage. Multivariable logistic regression analysis revealed that pediatric patients are more likely to be non-white, have insurance, present with unknown/occult stage disease, have poorly differentiated tumors, and receive immunotherapy, chemotherapy, or surgery. Additionally, multivariable Cox regression analysis identified factors associated with improved OS: age, diagnosis between 2011-2015, private insurance, non-metastatic disease, well-differentiated tumors, and receiving chemotherapy or surgery, but not RT. Conclusion: Pediatric patients diagnosed with osteosarcoma had better OS compared to their adult counterparts. Pediatric patients had better OS compared to adults when the analysis was stratified by treatment modality and stage of cancer. More research is necessary to delineate the underlying reason for this difference. osteosarcoma pediatric hazard ratio overall survival odds ratio Figures Figure 1 Figure 2 Figure 3 Background Osteosarcoma is the most common malignant primary bone tumor accounting for more than 50% of the primary bone tumors. It mainly affects children and adolescent, with individuals between the ages of 15 and 25 accounting for 55% of cases, 30% of cases occurring in individuals over the age of 40, and 10% being over the age of 60. 1 , 2 . Osteosarcoma is the sixth most common malignancy in both children aged 0–14 and those aged 15-19. 3 Approximately 70% of osteosarcoma cases occur in patients under the age of 18. 4 The five-year survival rate for early-stage osteosarcoma for all ages is 74% followed by 66% for locally advanced, and 27% for metastatic disease. The survival rate of osteosarcoma is inversely correlated with age at diagnosis with pediatric patients having a five-year survival rate of 78% and elderly patients having only a 25% five-year survival rate. Surgical resection with neoadjuvant and adjuvant chemotherapy is the mainstay of treatment for osteosarcoma. Methotrexate, doxorubicin, and cisplatin are the recommended chemotherapeutic agents. 5 , 6 After the introduction of multi-agent chemotherapy a few decades ago, the five-year survival rate of osteosarcoma improved from 20–60%. However, since then the survival rates remained unchanged despite advancement in cancer treatments and multiple attempts to refine various treatment regimens. Overall survival (OS) depends on various demographic, tumor, and treatment related factors, which include age at diagnosis, metastases at the time of diagnosis, tumor size, tumor location, response to chemotherapy, and time to treatment initiation. 7 The difference in OS between children and elderly patients is poorly understood. Correlations between more malignant variants of osteosarcoma and age have been demonstrated, 7 and data demonstrating a correlation between earlier presentations of disease and more aggressive forms of disease suggest that time to diagnosis might also be a significant prognostic factor. 8 In children vs young adult populations, age was found to be most important because of its correlation with risk of relapse, but it was not further associated with histologic response, or metastatic disease at presentation 4 . Prior research has suggested that age be the most important prognostic factor when considering outcomes from osteosarcoma, 4 , 9 , 10 but the literature is limited by small sample size especially in adults. The objective of the current study is to compare the OS of children and adolescents with the OS of adult patients diagnosed with osteosarcoma and determine the prognostic factors associated with OS using the National Cancer Database. We will also explore factors associated with pediatric patients with osteosarcoma. Methods Data source Data for the current study were extracted from the NCDB, a nationwide oncology outcomes database for more than 1500 Commission accredited cancer programs in the United States and Puerto Rico. The NCDB captures more than 70% of the cancer cases diagnosed in the United States annually. NCDB is a joint project of the Commission on Cancer (CoC) of the American College of Surgeons and the American Cancer Society. The CoC's NCDB and the hospitals participating in the CoC’s NCDB are the source of the de-identified data used herein; they have not verified and are not responsible for the statistical validity of the data analysis or the conclusions derived by the authors. The study was exempt from Institutional board review as the data is de-identified. Informed consent was also not required. Study population Patient >=1 years old diagnosed with osteosarcoma between 2004 and 2017 were included in the study. The primary end point was OS, which was measured in months from the date of diagnosis to death. Patients who were alive at last follow-up or were lost to follow-up were censored. Age at diagnosis was the main variable as a predictor of OS. Other covariates included sex, race, income, education, place of residence, health insurance type, year of cancer diagnosis, surgery, chemotherapy, radiation therapy (RT), immunotherapy, and cancer stage. For population in the city of diagnosis (urban/rural) patients, the following subcategories were used: >=1 million =10.9% without a high school diploma, surrounding population with <=10.8% without a high school diploma. For income, the following subcategories were used: median income $50,354. For patient insurance, the following subcategories were used: Not insured/unknown; Medicaid/Medicare/Other government insurance and Private/managed care. For treatment modality, patients were divided into categories based on whether they underwent any surgery chemotherapy. Patients were then subdivided into further categories depending on combination of treatment modality, for example, chemotherapy/surgery/radiation, chemotherapy/surgery alone, chemotherapy/radiation alone, chemotherapy alone, surgery/radiation alone, surgery alone, radiation alone, and no treatment. Statistical analysis Descriptive statistics for categorical and continuous variables were reported by children (1-17 years) and adult (18=> years). We performed multivariable logistic regression analysis to determine the factors associated with adults with osteosarcoma when compared to pediatric. Odds ratio was reported as a measure of association with the covariate of interest and being an adult with osteosarcoma. Kaplan-Meier analysis was used to report OS and log-rank test was used to compare OS between children and adult. Multivariable Cox regression analysis was used to report the hazard ratio (HR) and its 95% confidence interval (CI) for the factors associated with OS. A P-value of 0.05 was used for a significant level, which was based on 2-sided tests. The SAS 9.4 software was used for the analyses in the current study. Data with missing subject’s age were removed. For other missing data, such as population of the subject’s city or level of education, a separate category for that specific categorical variable was created (for example, “missing”), and the data analysis was conducted with their data included as such. Results Patient Characteristics The final analysis included 7,890 patients among whom 2,972 (37.7%) were between the ages of 1-17 years old and 4,918 (62.3%) were adult (defined as age greater than or equal to 18 years at the time of diagnosis). The proportion of most variables by age was similar between the two groups. However, 1809 (61%) of the pediatric patients had private insurance compared to 2705 (55%) of adults having private insurance. About 2544 (86%) of the pediatric patients received surgery compared to 3888 (79%) of adult patients. Approximately 2809 (95%) of the pediatric patients received chemotherapy, while only 3611 (73%) of the adult patients received chemotherapy. More pediatric patients (2409 (81%)) received surgery plus chemotherapy compared to 2659 (54%) of adult patients. Further details regarding population characteristics and subcategories can be found in Table 1. In the univariable logistic regression analysis, white race, missing median income, lack of insurance/unknown insurance, and receiving radiation were associated with a statistically significant increase in OR for adult patients, while rural location (population <1 million), private/managed care, unknown/occult stage of cancer at diagnosis, poorly differentiated tumor, and treatment modality (involving immunotherapy, surgery, or chemotherapy without radiation) were associated with being diagnosed with osteosarcoma at pediatric age. In the multivariable logistic regression analysis, white race, lack of insurance/unknown insurance, and radiation as part of their treatment modality was associated with greater OR for an adult patient, while unknown/occult stage of cancer at diagnosis, poorly differentiated tumor, and treatment modality (involving immunotherapy, surgery, or chemotherapy without radiation) were positively associated with being diagnosed at pediatric age (p<.01), as demonstrated in Table 1 . Overall Survival Comparison Pediatric patients had better OS compared to adult patients. The median survival was unreached for pediatric patients and 69 months for adults. The 5-year OS rates were 69.2% for pediatric patients and 51.6% for adults, while the 10-year OS rates were 63.5% and 44.0%, respectively (p=18 years old had a worse OS compared to patients diagnosed 1-17 years old (HR: 1.90; 95% CI: 1.76, 2.05; p<.01). In the multivariable Cox regression analysis ( Table 2 ) adjusted for sex, race, income, education, place of residence, insurance status, stage, grade, chemotherapy, surgery, RT, immunotherapy, and year of diagnosis, adult patients had worse OS compared to pediatric patients, making age a significant factor in prognosis (HR: 1.90; 95%; CI: 1.75, 2.05; p<.01). Other factors associated with worse OS were higher stage at diagnosis (Stage 4: HR 3.40; 95% CI: 3.12, 3.71; p<.01), poor differentiation (HR 2.89; 95% CI: 2.40, 3.48; p<.01), and RT (HR 1.46; 95% CI: 1.31, 1.63; p<.01). Notably, factors associated with improved OS were year of diagnosis between 2011 and 2015 when compared to 2004-2010 (HR: 0.84; 95% CI: 0.78, 0.91, p<.01), as well as either being uninsured/possessing unknown insurance or private insurance, when compared with Medicaid/Medicare/Other Government Insurance being associated with greater OS (HR: 0.70; 95% CI: 0.62, 0.79; p<.01 AND HR: 0.77; 95% CI: 0.71, 0.82; p<.01 respectively). With respect to treatment modality, regimens involving surgery, as well as regimens involving chemotherapy were both associated with increased OS (HR: 0.46; 95% CI: 0.42, 0.49; p <.01 AND HR: 0.73 95% CI: 0.66, 0.80; p <.01, respectively). Subset Analysis We further explored the improved OS associated with being diagnosed with osteosarcoma at pediatric age by performing analyses stratified by treatment type and stage of the cancer. Among patients who received only chemotherapy, pediatric patients had better OS compared to adult patients (HR: 0.58; 95% CI: 0.48, 0.71; p < .01). Among patients who only received surgery (HR: 0.48; 95% CI: 0.32, 0.74; p < .01) or surgery plus chemotherapy (HR: 0.55; 95% CI: 0.50, 0.61; p < .01), pediatric patients had higher OS compared to adult patients. There was no difference in the OS of pediatric patients and adult patients among those who received chemotherapy, plus surgery plus RT (HR: 0.66; 95% CI: 0.39, 1.11; p = 0.11) (Table 3). Also, among those who received no treatment, pediatric patients had better OS compared to adult patients (HR: 0.25; 95% CI: 0.14, 0.42; p <.01) (Figure 3). In the analyses stratified by stage of cancer, pediatric patients had better OS compared to adult patients in stage I, stage II/III, and stage IV cancer ( Table 3 and Figure 2 ). Discussion The bimodal distribution of incidence of osteosarcoma is well-studied and well-cited, as is the increased overall survival for pediatric patients relative to adult patients. 10 This study shows that pediatric patients with osteosarcoma have lower mortality rates compared to adult patients, even though pediatric cases are often associated with a poorly differentiated grade. This reduced mortality in pediatric patients is consistent across all stages and treatment modalities, except for radiation therapy. A thorough review of the literature shows an absence of a broad assessment comparing prognostic factors for osteosarcoma among different age groups. One of the more notable studies that attempted what we did here highlighted differences among five different age groups, collecting data from 1973-2004 10 . Mirabello et al (2009) described risk factors for osteosarcoma among five age cohorts; among them, race was noted to be statistically significant. Here, we found that, while white race was associated with a greater likelihood of the patient being diagnosed as an adult, it was not associated with a statistically significant difference in overall survival as a factor alone when comparing adults and pediatric patients. In this study, we found that factors such as later stage at diagnosis, poorly differentiated tumor, and presence of radiation as part of the treatment modality were associated with reduced overall survival for adults relative to pediatric patients, indicating that factors such as socioeconomic status or racial background broadly were less likely to be indicative of overall prognosis. We did not, however, explore specific racial or ethnic backgrounds (here, we examined simply white vs non-white) and how those details may have an impact on survival of adults compared to pediatric patients. We also did not assess specifically how factors such as race relate to socioeconomic background, insurance status, or whether it was associated with any delay in diagnosis. Other studies exploring the factors that could be responsible for worse OS in the adult population include Janeway et al (2012), examined differences in overall survival in patients with high-grade osteosarcoma of any site, and argued that the difference in event-free survival and overall survival was in the setting of increased rate of relapse for adult ( > = 18 years) relative to pediatric patients 4 . Their paper found decreased overall survival for adult population, as was the case in this paper, but argued that the difference in survival was not explained by tumor location, histologic response, or metastatic disease. Our data, however, found that there was decreased overall survival for stage IV malignancy as determined at diagnosis. This discrepancy may be in part due to the different population subsets used in their paper, as well as the much larger data set size in our study, reducing the likelihood of type B error. Some reasons that older patients diagnosed with osteosarcoma have poor OS are that older patients are more likely to not tolerate chemotherapy and more likely to have higher number of secondary osteosarcomas. The location of osteosarcoma is another important factor that is considered to play a role in the poor OS of older patients as they are more likely to have axial osteosarcoma, which we do not address here. 11 In previously published literature, difference in survival was also argued to be associated with unusual locations, abnormal radiological findings, and poor response to chemotherapy 12 . Here, we do not examine discrepancies in tumor location and, as a result, difficulty with surgery. We do, however, examine general trends in differences in tumor stage, grade, and treatment modality. In addition, the small number of patients used in the Jeon et al (2006) study, alongside their use of patients at a single institution limit external validity of their results. Patients included in our data set who were treated with chemotherapy, surgery, or chemotherapy plus surgery were associated with lower hazard ratio for pediatric relative to adult populations, providing support to the argument that differences in treatment decisions between the different populations is not the main factor contributing to differences in outcomes. The argument that adults may be afflicted with more aggressive tumors, or tumors found at a later stage would follow logically in the Jeon et al (2006) paper given the tissue responsiveness to chemotherapy and the reported grade among their patients, but this effect was not replicated in our data, in which the odds ratio suggested that more poorly differentiated tumors/occult tumors were more likely in pediatric populations, and that tumor stage at diagnosis did not significantly change the odds ratio between adults and pediatric populations, suggesting adults and pediatric patients have similar stage distribution. The fact that the chemotherapy, surgery, and radiation (C + S + R) treatment modality was not associated with significant differences in outcome between pediatrics and adults may be in part due to severity of disease necessitating more aggressive therapy, and more data may be needed to better elucidate a difference. There is also an argument that chemotherapy regimens are better tolerated in pediatric rather than adult populations 13 . This evidence is both anecdotal and supported by objective data of adverse outcomes associated with more common treatment regimens involving cisplatin, methotrexate, and doxorubicin. This difference is difficult to delineate in our data, where, while there is data that suggests that chemotherapy is more likely to be implemented in pediatric patients, with an associated improved survival in pediatric patients, but chemotherapy regimens, duration of chemotherapy and tolerability of chemotherapy were not part of our analysis. Regarding the notion that differences in survival are related to tumor location and difficulty with surgery, this is represented in the data with previous studies showing worse prognosis with axial -related tumors, and an increased frequency of axial osteosarcoma in adult patients 14 , 15 , however, the effect in the difference in outcome is inconsistent, and other data suggests that location (axial vs extra-axial) had no impact on survival for patients achieving surgical remission. 15 , 16 Overall, the difference in survival between adult and pediatric patients afflicted with osteosarcoma is likely multifactorial, with many factors at play potentially including histological findings conveying more resistance to treatment, surgical site, and other factors mentioned above, but the exact mechanism requires more study. Furthermore, this study revealed that pediatric patients with osteosarcoma are more likely to receive chemotherapy, surgery, and immunotherapy, while adult patients are more likely to receive RT. This treatment disparity could be one reason for the improved OS observed in pediatric patients. Pediatric patients often participate in Children's Oncology Group (COG) trials, which increases their chances of receiving comprehensive treatments such as chemotherapy, surgery, and immunotherapy, contributing to their better OS. On the other hand, RT in adults is frequently associated with palliative care, which correlates with poorer OS. Interestingly, the ongoing COG osteosarcoma trial AOST2032 has incorporated high dose definitive radiation therapy into the initial definitive therapy regimen. This inclusion may alter the current understanding of radiation therapy's impact on osteosarcoma outcomes in the future. Importantly, given the pace of medical innovation and the advent of new chemotherapy drugs and treatment regimens to better treat osteosarcoma, it is necessary to continually reevaluate our understanding of prognostic indicators. Within those researchers’ study, they noted significant improvement in survival amongst all age groups from 1973-83 and 1984-93, coinciding with the implementation of multiagent chemotherapy regimens 14 . There are ongoing collaborative discussions regarding more streamlined, efficacious therapies, with both the NCCN and ESMO continually updating their guidelines and recommendations to match the significant technologic advances in the field 17 – 19 . With the popularization of more targeted therapies, such as tyrosine kinase inhibitors, in the past two decades, survival rates for all cancers have improved 20 , 21 . By monitoring these prognostic factors over time, we can identify groups of people who, while treatments overall are improving survival outcomes, may be left behind relative to their peers. Limitations of this study include retrospective in nature, study period selected, study groups chosen, and limited information regarding precise treatment regimens, incomplete data, and ascertainment bias. Further research would be beneficial to describe how different interventions or diagnostic studies would be influential in improving the prognoses of the various study groups. Nevertheless, our study is the largest study that investigated the factors associated with being diagnosed at age < 18 years and explored the difference in the OS of adult and pediatric patients diagnosed with osteosarcoma. Conclusions In this comprehensive analysis of the NCDB, we found that adult patients diagnosed with osteosarcoma had worse OS compared with pediatric patients. This reduced mortality in pediatric patients is consistent across all stages and treatment plans. Pediatric patients are more likely to be non-white, have insurance, present with unknown or occult stage disease, have poorly differentiated tumors, and receive immunotherapy, chemotherapy, or surgery, but not radiation therapy. Additionally, prognostic factors associated with improved OS include pediatric status, diagnosis between 2011–2015, having private insurance or managed care, non-metastatic disease, well-differentiated tumors, and receiving chemotherapy or surgery, but not radiation therapy. More research will be necessary to delineate the underlying reason for this difference. Abbreviations Overall Survival (OS), National Cancer Database (NCDB), Hazard Ratio (HR), Odds Ratio (OR), Commission on Cancer (CoC), Confidence Interval (CI), Radiation Thearpy (RT) Declarations Ethics approval and consent to participate: Not Applicable Consent for publication: Not Applicable Competing Interests: VS owns stock in Pfizer. CL has received an NIH grant to support a rectal cancer trial and is currently performing two trials that use a drug developed by BioMimetix. All other authors declare that they have no competing interests. Funding: Not Applicable Author Contribution RB, CL, SA wrote and edited the manuscript text and abstract.RB assisted with creating figures 2-3.VS performed statistical analysis, data collection, and table 1-3 and figure 1 creation.JA assisted with editing the manuscript, project initiation, and the discussion section. CZ assisted with project initiation and editing the manuscript. 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Osteosarcoma: Current Treatment and a Collaborative Pathway to Success. J Clin Oncol Off J Am Soc Clin Oncol. 2015;33(27):3029–35. 10.1200/JCO.2014.59.4895 . Iqbal N, Iqbal N. Imatinib: a breakthrough of targeted therapy in cancer. Chemother Res Pract. 2014;2014:357027. 10.1155/2014/357027 . Tables Table 1: Logistic Regression Analysis of the Factors Associated with Adult vs. pediatric Patients with Osteosarcoma. Variable Age group* Univariable OR (95% CI)* P-value Multivariable OR (95% CI)* P-value 1-17 N=2972 >=18 N=4918 Sex Male Female 1687 (57%) 1285 (43%) 2781 (57%) 2137 (43%) 0.991 (0.904, 1.087) Reference 0.8514 Race White Non-white 2173 (73%) 799 (27%) 3804 (77%) 1114 (23%) 1.26 (1.13, 1.40) Reference <.01 1.28 (1.14, 1.43) Reference <.01 Year of diagnosis 2004-2010 2011-2015 2016 2017 1470 (49%) 1087 (37%) 198 (7%) 217 (7%) 2369 (48%) 1760 (36%) 379 (8%) 410 (8%) Reference 1.01 (0.91, 1.11) 1.19 (0.99, 1.43) 1.17 (0.98, 1.40) 0.10 Urban/rural >=1 million <1 million missing 1431 (48%) 1400 (47%) 141 (5%) 2516 (51%) 2154 (44%) 248 (5%) Reference 0.88 (0.80, 0.96) 1.00 (0.81, 1.24) 0.02 =10.9% <=10.8% Missing 1391 (47%) 1320 (44%) 261 (9%) 2232 (45%) 2207 (45%) 479 (10%) Reference 1.04 (0.95, 1.15) 1.14 (0.97, 1.35) 0.26 Median income =50354 Missing 1161 (39%) 1546 (52%) 265 (9%) 1922 (39%) 2506 (51%) 490 (10%) Reference 0.98 (0.89, 1.08) 1.12 (0.95, 1.32) 0.28 Insurance Not insured/unknown Medicaid/Medicare/other gov Private/managed care 186 (6%) 977 (33%) 1809 (61%) 548 (11%) 1665 (34%) 2705 (55%) 1.73 (1.44, 2.08) Reference 0.88 (0.80, 0.97) <.01 <.01 0.01 1.87 (1.54, 2.27) Reference 0.97 (0.87, 1.08) <.01 <.01 0.61 Stage I/II/III IV NA/UNK/Occult 1859 (63%) 434 (15%) 679 (23%) 3219 (65%) 791 (16%) 908 (18%) Reference 1.05 (0.92, 1.20) 0.77 (0.69, 0.87) <.01 0.44 <.01 Reference 1.00 (0.87, 1.15) 0.61 (0.41, 0.67) <.01 0.98 <.01 Grade Well/moderately differentiated Poor/Undifferentiated NA 95 (3%) 2007 (68%) 870 (29%) 490 (10%) 3194 (65%) 1234 (25%) Reference 0.31 (0.25, 0.39) 0.28 (0.22, 0.35) <.01 <.01 <.01 Reference 0.53 (0.41, 0.67) 0.44 (0.34, 0.56) <.01 <.01 <.01 Immunotherapy Yes No 29 (1%) 2943 (99%) 18 (0.4%) 4900 (99.6%) 0.37 (0.21, 0.67) Reference <.01 0.38 (0.20, 0.72) Reference 0.0031 Surgery Yes No 2544 (86%) 428 (14%) 3888 (79%) 1030 (21%) 0.64 (0.56, 0.72) Reference <.01 0.70 (0.61, 0.80) Reference <.01 Chemotherapy Yes No 2809 (95%) 163 (5%) 3611 (73%) 1307 (27%) 0.16 (0.14, 0.19) Reference <.01 0.18 (0.15, 0.22) Reference <.01 Radiation Yes No 64 (2%) 2908 (98%) 580 (12%) 4338 (88%) 6.08 (4.67, 7.90) Reference <.01 5.07 (3.87, 6.64) Reference <.01 Chemo/surgery/radiation CSR CS C CR SR S R None 37 (1%) 2409 (81%) 337 (11%) 26 (1%) 1 (.03%) 97 (3%) 0 (0%) 65 (2%) 245 (5%) 2659 (54%) 609 (12%) 98 (2%) 176 (4%) 808 (16%) 61 (1%) 262 (5%) *Predicting age>=18; All terms put in multivariable model (except CSR variable); backward selection applied to arrive at final model; C=Chemotherapy; S=Surgery; R=Radiation; CS=Chemotherapy and Surgery; CSR=Chemotherapy, Surgery, and Radiation; CR=Chemotherapy and Radiation; SR=Surgery and Radiation Table 2: Univariable and Multivariable Cox Proportional Regression Analysis of Factors Associated With Overall Survival. Variable Univariable HR (95% CI) P-value Multivariable HR (95% CI) P-value Age 1-17 18+ Reference 1.90 (1.76, 2.05) <.01 Reference 1.90 (1.75, 2.05) <.01 Race White Not white Reference 0.98 (0.90, 1.06) 0.61 Year of diagnosis 2004-2010 2011-2015 2016 2017 Reference 0.87 (0.80, 094) 0.96 (0.82, 1.12) 1.14 (0.97, 1.33) <0.01 <0.01 0.56 0.11 Reference 0.84 (0.78, 0.91) 0.86 (0.74, 1.01) 1.07 (0.91, 1.25) <.01 =1 million <1 million Missing Reference 1.06 (0.99, 1.13) 0.73 (0.61, 0.88) <.01 0.12 =10.9% <=10.8% Missing Reference 0.92 (0.85, 0.98) 0.46 (0.40, 0.54) <.01 .01 <.01 Reference 0.97 (0.90, 1.04) 0.52 (0.44, 0.61) <.01 0.41 <.01 Median income =50354 Missing Reference 0.92 (0.86, 0.99) 0.47 (0.40, 0.55) <.01 .02 <.01 Insurance Not insured/unknown Medicaid/Medicare/other gov Private/managed care 0.86 (0.76, 0.97) Reference 0.69 (0.64, 0.74) <.01 .01 <.01 0.70 (0.62, 0.79) Reference 0.77 (0.71, 0.82) <.01 <.01 <.01 Stage I/II/III IV NA/UNK/Occult Reference 3.91 (3.60, 4.24) 1.34 (1.23, 1.47) <.01 <.01 <.01 Reference 3.40 (3.12, 3.71) 1.18 (1.07, 1.30) <.01 <.01 <.01 Grade Well/moderately diff. Poor/undiff. NA Reference 2.45 (2.05, 2.94) 2.50 (2.07, 3.01) <.01 <.01 <.01 Reference 2.89 (2.40, 3.48) 2.47 (2.04, 3.00) <.01 <.01 <.01 Immunotherapy Yes No 1.40 (0.950, 2.05) Reference 0.09 Surgery Yes No 0.35 (0.32, 0.38) Reference <.01 0.46 (0.42, 0.49) Reference <.01 Chemotherapy Yes No 0.75 (0.69, 0.81) Reference <.01 0.73 (0.66, 0.80) Reference <.01 Radiation Yes No 2.08 (1.88, 2.31) Reference <.01 1.46 (1.31, 1.63) Reference <.01 All terms put in multivariable model (except CSR variable); backward selection (p<0.05) applied to arrive at final model. HR=Hazard Ratio; CI=Confidence Interval; HS=High School; NA=Not Available; UNK=Unknown Table 3: Multivariate Analysis of subpopulations receiving different treatments and with distinct stages at diagnosis. Subset analysis with the following subset population Multivariable HR (Pediatric vs Adult) P Chemotherapy 0.58 (0.48, 0.71) <.01 Surgery 0.48 (0.32, 0.72) <.01 Chemotherapy + surgery 0.55 (0.50, 0.61) <.01 Chemo + surgery + radiation 0.66 (0.39, 1.11) 0.11 No treatment 0.25 (0.14, 0.42) <.01 Stage I 0.48 (0.37, 0.63) <.01 Stage II/III 0.56 (0.50, 0.64) <.01 Stage IV 0.60 (0.51, 0.71) <.01 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 18 Feb, 2025 Read the published version in BMC Cancer → Version 1 posted Editorial decision: Revision requested 25 Sep, 2024 Editor assigned by journal 25 Sep, 2024 Submission checks completed at journal 25 Sep, 2024 First submitted to journal 13 Sep, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5085447","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":358886523,"identity":"46068f9a-55bf-4d13-903a-771e2baa7529","order_by":0,"name":"Ryan Boyland","email":"","orcid":"","institution":"University of Nebraska Medical Center","correspondingAuthor":false,"prefix":"","firstName":"Ryan","middleName":"","lastName":"Boyland","suffix":""},{"id":358886524,"identity":"6aef2ba2-36c4-4596-8c55-e54fba9a25eb","order_by":1,"name":"Saber Amin","email":"","orcid":"","institution":"Department of Radiation Oncology, University of Nebraska Medical Center","correspondingAuthor":false,"prefix":"","firstName":"Saber","middleName":"","lastName":"Amin","suffix":""},{"id":358886525,"identity":"3da8057f-b56c-4e7e-8f6c-7b7c4bce34f8","order_by":2,"name":"Valerie Shostrom","email":"","orcid":"","institution":"Department of Biostatistics, University of Nebraska Medical Center","correspondingAuthor":false,"prefix":"","firstName":"Valerie","middleName":"","lastName":"Shostrom","suffix":""},{"id":358886526,"identity":"c91c3f9a-c73f-44e1-80cf-f37b2e64e83a","order_by":3,"name":"Cheng Zheng","email":"","orcid":"","institution":"Department of Biostatistics, University of Nebraska Medical Center","correspondingAuthor":false,"prefix":"","firstName":"Cheng","middleName":"","lastName":"Zheng","suffix":""},{"id":358886527,"identity":"cd634a76-1e5f-4633-a87a-1eebbc8d4f36","order_by":4,"name":"Jenna Allison","email":"","orcid":"","institution":"Department of Pediatrics, University of Nebraska Medical Center","correspondingAuthor":false,"prefix":"","firstName":"Jenna","middleName":"","lastName":"Allison","suffix":""},{"id":358886528,"identity":"f423142a-1ae9-462d-b3ad-84ad028a6af0","order_by":5,"name":"Chi Lin","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAnklEQVRIiWNgGAWjYBAC/nbGBoYPUI4EUVokDjM2MM4gSYuBMwMDMw9pWpiZ2x7btt2J5m9gPnibh7AGkBbGduPctme5Mw6wJVsTq6VNOrftcO4GBh4zaeK1WIK18H8jUoszUAsjxBY24rQAA7lNsufc4dwZh9mMLecQo4W/vf2ZxI+yw7n97c0Pb7whRgsCMJOmfBSMglEwCkYBPgAA1T4rpPHY6a0AAAAASUVORK5CYII=","orcid":"","institution":"University of Nebraska Medical Center","correspondingAuthor":true,"prefix":"","firstName":"Chi","middleName":"","lastName":"Lin","suffix":""}],"badges":[],"createdAt":"2024-09-13 17:40:11","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5085447/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5085447/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12885-025-13496-3","type":"published","date":"2025-02-18T15:57:19+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":71682543,"identity":"5a22a478-104c-4d01-8780-a56e61572286","added_by":"auto","created_at":"2024-12-17 16:46:55","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":266268,"visible":true,"origin":"","legend":"\u003cp\u003eOverall Survival for pediatric (blue) and adult (red) patients\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-5085447/v1/37188b68e87dee8779b3af06.png"},{"id":71682545,"identity":"f130f85f-5ae9-43a3-9f26-b4c601242266","added_by":"auto","created_at":"2024-12-17 16:46:55","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":30770,"visible":true,"origin":"","legend":"\u003cp\u003eHazard ratio (HR) (pediatrics vs. Adults) as a function of stage at diagnosis\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-5085447/v1/6c900cec8c12378d5ebaca9d.png"},{"id":71682542,"identity":"9c07d57f-84fa-415b-9523-5a4110bb67ac","added_by":"auto","created_at":"2024-12-17 16:46:55","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":28861,"visible":true,"origin":"","legend":"\u003cp\u003eHazard ratio (HR) (pediatrics vs. Adults) as a function of treatment regimens (No Tx: no treatment; S: surgery; S+C: surgery+chemotherapy; C: Chemotherapy; and S+C+R: surgery+chemotherapy+radiation.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-5085447/v1/45a61bb5c0e08d0009b6239b.png"},{"id":77052549,"identity":"345aaff7-9dbf-4385-9e57-902394ce1707","added_by":"auto","created_at":"2025-02-24 16:14:32","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1097619,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5085447/v1/c7077843-a694-45bb-86d3-9a3dca077ae6.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Comparison of overall survival of adult and pediatric osteosarcoma patients using the National Cancer Database","fulltext":[{"header":"Background","content":"\u003cp\u003eOsteosarcoma is the most common malignant primary bone tumor accounting for more than 50% of the primary bone tumors. It mainly affects children and adolescent, with individuals between the ages of 15 and 25 accounting for 55% of cases, 30% of cases occurring in individuals over the age of 40, and 10% being over the age of 60.\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. Osteosarcoma is the sixth most common malignancy in both children aged 0\u0026ndash;14 and those aged 15-19.\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e Approximately 70% of osteosarcoma cases occur in patients under the age of 18.\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e The five-year survival rate for early-stage osteosarcoma for all ages is 74% followed by 66% for locally advanced, and 27% for metastatic disease. The survival rate of osteosarcoma is inversely correlated with age at diagnosis with pediatric patients having a five-year survival rate of 78% and elderly patients having only a 25% five-year survival rate.\u003c/p\u003e \u003cp\u003eSurgical resection with neoadjuvant and adjuvant chemotherapy is the mainstay of treatment for osteosarcoma. Methotrexate, doxorubicin, and cisplatin are the recommended chemotherapeutic agents.\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e,\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e After the introduction of multi-agent chemotherapy a few decades ago, the five-year survival rate of osteosarcoma improved from 20\u0026ndash;60%. However, since then the survival rates remained unchanged despite advancement in cancer treatments and multiple attempts to refine various treatment regimens.\u003c/p\u003e \u003cp\u003eOverall survival (OS) depends on various demographic, tumor, and treatment related factors, which include age at diagnosis, metastases at the time of diagnosis, tumor size, tumor location, response to chemotherapy, and time to treatment initiation.\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e The difference in OS between children and elderly patients is poorly understood.\u003c/p\u003e \u003cp\u003eCorrelations between more malignant variants of osteosarcoma and age have been demonstrated,\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e and data demonstrating a correlation between earlier presentations of disease and more aggressive forms of disease suggest that time to diagnosis might also be a significant prognostic factor.\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e In children vs young adult populations, age was found to be most important because of its correlation with risk of relapse, but it was not further associated with histologic response, or metastatic disease at presentation\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003ePrior research has suggested that age be the most important prognostic factor when considering outcomes from osteosarcoma,\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e,\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e but the literature is limited by small sample size especially in adults. The objective of the current study is to compare the OS of children and adolescents with the OS of adult patients diagnosed with osteosarcoma and determine the prognostic factors associated with OS using the National Cancer Database. We will also explore factors associated with pediatric patients with osteosarcoma.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cstrong\u003eData source\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData for the current study were extracted from the NCDB, a nationwide oncology outcomes database for more than 1500 Commission accredited cancer programs in the United States and Puerto Rico. The NCDB captures more than 70% of the cancer cases diagnosed in the United States annually. NCDB is a joint project of the Commission on Cancer (CoC) of the American College of Surgeons and the American Cancer Society. The CoC\u0026apos;s NCDB and the hospitals participating in the CoC\u0026rsquo;s NCDB are the source of the de-identified data used herein; they have not verified and are not responsible for the statistical validity of the data analysis or the conclusions derived by the authors. The study was exempt from Institutional board review as the data is de-identified. Informed consent was also not required.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStudy population\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePatient \u0026gt;=1 years old diagnosed with osteosarcoma between 2004 and 2017 were included in the study. The primary end point was OS, which was measured in months from the date of diagnosis to death. Patients who were alive at last follow-up or were lost to follow-up were censored. Age at diagnosis was the main variable as a predictor of OS. Other covariates included sex, race, income, education, place of residence, health insurance type, year of cancer diagnosis, surgery, chemotherapy, radiation therapy (RT), immunotherapy, and cancer stage. For population in the city of diagnosis (urban/rural) patients, the following subcategories were used: \u0026gt;=1 million \u0026nbsp; \u0026lt;1 million. \u0026nbsp;For level of education, the following subcategories were used: surrounding population with \u0026gt;=10.9% without a high school diploma, surrounding population with \u0026lt;=10.8% without a high school diploma. For income, the following subcategories were used: median income \u0026lt;=$50,353; median income \u0026gt;$50,354. For patient insurance, the following subcategories were used: Not insured/unknown; Medicaid/Medicare/Other government insurance and Private/managed care. For treatment modality, patients were divided into categories based on whether they underwent any surgery chemotherapy. Patients were then subdivided into further categories depending on combination of treatment modality, for example, chemotherapy/surgery/radiation, chemotherapy/surgery alone, chemotherapy/radiation alone, chemotherapy alone, surgery/radiation alone, surgery alone, radiation alone, and no treatment.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDescriptive statistics for categorical and continuous variables were reported by children (1-17 years) and adult (18=\u0026gt; years). We performed multivariable logistic regression analysis to determine the factors associated with adults with osteosarcoma when compared to pediatric. Odds ratio was reported as a measure of association with the covariate of interest and being an adult with osteosarcoma. Kaplan-Meier analysis was used to report OS and log-rank test \u0026nbsp; was used to compare OS between children and adult. Multivariable Cox regression analysis was used to report the hazard ratio (HR) and its 95% confidence interval (CI) for the factors associated with OS. A P-value of 0.05 was used for a significant level, which was based on 2-sided tests. The SAS 9.4 software was used for the analyses in the current study. Data with missing subject\u0026rsquo;s age were removed. For other missing data, such as population of the subject\u0026rsquo;s city or level of education, a separate category for that specific categorical variable was created (for example, \u0026ldquo;missing\u0026rdquo;), and the data analysis was conducted with their data included as such.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003ePatient Characteristics\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe final analysis included 7,890 patients among whom 2,972 (37.7%) were between the ages of 1-17 years old and 4,918 (62.3%) were adult (defined as age greater than or equal to 18 years at the time of diagnosis). The proportion of most variables by age was similar between the two groups. However, 1809 (61%) of the pediatric patients had private insurance compared to 2705 (55%) of adults having private insurance. About 2544 (86%) of the pediatric patients received surgery compared to 3888 (79%) of adult patients. Approximately 2809 (95%) of the pediatric patients received chemotherapy, while only 3611 (73%) of the adult patients received chemotherapy. More pediatric patients (2409 (81%)) received surgery plus chemotherapy compared to 2659 (54%) of adult patients. Further details regarding population characteristics and subcategories can be found in Table 1.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn the univariable logistic regression analysis, white race, missing median income, lack of insurance/unknown insurance, and receiving radiation were associated with a statistically significant increase in OR for adult patients, while rural location (population \u0026lt;1 million), private/managed care, unknown/occult stage of cancer at diagnosis, poorly differentiated tumor, and treatment modality (involving immunotherapy, surgery, or chemotherapy without radiation) were associated with being diagnosed with osteosarcoma at pediatric age.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn the multivariable logistic regression analysis, white race, lack of insurance/unknown insurance, and radiation as part of their treatment modality was associated with greater OR for an adult patient, while unknown/occult stage of cancer at diagnosis, poorly differentiated tumor, and treatment modality (involving immunotherapy, surgery, or chemotherapy without radiation) were positively associated with being diagnosed at pediatric age (p\u0026lt;.01), as demonstrated in \u003cstrong\u003eTable 1\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eOverall Survival Comparison\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePediatric patients had better OS compared to adult patients. The median survival was unreached for pediatric patients and 69 months for adults. The 5-year OS rates were 69.2% for pediatric patients and 51.6% for adults, while the 10-year OS rates were 63.5% and 44.0%, respectively (p\u0026lt;.01). (\u003cstrong\u003eFigure 1)\u003c/strong\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn the univariable Cox regression analysis, patients diagnosed with osteosarcoma at age \u0026gt;=18 years old had a worse OS compared to patients diagnosed 1-17 years old (HR: 1.90; 95% CI: 1.76, 2.05; p\u0026lt;.01).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn the multivariable Cox regression analysis (\u003cstrong\u003eTable 2\u003c/strong\u003e) adjusted for sex, race, income, education, place of residence, insurance status, stage, grade, chemotherapy, surgery, RT, immunotherapy, and year of diagnosis, adult patients had worse OS compared to pediatric patients, making age a significant factor in prognosis (HR: 1.90; 95%; CI: 1.75, 2.05; p\u0026lt;.01). Other factors associated with worse OS were higher stage at diagnosis (Stage 4: HR 3.40; 95% CI: 3.12, 3.71; p\u0026lt;.01), poor differentiation (HR 2.89; 95% CI: 2.40, 3.48; p\u0026lt;.01), and RT (HR 1.46; 95% CI: 1.31, 1.63; p\u0026lt;.01).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eNotably, factors associated with improved OS were year of diagnosis between 2011 and 2015 when compared to 2004-2010 (HR: 0.84; 95% CI: 0.78, 0.91, p\u0026lt;.01), as well as either being uninsured/possessing unknown insurance or private insurance, when compared with Medicaid/Medicare/Other Government Insurance being associated with greater OS (HR: 0.70; 95% CI: 0.62, 0.79; p\u0026lt;.01 AND HR: 0.77; 95% CI: 0.71, 0.82; p\u0026lt;.01 respectively).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWith respect to treatment modality, regimens involving surgery, as well as regimens involving chemotherapy were both associated with increased OS (HR: 0.46; 95% CI: 0.42, 0.49; p \u0026lt;.01 AND HR: 0.73 95% CI: 0.66, 0.80; p \u0026lt;.01, respectively).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSubset Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe further explored the improved OS associated with being diagnosed with osteosarcoma at pediatric age by performing analyses stratified by treatment type and stage of the cancer.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAmong patients who received only chemotherapy, pediatric patients had better OS compared to adult patients (HR: 0.58; 95% CI: 0.48, 0.71; p \u0026lt; .01). Among patients who only received surgery (HR: 0.48; 95% CI: 0.32, 0.74; p \u0026lt; .01) or surgery plus chemotherapy (HR: 0.55; 95% CI: 0.50, 0.61; p \u0026lt; .01), pediatric patients had higher OS compared to adult patients. There was no difference in the OS of pediatric patients and adult patients among those who received chemotherapy, plus surgery plus RT (HR: 0.66; 95% CI: 0.39, 1.11; p = 0.11) (Table 3). Also, among those who received no treatment, pediatric patients had better OS compared to adult patients (HR: 0.25; 95% CI: 0.14, 0.42; p \u0026lt;.01) (Figure 3). In the analyses stratified by stage of cancer, pediatric patients had better OS compared to adult patients in stage I, stage II/III, and stage IV cancer (\u003cstrong\u003eTable 3\u003c/strong\u003e and \u003cstrong\u003eFigure 2\u003c/strong\u003e).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe bimodal distribution of incidence of osteosarcoma is well-studied and well-cited, as is the increased overall survival for pediatric patients relative to adult patients.\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e This study shows that pediatric patients with osteosarcoma have lower mortality rates compared to adult patients, even though pediatric cases are often associated with a poorly differentiated grade. This reduced mortality in pediatric patients is consistent across all stages and treatment modalities, except for radiation therapy.\u003c/p\u003e \u003cp\u003eA thorough review of the literature shows an absence of a broad assessment comparing prognostic factors for osteosarcoma among different age groups. One of the more notable studies that attempted what we did here highlighted differences among five different age groups, collecting data from 1973-2004\u003csup\u003e10\u003c/sup\u003e. Mirabello et al (2009) described risk factors for osteosarcoma among five age cohorts; among them, race was noted to be statistically significant. Here, we found that, while white race was associated with a greater likelihood of the patient being diagnosed as an adult, it was not associated with a statistically significant difference in overall survival as a factor alone when comparing adults and pediatric patients. In this study, we found that factors such as later stage at diagnosis, poorly differentiated tumor, and presence of radiation as part of the treatment modality were associated with reduced overall survival for adults relative to pediatric patients, indicating that factors such as socioeconomic status or racial background broadly were less likely to be indicative of overall prognosis. We did not, however, explore specific racial or ethnic backgrounds (here, we examined simply white vs non-white) and how those details may have an impact on survival of adults compared to pediatric patients. We also did not assess specifically how factors such as race relate to socioeconomic background, insurance status, or whether it was associated with any delay in diagnosis.\u003c/p\u003e \u003cp\u003eOther studies exploring the factors that could be responsible for worse OS in the adult population include Janeway et al (2012), examined differences in overall survival in patients with high-grade osteosarcoma of any site, and argued that the difference in event-free survival and overall survival was in the setting of increased rate of relapse for adult (\u0026thinsp;\u0026gt;\u0026thinsp;=\u0026thinsp;18 years) relative to pediatric patients\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. Their paper found decreased overall survival for adult population, as was the case in this paper, but argued that the difference in survival was not explained by tumor location, histologic response, or metastatic disease. Our data, however, found that there was decreased overall survival for stage IV malignancy as determined at diagnosis. This discrepancy may be in part due to the different population subsets used in their paper, as well as the much larger data set size in our study, reducing the likelihood of type B error. Some reasons that older patients diagnosed with osteosarcoma have poor OS are that older patients are more likely to not tolerate chemotherapy and more likely to have higher number of secondary osteosarcomas. The location of osteosarcoma is another important factor that is considered to play a role in the poor OS of older patients as they are more likely to have axial osteosarcoma, which we do not address here.\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eIn previously published literature, difference in survival was also argued to be associated with unusual locations, abnormal radiological findings, and poor response to chemotherapy\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. Here, we do not examine discrepancies in tumor location and, as a result, difficulty with surgery. We do, however, examine general trends in differences in tumor stage, grade, and treatment modality. In addition, the small number of patients used in the Jeon et al (2006) study, alongside their use of patients at a single institution limit external validity of their results. Patients included in our data set who were treated with chemotherapy, surgery, or chemotherapy plus surgery were associated with lower hazard ratio for pediatric relative to adult populations, providing support to the argument that differences in treatment decisions between the different populations is not the main factor contributing to differences in outcomes. The argument that adults may be afflicted with more aggressive tumors, or tumors found at a later stage would follow logically in the Jeon et al (2006) paper given the tissue responsiveness to chemotherapy and the reported grade among their patients, but this effect was not replicated in our data, in which the odds ratio suggested that more poorly differentiated tumors/occult tumors were more likely in pediatric populations, and that tumor stage at diagnosis did not significantly change the odds ratio between adults and pediatric populations, suggesting adults and pediatric patients have similar stage distribution. The fact that the chemotherapy, surgery, and radiation (C\u0026thinsp;+\u0026thinsp;S\u0026thinsp;+\u0026thinsp;R) treatment modality was not associated with significant differences in outcome between pediatrics and adults may be in part due to severity of disease necessitating more aggressive therapy, and more data may be needed to better elucidate a difference.\u003c/p\u003e \u003cp\u003eThere is also an argument that chemotherapy regimens are better tolerated in pediatric rather than adult populations\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. This evidence is both anecdotal and supported by objective data of adverse outcomes associated with more common treatment regimens involving cisplatin, methotrexate, and doxorubicin. This difference is difficult to delineate in our data, where, while there is data that suggests that chemotherapy is more likely to be implemented in pediatric patients, with an associated improved survival in pediatric patients, but chemotherapy regimens, duration of chemotherapy and tolerability of chemotherapy were not part of our analysis.\u003c/p\u003e \u003cp\u003eRegarding the notion that differences in survival are related to tumor location and difficulty with surgery, this is represented in the data with previous studies showing worse prognosis with axial -related tumors, and an increased frequency of axial osteosarcoma in adult patients\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e,\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e, however, the effect in the difference in outcome is inconsistent, and other data suggests that location (axial vs extra-axial) had no impact on survival for patients achieving surgical remission.\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e,\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003eOverall, the difference in survival between adult and pediatric patients afflicted with osteosarcoma is likely multifactorial, with many factors at play potentially including histological findings conveying more resistance to treatment, surgical site, and other factors mentioned above, but the exact mechanism requires more study.\u003c/p\u003e \u003cp\u003eFurthermore, this study revealed that pediatric patients with osteosarcoma are more likely to receive chemotherapy, surgery, and immunotherapy, while adult patients are more likely to receive RT. This treatment disparity could be one reason for the improved OS observed in pediatric patients. Pediatric patients often participate in Children's Oncology Group (COG) trials, which increases their chances of receiving comprehensive treatments such as chemotherapy, surgery, and immunotherapy, contributing to their better OS. On the other hand, RT in adults is frequently associated with palliative care, which correlates with poorer OS. Interestingly, the ongoing COG osteosarcoma trial AOST2032 has incorporated high dose definitive radiation therapy into the initial definitive therapy regimen. This inclusion may alter the current understanding of radiation therapy's impact on osteosarcoma outcomes in the future.\u003c/p\u003e \u003cp\u003eImportantly, given the pace of medical innovation and the advent of new chemotherapy drugs and treatment regimens to better treat osteosarcoma, it is necessary to continually reevaluate our understanding of prognostic indicators. Within those researchers\u0026rsquo; study, they noted significant improvement in survival amongst all age groups from 1973-83 and 1984-93, coinciding with the implementation of multiagent chemotherapy regimens\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. There are ongoing collaborative discussions regarding more streamlined, efficacious therapies, with both the NCCN and ESMO continually updating their guidelines and recommendations to match the significant technologic advances in the field\u003csup\u003e\u003cspan additionalcitationids=\"CR18\" citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e. With the popularization of more targeted therapies, such as tyrosine kinase inhibitors, in the past two decades, survival rates for all cancers have improved\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e,\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. By monitoring these prognostic factors over time, we can identify groups of people who, while treatments overall are improving survival outcomes, may be left behind relative to their peers.\u003c/p\u003e \u003cp\u003eLimitations of this study include retrospective in nature, study period selected, study groups chosen, and limited information regarding precise treatment regimens, incomplete data, and ascertainment bias. Further research would be beneficial to describe how different interventions or diagnostic studies would be influential in improving the prognoses of the various study groups. Nevertheless, our study is the largest study that investigated the factors associated with being diagnosed at age\u0026thinsp;\u0026lt;\u0026thinsp;18 years and explored the difference in the OS of adult and pediatric patients diagnosed with osteosarcoma.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eIn this comprehensive analysis of the NCDB, we found that adult patients diagnosed with osteosarcoma had worse OS compared with pediatric patients. This reduced mortality in pediatric patients is consistent across all stages and treatment plans. Pediatric patients are more likely to be non-white, have insurance, present with unknown or occult stage disease, have poorly differentiated tumors, and receive immunotherapy, chemotherapy, or surgery, but not radiation therapy. Additionally, prognostic factors associated with improved OS include pediatric status, diagnosis between 2011\u0026ndash;2015, having private insurance or managed care, non-metastatic disease, well-differentiated tumors, and receiving chemotherapy or surgery, but not radiation therapy. More research will be necessary to delineate the underlying reason for this difference.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eOverall Survival (OS), National Cancer Database (NCDB), Hazard Ratio (HR), Odds Ratio (OR), Commission on Cancer (CoC), Confidence Interval (CI), Radiation Thearpy (RT)\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eEthics approval and consent to participate:\u003c/h2\u003e\n\u003cp\u003eNot Applicable\u003c/p\u003e\n\u003ch2\u003eConsent for publication:\u003c/h2\u003e\n\u003cp\u003eNot Applicable\u003c/p\u003e\n\u003ch2\u003eCompeting Interests:\u003c/h2\u003e\n\u003cp\u003eVS owns stock in Pfizer. CL has received an NIH grant to support a rectal cancer trial and is currently performing two trials that use a drug developed by BioMimetix. All other authors declare that they have no competing interests.\u003c/p\u003e\n\u003ch2\u003eFunding:\u003c/h2\u003e\n\u003cp\u003eNot Applicable\u003c/p\u003e\n\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\n\u003cp\u003eRB, CL, SA wrote and edited the manuscript text and abstract.RB assisted with creating figures 2-3.VS performed statistical analysis, data collection, and table 1-3 and figure 1 creation.JA assisted with editing the manuscript, project initiation, and the discussion section. CZ assisted with project initiation and editing the manuscript.\u003c/p\u003e\n\u003ch2\u003eAcknowledgements:\u003c/h2\u003e\n\u003cp\u003eNot Applicable\u003c/p\u003e\n\u003ch2\u003eData Availability\u003c/h2\u003e\n\u003cp\u003eData used in the paper was accessed using the National Cancer Database, available publicly.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003evon Eisenhart-Rothe R, Toepfer A, Salzmann M, Schauwecker J, Gollwitzer H, Rechl H. Prim\u0026auml;r maligne Knochentumoren. Orthop. 2011;40(12):1121\u0026ndash;42. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s00132-011-1866-7\u003c/span\u003e\u003cspan address=\"10.1007/s00132-011-1866-7\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMirabello L, Troisi RJ, Savage SA. 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Guidelines detail. 2022;2022(July 8). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.nccn.org/guidelines/guidelines-detail?category=1\u0026amp;id=1418\u003c/span\u003e\u003cspan address=\"https://www.nccn.org/guidelines/guidelines-detail?category=1\u0026amp;id=1418\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eIsakoff MS, Bielack SS, Meltzer P, Gorlick R. Osteosarcoma: Current Treatment and a Collaborative Pathway to Success. J Clin Oncol Off J Am Soc Clin Oncol. 2015;33(27):3029\u0026ndash;35. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1200/JCO.2014.59.4895\u003c/span\u003e\u003cspan address=\"10.1200/JCO.2014.59.4895\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eIqbal N, Iqbal N. Imatinib: a breakthrough of targeted therapy in cancer. Chemother Res Pract. 2014;2014:357027. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1155/2014/357027\u003c/span\u003e\u003cspan address=\"10.1155/2014/357027\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTable 1: Logistic Regression Analysis of the Factors Associated with Adult vs. pediatric Patients with Osteosarcoma.\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 222px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 234px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge group*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 150px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eUnivariable OR (95% CI)*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 60px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 139px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMultivariable OR (95% CI)*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 58px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1-17\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eN=2972\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 120px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026gt;=18\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eN=4918\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 222px;\"\u003e\n \u003cp\u003eSex\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; Male\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; Female\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1687 (57%)\u003c/p\u003e\n \u003cp\u003e1285 (43%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e2781 (57%)\u003c/p\u003e\n \u003cp\u003e2137 (43%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.991 (0.904, 1.087)\u003c/p\u003e\n \u003cp\u003eReference\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e0.8514\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 139px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 222px;\"\u003e\n \u003cp\u003eRace\u003c/p\u003e\n \u003cp\u003eWhite\u003c/p\u003e\n \u003cp\u003eNon-white\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e2173 (73%)\u003c/p\u003e\n \u003cp\u003e799 (27%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e3804 (77%)\u003c/p\u003e\n \u003cp\u003e1114 (23%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1.26 (1.13, 1.40)\u003c/p\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026lt;.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 139px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1.28 (1.14, 1.43)\u003c/p\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e\u0026lt;.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 222px;\"\u003e\n \u003cp\u003eYear of diagnosis\u003c/p\u003e\n \u003cp\u003e2004-2010\u003c/p\u003e\n \u003cp\u003e2011-2015\u003c/p\u003e\n \u003cp\u003e2016\u003c/p\u003e\n \u003cp\u003e2017\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1470 (49%)\u003c/p\u003e\n \u003cp\u003e1087 (37%)\u003c/p\u003e\n \u003cp\u003e198 (7%)\u003c/p\u003e\n \u003cp\u003e217 (7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e2369 (48%)\u003c/p\u003e\n \u003cp\u003e1760 (36%)\u003c/p\u003e\n \u003cp\u003e379 (8%)\u003c/p\u003e\n \u003cp\u003e410 (8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003cp\u003e1.01 (0.91, 1.11)\u003c/p\u003e\n \u003cp\u003e1.19 (0.99, 1.43)\u003c/p\u003e\n \u003cp\u003e1.17 (0.98, 1.40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e0.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 139px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 222px;\"\u003e\n \u003cp\u003eUrban/rural\u003c/p\u003e\n \u003cp\u003e\u0026gt;=1 million\u003c/p\u003e\n \u003cp\u003e\u0026lt;1 million\u003c/p\u003e\n \u003cp\u003emissing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1431 (48%)\u003c/p\u003e\n \u003cp\u003e1400 (47%)\u003c/p\u003e\n \u003cp\u003e141 (5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e2516 (51%)\u003c/p\u003e\n \u003cp\u003e2154 (44%)\u003c/p\u003e\n \u003cp\u003e248 (5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003cp\u003e0.88 (0.80, 0.96)\u003c/p\u003e\n \u003cp\u003e1.00 (0.81, 1.24)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026lt;.01\u003c/p\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 139px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 222px;\"\u003e\n \u003cp\u003eNo HS degree\u003c/p\u003e\n \u003cp\u003e\u0026gt;=10.9%\u003c/p\u003e\n \u003cp\u003e\u0026lt;=10.8%\u003c/p\u003e\n \u003cp\u003eMissing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1391 (47%)\u003c/p\u003e\n \u003cp\u003e1320 (44%)\u003c/p\u003e\n \u003cp\u003e261 (9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e2232 (45%)\u003c/p\u003e\n \u003cp\u003e2207 (45%)\u003c/p\u003e\n \u003cp\u003e479 (10%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003cp\u003e1.04 (0.95, 1.15)\u003c/p\u003e\n \u003cp\u003e1.14 (0.97, 1.35)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e0.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 139px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 222px;\"\u003e\n \u003cp\u003eMedian income\u003c/p\u003e\n \u003cp\u003e\u0026lt;=$50353\u003c/p\u003e\n \u003cp\u003e\u0026gt;=50354\u003c/p\u003e\n \u003cp\u003eMissing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1161 (39%)\u003c/p\u003e\n \u003cp\u003e1546 (52%)\u003c/p\u003e\n \u003cp\u003e265 (9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1922 (39%)\u003c/p\u003e\n \u003cp\u003e2506 (51%)\u003c/p\u003e\n \u003cp\u003e490 (10%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003cp\u003e0.98 (0.89, 1.08)\u003c/p\u003e\n \u003cp\u003e1.12 (0.95, 1.32)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e0.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 139px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 222px;\"\u003e\n \u003cp\u003eInsurance\u003c/p\u003e\n \u003cp\u003eNot insured/unknown\u003c/p\u003e\n \u003cp\u003eMedicaid/Medicare/other gov\u003c/p\u003e\n \u003cp\u003ePrivate/managed care\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e186 (6%)\u003c/p\u003e\n \u003cp\u003e977 (33%)\u003c/p\u003e\n \u003cp\u003e1809 (61%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e548 (11%)\u003c/p\u003e\n \u003cp\u003e1665 (34%)\u003c/p\u003e\n \u003cp\u003e2705 (55%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1.73 (1.44, 2.08)\u003c/p\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003cp\u003e0.88 (0.80, 0.97)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026lt;.01\u003c/p\u003e\n \u003cp\u003e\u0026lt;.01\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 139px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1.87 (1.54, 2.27)\u003c/p\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003cp\u003e0.97 (0.87, 1.08)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e\u0026lt;.01\u003c/p\u003e\n \u003cp\u003e\u0026lt;.01\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.61\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 222px;\"\u003e\n \u003cp\u003eStage\u003c/p\u003e\n \u003cp\u003eI/II/III\u003c/p\u003e\n \u003cp\u003eIV\u003c/p\u003e\n \u003cp\u003eNA/UNK/Occult\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1859 (63%)\u003c/p\u003e\n \u003cp\u003e434 (15%)\u003c/p\u003e\n \u003cp\u003e679 (23%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e3219 (65%)\u003c/p\u003e\n \u003cp\u003e791 (16%)\u003c/p\u003e\n \u003cp\u003e908 (18%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003cp\u003e1.05 (0.92, 1.20)\u003c/p\u003e\n \u003cp\u003e0.77 (0.69, 0.87)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026lt;.01\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.44\u003c/p\u003e\n \u003cp\u003e\u0026lt;.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 139px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003cp\u003e1.00 (0.87, 1.15)\u003c/p\u003e\n \u003cp\u003e0.61 (0.41, 0.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e\u0026lt;.01\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.98\u003c/p\u003e\n \u003cp\u003e\u0026lt;.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 222px;\"\u003e\n \u003cp\u003eGrade\u003c/p\u003e\n \u003cp\u003eWell/moderately differentiated\u003c/p\u003e\n \u003cp\u003ePoor/Undifferentiated\u003c/p\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e95 (3%)\u003c/p\u003e\n \u003cp\u003e2007 (68%)\u003c/p\u003e\n \u003cp\u003e870 (29%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e490 (10%)\u003c/p\u003e\n \u003cp\u003e3194 (65%)\u003c/p\u003e\n \u003cp\u003e1234 (25%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003cp\u003e0.31 (0.25, 0.39)\u003c/p\u003e\n \u003cp\u003e0.28 (0.22, 0.35)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026lt;.01\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026lt;.01\u003c/p\u003e\n \u003cp\u003e\u0026lt;.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 139px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003cp\u003e0.53 (0.41, 0.67)\u003c/p\u003e\n \u003cp\u003e0.44 (0.34, 0.56)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e\u0026lt;.01\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026lt;.01\u003c/p\u003e\n \u003cp\u003e\u0026lt;.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 222px;\"\u003e\n \u003cp\u003eImmunotherapy\u003c/p\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e29 (1%)\u003c/p\u003e\n \u003cp\u003e2943 (99%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e18 (0.4%)\u003c/p\u003e\n \u003cp\u003e4900 (99.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.37 (0.21, 0.67)\u003c/p\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026lt;.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 139px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.38 (0.20, 0.72)\u003c/p\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e0.0031\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 222px;\"\u003e\n \u003cp\u003eSurgery\u003c/p\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e2544 (86%)\u003c/p\u003e\n \u003cp\u003e428 (14%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e3888 (79%)\u003c/p\u003e\n \u003cp\u003e1030 (21%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.64 (0.56, 0.72)\u003c/p\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026lt;.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 139px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.70 (0.61, 0.80)\u003c/p\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e\u0026lt;.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 222px;\"\u003e\n \u003cp\u003eChemotherapy\u003c/p\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e2809 (95%)\u003c/p\u003e\n \u003cp\u003e163 (5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e3611 (73%)\u003c/p\u003e\n \u003cp\u003e1307 (27%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.16 (0.14, 0.19)\u003c/p\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026lt;.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 139px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.18 (0.15, 0.22)\u003c/p\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e\u0026lt;.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 222px;\"\u003e\n \u003cp\u003eRadiation\u003c/p\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e64 (2%)\u003c/p\u003e\n \u003cp\u003e2908 (98%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e580 (12%)\u003c/p\u003e\n \u003cp\u003e4338 (88%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e6.08 (4.67, 7.90)\u003c/p\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026lt;.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 139px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e5.07 (3.87, 6.64)\u003c/p\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e\u0026lt;.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 222px;\"\u003e\n \u003cp\u003eChemo/surgery/radiation\u003c/p\u003e\n \u003cp\u003eCSR\u003c/p\u003e\n \u003cp\u003eCS\u003c/p\u003e\n \u003cp\u003eC\u003c/p\u003e\n \u003cp\u003eCR\u003c/p\u003e\n \u003cp\u003eSR\u003c/p\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003cp\u003eNone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e37 (1%)\u003c/p\u003e\n \u003cp\u003e2409 (81%)\u003c/p\u003e\n \u003cp\u003e337 (11%)\u003c/p\u003e\n \u003cp\u003e26 (1%)\u003c/p\u003e\n \u003cp\u003e1 (.03%)\u003c/p\u003e\n \u003cp\u003e97 (3%)\u003c/p\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003cp\u003e65 (2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 120px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e245 (5%)\u003c/p\u003e\n \u003cp\u003e2659 (54%)\u003c/p\u003e\n \u003cp\u003e609 (12%)\u003c/p\u003e\n \u003cp\u003e98 (2%)\u003c/p\u003e\n \u003cp\u003e176 (4%)\u003c/p\u003e\n \u003cp\u003e808 (16%)\u003c/p\u003e\n \u003cp\u003e61 (1%)\u003c/p\u003e\n \u003cp\u003e262 (5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 139px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e*Predicting age\u0026gt;=18; All terms put in multivariable model (except CSR variable); backward selection applied to arrive at final model; C=Chemotherapy; S=Surgery; R=Radiation; CS=Chemotherapy and Surgery; CSR=Chemotherapy, Surgery, and Radiation; CR=Chemotherapy and Radiation; SR=Surgery and Radiation\u003c/p\u003e\n\u003cp\u003eTable 2: Univariable and Multivariable Cox Proportional Regression Analysis of Factors Associated With Overall Survival.\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eUnivariable HR (95% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eP-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eMultivariable HR (95% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eP-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd height=\"37\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd height=\"37\" style=\"width: 0px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003cp\u003e1-17\u003c/p\u003e\n \u003cp\u003e18+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003cp\u003e1.90 (1.76, 2.05)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003cp\u003e1.90 (1.75, 2.05)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eRace\u003c/p\u003e\n \u003cp\u003eWhite\u003c/p\u003e\n \u003cp\u003eNot white\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003cp\u003e0.98 (0.90, 1.06)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eYear of diagnosis\u003c/p\u003e\n \u003cp\u003e2004-2010\u003c/p\u003e\n \u003cp\u003e2011-2015\u003c/p\u003e\n \u003cp\u003e2016\u003c/p\u003e\n \u003cp\u003e2017\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003cp\u003e0.87 (0.80, 094)\u003c/p\u003e\n \u003cp\u003e0.96 (0.82, 1.12)\u003c/p\u003e\n \u003cp\u003e1.14 (0.97, 1.33)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003cp\u003e0.56\u003c/p\u003e\n \u003cp\u003e0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003cp\u003e0.84 (0.78, 0.91)\u003c/p\u003e\n \u003cp\u003e0.86 (0.74, 1.01)\u003c/p\u003e\n \u003cp\u003e1.07 (0.91, 1.25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;.01\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026lt;.01\u003c/p\u003e\n \u003cp\u003e0.06\u003c/p\u003e\n \u003cp\u003e0.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eUrban/rural\u003c/p\u003e\n \u003cp\u003e\u0026gt;=1 million\u003c/p\u003e\n \u003cp\u003e\u0026lt;1 million\u003c/p\u003e\n \u003cp\u003eMissing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003cp\u003e1.06 (0.99, 1.13)\u003c/p\u003e\n \u003cp\u003e0.73 (0.61, 0.88)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;.01\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.12\u003c/p\u003e\n \u003cp\u003e\u0026lt;.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNo HS degree\u003c/p\u003e\n \u003cp\u003e\u0026gt;=10.9%\u003c/p\u003e\n \u003cp\u003e\u0026lt;=10.8%\u003c/p\u003e\n \u003cp\u003eMissing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003cp\u003e0.92 (0.85, 0.98)\u003c/p\u003e\n \u003cp\u003e0.46 (0.40, 0.54)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;.01\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e.01\u003c/p\u003e\n \u003cp\u003e\u0026lt;.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003cp\u003e0.97 (0.90, 1.04)\u003c/p\u003e\n \u003cp\u003e0.52 (0.44, 0.61)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;.01\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.41\u003c/p\u003e\n \u003cp\u003e\u0026lt;.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMedian income\u003c/p\u003e\n \u003cp\u003e\u0026lt;=$50353\u003c/p\u003e\n \u003cp\u003e\u0026gt;=50354\u003c/p\u003e\n \u003cp\u003eMissing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003cp\u003e0.92 (0.86, 0.99)\u003c/p\u003e\n \u003cp\u003e0.47 (0.40, 0.55)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;.01\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e.02\u003c/p\u003e\n \u003cp\u003e\u0026lt;.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eInsurance\u003c/p\u003e\n \u003cp\u003eNot insured/unknown\u003c/p\u003e\n \u003cp\u003eMedicaid/Medicare/other gov\u003c/p\u003e\n \u003cp\u003ePrivate/managed care\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.86 (0.76, 0.97)\u003c/p\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003cp\u003e0.69 (0.64, 0.74)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;.01\u003c/p\u003e\n \u003cp\u003e.01\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026lt;.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.70 (0.62, 0.79)\u003c/p\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003cp\u003e0.77 (0.71, 0.82)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;.01\u003c/p\u003e\n \u003cp\u003e\u0026lt;.01\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026lt;.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eStage\u003c/p\u003e\n \u003cp\u003eI/II/III\u003c/p\u003e\n \u003cp\u003eIV\u003c/p\u003e\n \u003cp\u003eNA/UNK/Occult\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003cp\u003e3.91 (3.60, 4.24)\u003c/p\u003e\n \u003cp\u003e1.34 (1.23, 1.47)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;.01\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026lt;.01\u003c/p\u003e\n \u003cp\u003e\u0026lt;.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003cp\u003e3.40 (3.12, 3.71)\u003c/p\u003e\n \u003cp\u003e1.18 (1.07, 1.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;.01\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026lt;.01\u003c/p\u003e\n \u003cp\u003e\u0026lt;.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eGrade\u003c/p\u003e\n \u003cp\u003eWell/moderately diff.\u003c/p\u003e\n \u003cp\u003ePoor/undiff.\u003c/p\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003cp\u003e2.45 (2.05, 2.94)\u003c/p\u003e\n \u003cp\u003e2.50 (2.07, 3.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;.01\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026lt;.01\u003c/p\u003e\n \u003cp\u003e\u0026lt;.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003cp\u003e2.89 (2.40, 3.48)\u003c/p\u003e\n \u003cp\u003e2.47 (2.04, 3.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;.01\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026lt;.01\u003c/p\u003e\n \u003cp\u003e\u0026lt;.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eImmunotherapy\u003c/p\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1.40 (0.950, 2.05)\u003c/p\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSurgery\u003c/p\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.35 (0.32, 0.38)\u003c/p\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.46 (0.42, 0.49)\u003c/p\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eChemotherapy\u003c/p\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.75 (0.69, 0.81)\u003c/p\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.73 (0.66, 0.80)\u003c/p\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eRadiation\u003c/p\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e2.08 (1.88, 2.31)\u003c/p\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1.46 (1.31, 1.63)\u003c/p\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eAll terms put in multivariable model (except CSR variable); backward selection (p\u0026lt;0.05) applied to arrive at final model. HR=Hazard Ratio; CI=Confidence Interval; HS=High School; NA=Not Available; UNK=Unknown\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 3: Multivariate Analysis of \u0026nbsp;subpopulations receiving different treatments and with distinct stages at diagnosis.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003eSubset analysis with the following subset population\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003eMultivariable HR\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(Pediatric vs Adult)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003eChemotherapy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003e0.58 (0.48, 0.71)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003e\u0026lt;.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003eSurgery\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003e0.48 (0.32, 0.72)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003e\u0026lt;.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003eChemotherapy + surgery\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003e0.55 (0.50, 0.61)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003e\u0026lt;.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003eChemo + surgery + radiation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003e0.66 (0.39, 1.11)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003e0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003eNo treatment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003e0.25 (0.14, 0.42)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003e\u0026lt;.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003eStage I\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003e0.48 (0.37, 0.63)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003e\u0026lt;.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003eStage II/III\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003e0.56 (0.50, 0.64)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003e\u0026lt;.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003eStage IV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003e0.60 (0.51, 0.71)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 208px;\"\u003e\n \u003cp\u003e\u0026lt;.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-cancer","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bcan","sideBox":"Learn more about [BMC Cancer](http://bmccancer.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bcan/default.aspx","title":"BMC Cancer","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"osteosarcoma, pediatric, hazard ratio, overall survival, odds ratio","lastPublishedDoi":"10.21203/rs.3.rs-5085447/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5085447/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDifferences in overall survival (OS) between children and adult patients diagnosed with osteosarcoma are poorly understood. The objective of this study is to compare the OS of pediatric and adult patients diagnosed with osteosarcoma, \u0026nbsp;identify prognostic factors associated with OS, and explore factors specifically associated with pediatric patients with osteosarcoma using data gathered from the National Cancer Database (NCDB).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePatients \u0026gt;=1 years old and diagnosed with osteosarcoma between 2004 and 2017 were included in the study. Multivariable Cox regression analysis adjusted for gender, race, income, education, place of living, health insurance status, year of diagnosis, stage of cancer, surgery, chemotherapy, radiation therapy (RT), and immunotherapy was used to assess the association of age with the OS of the patients.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe analysis included 7,890 patients among whom 2,972 (37.7%) were between 1-17 years old. In the multivariable Cox regression analysis, adult patients had worse OS compared with pediatric patients (HR: 1.90; p\u0026lt;.01). When stratified by treatment type, pediatric patients had better OS in several groups. This includes those who received chemotherapy alone (HR: 0.58, p \u0026lt; .01), surgery alone (HR: 0.48, p \u0026lt; .01), surgery plus chemotherapy (HR: 0.55, p \u0026lt; .01), and those who received no treatment (HR: 0.25, p \u0026lt; .01). There was no significant difference in OS between pediatric and adult patients receiving a combination of chemotherapy, surgery, and RT (HR: 0.66, p = 0.11). In analysis stratified by cancer stage, pediatric patients had better OS compared to adult patients at each stage.\u003c/p\u003e\n\u003cp\u003eMultivariable logistic regression analysis revealed that pediatric patients are more likely to be non-white, have insurance, present with unknown/occult stage disease, have poorly differentiated tumors, and receive immunotherapy, chemotherapy, or surgery. Additionally, multivariable Cox regression analysis identified factors associated with improved OS: age, diagnosis between 2011-2015, private insurance, non-metastatic disease, well-differentiated tumors, and receiving chemotherapy or surgery, but not RT.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePediatric patients diagnosed with osteosarcoma had better OS compared to their adult counterparts. Pediatric patients had better OS compared to adults when the analysis was stratified by treatment modality and stage of cancer. More research is necessary to delineate the underlying reason for this difference.\u003c/p\u003e","manuscriptTitle":"Comparison of overall survival of adult and pediatric osteosarcoma patients using the National Cancer Database","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-12-17 16:46:50","doi":"10.21203/rs.3.rs-5085447/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-09-25T11:13:35+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-09-25T07:26:54+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-09-25T07:26:34+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Cancer","date":"2024-09-13T17:38:06+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-cancer","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bcan","sideBox":"Learn more about [BMC Cancer](http://bmccancer.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bcan/default.aspx","title":"BMC Cancer","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"04a0a46b-05c7-4c1f-ba8a-6cf48c827b35","owner":[],"postedDate":"December 17th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-02-24T16:00:46+00:00","versionOfRecord":{"articleIdentity":"rs-5085447","link":"https://doi.org/10.1186/s12885-025-13496-3","journal":{"identity":"bmc-cancer","isVorOnly":false,"title":"BMC Cancer"},"publishedOn":"2025-02-18 15:57:19","publishedOnDateReadable":"February 18th, 2025"},"versionCreatedAt":"2024-12-17 16:46:50","video":"","vorDoi":"10.1186/s12885-025-13496-3","vorDoiUrl":"https://doi.org/10.1186/s12885-025-13496-3","workflowStages":[]},"version":"v1","identity":"rs-5085447","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5085447","identity":"rs-5085447","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}