Epidemiological and clinicopathologic characteristics, and prognostic factors of patients with Extra-skeletal Osteosarcoma

Epidemiological and clinicopathologic characteristics, and prognostic factors of patients with Extra-skeletal Osteosarcoma | 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 Article Epidemiological and clinicopathologic characteristics, and prognostic factors of patients with Extra-skeletal Osteosarcoma Zhengzhong Liu, Fapeng Gao, Li Du, Chenhua Zhu, Yinan Wang, Haixiao Wu, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4072434/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract The aim of this study was to investigate the epidemiological characteristics and prognostic factors of Extra-skeletal Osteosarcoma (ESOS) and to establish and validate a prognostic model. The baseline information and survival outcome of patients was illustrated according to different primary tumor sites. The independent prognostic factors for ESOS were analyzed using univariate and multivariate Cox regression analysis. A nomogram was constructed using these prognostic factors to predict the prognostic survival of patients. Kaplan-Meier method was performed to estimate survival and both log-rank test and Wilcoxon-Breslow-Gehan test were used to compare the survival. A total of 4567 patients with osteosarcoma who met the inclusion criteria were enrolled, including 4317 patients with osteosarcoma of bone and joint origin and 250 patients with ESOS. The 1-, 3-, and 5-year tumor-specific survival rates for ESOS were lower than those for skeletal osteosarcoma. Multivariate Cox analysis showed that older age at diagnosis, distant staging, and presence of bone metastases were independent risk factors affecting patient prognosis, and surgery of the primary site was an independent factor suggesting a better survival outcome. A nomogram was created based on these factors to predict OS at 1, 3 and 5 years in patients with ESOS. An internally validated nomogram consistency index showed satisfactory results between predictions. Primary focus surgery is an important factor in improving survival outcomes in patients with ESOS. The nomogram for predicting the prognostic of patients with ESOS was proved to be favorable accuracy and reliability. Such prognostic nomogram may assist clinicians optimize clinical treatment. Biological sciences/Cancer Health sciences/Diseases Health sciences/Medical research Health sciences/Oncology Health sciences/Pathogenesis Health sciences/Risk factors Extra-skeletal Osteosarcoma Epidemiology Overall survival Nomograms SEER program Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 1 Introduction Extra-skeletal Osteosarcoma (ESOS) stands as a rare malignancy originating in soft tissues and organs, representing a mere 2–4% of osteosarcoma cases and approximately 1% of soft tissue sarcomas[1, 2, 3, 4, 5]. Distinguished by its tumour cells directly producing a bone-like stroma akin to osteosarcoma, ESOS exhibits a histological resemblance to its skeletal counterpart. Nevertheless, this similarity notwithstanding, ESOS diverges by its lack of origin and attachment to adjacent bone structures[6, 7]. In contrast to skeletal osteosarcoma, ESOS afflicts individuals at a later stage in life, boasting a mean onset age of 60.7 years[7, 8]. Predominantly situated within the depths of the trunk, lower limbs, or upper limbs, ESOS manifests as a challenging entity to diagnose due to its pronounced malignancy and extended diagnostic timeline. Regrettably, the prognosis for ESOS is considerably grimmer than that of skeletal osteosarcoma, often accompanied by a higher propensity for metastasis, predominantly involving local lymph nodes, bone, and lung[9, 10]. Since its initial documentation by Wilson in 1941, the optimal management and prognostic evaluation for ESOS have been subjects of intensive investigation[11]. Given its high malignancy and protracted diagnostic journey, surgical tumour excision currently constitutes a pivotal therapeutic approach. The role of chemotherapy in ESOS remains contentious, and while radiotherapy holds limited efficacy, it is generally not a customary recourse for ESOS management[5]. Comparative to osteosarcoma, ESOS patients face a bleaker prognosis, reflected in a suboptimal 5-year overall survival rate of less than 50%[12, 13, 14]. Earlier studies have underscored the significance of prognostic factors like age, tumour grade, tumour size, surgical intervention, and chemotherapy in shaping the outlook of ESOS patients[13, 15]. However, due to ESOS's low incidence rate, the body of literature surrounding it is limited, predominantly comprising case reports and retrospective analyses characterised by modest sample sizes. The comprehensive delineation of ESOS attributes and a holistic assessment of its population-level prognosis remain incomplete. Hence, the establishment of predictive models designed to prognosticate ESOS patient outcomes emerges as an imperative undertaking. Consequently, a comprehensive analysis of Extra-skeletal Osteosarcoma (ESOS) was undertaken, encompassing demographic profiles, overall survival trends, and prognostic attributes. This investigation was grounded in data sourced from the Surveillance, Epidemiology, and End Results (SEER) program. In parallel, a prognostic nomogram model was developed, hinging upon impactful factors intrinsic to ESOS outcomes. 2 Result 2.1 Demographic and clinicopathologic characteristics of patients with ESOS A total of 4,567 osteosarcoma patients satisfying the stipulated inclusion criteria were identified. This comprised 4,317 patients presenting with osteosarcoma originating from bones and joints (C40.0-C41.9), and 250 patients with ESOS. The median ages for osteosarcoma (C40.0-C41.9) and ESOS were 19.0 and 58.0 years, respectively. As presented in Table 1 , appreciable disparities were evident in various demographic and clinicopathologic aspects across the groups. These encompassed age at diagnosis, gender distribution, marital status, tumour grade, as well as T and N stages. Notably, discernible distinctions in treatment modalities emerged between the groups, with a greater proportion of ESOS patients receiving chemotherapy and fewer opting for radiation therapy. Table 1 Demographic and clinicopathologic characteristics of osteosarcoma patients in SEER database. Characteristics Osteosarcoma (All sites) N (%) Osteosarcoma (C40.0-C41.9) N (%) Extraskeletal osteosarcoma (ESOS) N (%) χ 2 P Year of diagnosis 2000–2003 847 (18.5) 799 (18.5) 48 (19.2) 1.081 0.582 2004–2009 1282 (28.1) 1219 (28.2) 63 (25.2) 2010–2020 2438 (53.4) 2299 (53.3) 139 (55.6) Age ≤18 years 2138 (46.8) 2127 (49.3) 11 (4.4) 417.968 50 years 832 (18.2) 670 (15.5) 162 (64.8) Gender Male 2530 (55.4) 2409 (55.8) 121 (48.4) 5.214 0.022 Female 2037 (44.6) 1908 (44.2) 129 (51.6) Marital status Married 1051 (23.0) 914 (21.2) 137 (54.8) 160.941 < 0.001 Unmarried 3406 (74.6) 3304 (76.5) 102 (40.8) Unknown 110 (2.4) 99 (2.3) 11 (4.4) Race White 3413 (74.7) 3209 (74.3) 204 (81.6) 6.712 0.082 Black 697 (15.3) 668 (15.5) 29 (11.6) Others 429 (9.4) 413 (9.6) 16 (6.4) Unknown 28 (0.6) 27 (0.6) 1 (0.4) Median household income $ 75,000 1853 (40.6) 1762 (40.8) 91 (36.4) Unknown 1 (0) 1 (0) 0 (0) Grade Well differentiated; Grade I 192 (4.2) 188 (4.4) 4 (1.6) 17.097 0.002 Moderately differentiated; Grade II 254 (5.6) 243 (5.6) 11 (4.4) Poorly differentiated; Grade III 1029 (22.5) 954 (22.1) 75 (30.0) Undifferentiated; anaplastic; Grade IV 1618 (35.4) 1520 (35.2) 98 (39.2) Unknown 1474 (32.3) 1412 (32.7) 62 (24.8) SEER Stage Localized 1343 (29.4) 1258 (29.1) 85 (34.0) 4.341 0.227 Regional 1352 (29.6) 1291 (29.9) 61 (24.4) Distant 844 (18.5) 797 (18.5) 47 (18.8) Unknown 1028 (22.5) 971 (22.5) 57 (22.8) T stage T1 1197 (26.2) 1164 (27.0) 33 (13.2) 81.673 < 0.001 T2 1664 (36.4) 1573 (36.4) 91 (36.4) T3 123 (2.7) 116 (2.7) 7 (2.8) T4 34 (0.7) 22 (0.5) 12 (4.8) Unknown 1549 (33.9) 1442 (33.4) 107 (42.8) N stage N0 3255 (71.3) 3115 (72.2) 140 (56.0) 30.190 < 0.001 N1 102 (2.2) 94 (2.2) 8 (3.2) Unknown 1210 (26.5) 1108 (25.7) 102 (40.8) Bone metastasis No 2255 (49.4) 2124 (49.2) 131 (52.4) 1.270 0.530 Yes 111 (2.4) 104 (2.4) 7 (2.8) Unknown 2201 (48.2) 2089 (48.4) 112 (44.8) Brain metastasis No 2356 (51.6) 2220 (51.4) 136 (54.4) 1.457 0.483 Yes 9 (0.2) 8 (0.2) 1 (0.4) Unknown 2202 (48.2) 2089 (48.4) 113 (45.2) Liver metastasis No 2350 (51.5) 2215 (51.3) 135 (54.0) 5.307 0.070 Yes 18 (0.4) 15 (0.3) 3 (1.2) Unknown 2199 (48.1) 2087 (48.3) 112 (44.8) Lung metastasis No 1955 (42.8) 1839 (42.6) 116 (46.4) 1.453 0.484 Yes 409 (9.0) 387 (9.0) 22 (8.8) Unknown 2203 (48.2) 2091 (48.4) 112 (44.8) Surgery No 739 (16.2) 709 (16.4) 30 (12.0) 5.011 0.082 Yes 3708 (81.2) 3498 (81.0) 210 (84.0) Unknown 120 (2.6) 110 (2.5) 10 (4.0) Chemotherapy Yes 1031 (22.6) 908 (21.0) 123 (49.2) 107.265 < 0.001 No/Unknown 3536 (77.4) 3409 (79.0) 127 (50.8) Radiation therapy Yes 4115 (90.1) 3929 (91.0) 186 (74.4) 73.131 < 0.001 No/Unknown 452 (9.9) 388 (9.0) 64 (25.6) Table 2 provides a comprehensive listing of patient numbers and detailed demographic, clinicopathologic, and survival data for ESOS, organized in accordance with distinct primary tumour sites. The prevalent primary site for ESOS was the soft tissue (N = 175), particularly in the upper (25 cases) and lower limbs (94 cases), followed by occurrences in the breast (N = 24) and respiratory system (N = 16). Notably, the 5-year overall survival rates stood at 42.4% for patients with primary tumours originating from soft tissue and 34.1% for those originating from the breast. It is of significance to mention that ESOS patients stemming from the nasal cavity and sinus were notably younger, with a mean age of 34.7 years. As indicated in Table 2 , ESOS manifests across diverse systems, each accompanied by distinct treatment strategies and survival outcomes. Table 2 The summarized information of patients with ESOS in SEER database, grouped by primary tumor sites. Site Group Primary tumor site No. of Patients Age Male/ Female Surgery Type Chemotherapy Radiation Therapy Survival Outcome Soft Tissue including Heart C49.0 Conn, subcutaneous, other soft tissue: head, face, neck 5 62.4 (mean) 4/1 Partial resection (5) Yes (0) Yes (1) 1-year OS: 76.0% 3-year OS: 47.1% 5-year OS: 42.4% Median OS: 33.0 months Mean OS: 103.1 months C49.1 Conn, subcutaneous, other soft tissue: upper limb, shoulder 25 55.3 (mean) 12/13 Partial resection (10) Radical excision (9) Amputation (2) No surgery (4) Yes (11) Yes (4) C49.2 Conn, subcutaneous, other soft tissue: lower limb, hip 94 53.0 (mean) 52/42 Partial resection (23) Radical excision (54) Amputation (8) No surgery (7) Unknown (2) Yes (56) Yes (29) C49.3 Conn, subcutaneous, other soft tissue: thorax 15 62.1 (mean) 4/11 Partial resection (5) Radical excision (6) No surgery (4) Yes (9) Yes (2) C49.4 Conn, subcutaneous, other soft tissue: abdomen 4 28; 51; 76; 83 3/1 Partial resection (1) Radical excision (2) Amputation (1) Yes (1) Yes (0) C49.5 Conn, subcutaneous, other soft tissue: pelvis 14 58.1 (mean) 7/7 Partial resection (3) Radical excision (10) No surgery (1) Yes (6) Yes (5) C49.6 Conn, subcutaneous, other soft tissue: trunk, NOS 8 47.6 (mean) 5/3 Partial resection (5) Radical excision (2) No surgery (1) Yes (4) Yes (5) C49.8 Overlap conn, subcutaneous, other soft tissues 1 72 1/0 Radical excision (1) Yes (0) Yes (1) C49.9 Conn, subcutaneous and other soft tissues, NOS 4 63; 68; 67; 20 4/0 Radical excision (1) No surgery (3) Yes (2) Yes (0) C38.0 Heart 5 52.6 (mean) 2/3 Partial remove (3) Debulking (1) Unknown (1) Yes (2) Yes (0) Breast C50.0-C50.9 Breast 24 69.2 (mean) 0/24 Subcutaneous mastectomy (1) Partial mastectomy (6) Total mastectomy (9) Modified radical mastectomy (6) Mastectomy, NOS (1) No surgery (1) Yes (11) Yes (5) 1-year OS: 50.0% 3-year OS: 39.8% 5-year OS: 34.1% Median OS: 12.0 months Mean OS: 69.6 months Respiratory System C30.0-Nasal cavity C31.0-Maxillary sinus C31.1-Ethmoid sinus 9 34.7 (mean) 6/3 Total remove (4) Partial remove (1) Radical surgery (2) Excisional biopsy (1) Unknown (1) Yes (6) Yes (5) 1-year OS: 54.5% 3-year OS: 37.4% Median OS: 19.0 months Mean OS: 98.2 months C34.0-C34.9 Lung and Bronchus 5 77.2 (mean) 4/1 Lobectomy with lymph node dissection (1) No surgery (4) Yes (1) Yes (1) C38.4 Pleura 1 89 1/0 Total remove (1) Yes (0) Yes (0) C38.3 Mediastinum 1 57 1/0 Radical surgery (1) Yes (1) Yes (0) Digestive System Liver and Intrahepatic Bile Duct C22.0 Liver 3 70; 19; 56 1/2 Left lobectomy (1) Wedge or segmental resection (1) No surgery (1) Yes (3) Yes (0) 1-year OS: 55.6% 3-year OS: 41.7% Median OS: 23.0 months Mean OS: 98.7 months C48.0 Retroperitoneum 4 64; 49; 39; 72 3/1 Partial remove (1) Radical surgery (2) Excisional biopsy (1) Yes (1) Yes (1) C48.1 Specified parts of peritoneum 1 61 0/1 Unknown (1) Yes (1) Yes (0) Colon and Rectum C18.0 Cecum 1 43 1/0 Colectomy/hemicolectomy (1) Yes (0) Yes (0) Female Genital System C54.0-C54.9 Corpus Uteri C55.9 Uterus, NOS 4 53; 57; 54; 48 0/4 Hysterectomy (1) Total hysterectomy without removal of tube and ovary (3) Yes (1) Yes (0) Median OS: 4.0 months Mean OS: 11.1 months C56.9 Ovary 3 75; 29; 65 0/3 Unilateral oophorectomy (1) Debulking (2) Yes (1) Yes (0) Urinary System C67.0-C67.9 Urinary Bladder 4 90; 71; 57; 68 3/1 Excisional biopsy (1) Polypectomy (1) Radical cystectomy (1) No surgery (1) Yes (3) Yes (0) Mean OS: 16.8 months C64.9-Kidney, NOS 1 39 1/0 No surgery (1) Yes (0) Yes (0) Oral Cavity and Pharynx C09.9 Tonsil, NOS 1 49 1/0 Laryngectomy (1) Yes (0) Yes (0) Mean OS: 140.4 months C05.0 Hard palate 3 39; 44; 25 1/2 Radical excision (3) Yes (1) Yes (1) C03.1 Lower gum 1 58 0/1 Radical excision (1) Yes (1) Yes (1) Brain and Other Nervous System C71.3 Parietal lobe 1 50 0/1 Unknown (1) Yes (0) Yes (1) 22 months (A) C71.4 Occipital lobe 1 5 0/1 Unknown (1) Yes (1) Yes (1) 16 months (D) C72.0 Spinal cord 1 26 0/1 No surgery (1) Yes (0) Yes (0) 224 months (A) Male Genital System C61.9 Prostate gland 1 60 1/0 No surgery (1) Yes (1) Yes (0) 9 months (D) C63.1 Spermatic cord 1 52 1/0 Total remove (1) Yes (0) Yes (0) 26 months (D) Skin excluding Basal and Squamous C44.4 Skin of scalp and neck 1 82 1/0 Mohs with 1-cm margin or less (1) Yes (0) Yes (0) 59 months (D) Miscellaneous C80.9 Unknown primary site 3 66; 59; 68 1/2 Unknown (1) Yes (3) Yes (1) 5 months (D) 8 months (D) 2 months (D) 2.2 Epidemiological performance of patients with ESOS To delve into the extent of the cancer burden, the 20-year limited-duration prevalence rates for osteosarcoma and ESOS were computed, incorporating adjustments based on the 2000 US standard population. Illustrated in Fig. 2 A, the prevalence of osteosarcoma was 0.00028% in the year 2000, rising notably to 0.00294% by 2019. Correspondingly, the prevalence of ESOS exhibited a slight increment from 0.00002% in 2000 to 0.00011% in 2019. Given the prevalence's potential to mirror the ascending incidence and relatively indolent behaviour of cancers, the incidence and survival rates of both osteosarcoma and ESOS were subjected to calculation. The yearly age-adjusted incidence rate for ESOS hovered at approximately 0.02 per 100,000 individuals, displaying a lack of significant alteration (Fig. 2 B and Supplementary Fig. 1). Figure 2 C and Supplementary Fig. 2 delineate the age-adjusted mortality rates for ESOS. In 2001, the lowest mortality rate was recorded at 0.0027 per 100,000 individuals, while the peak rate reached 0.0132 per 100,000 in 2011. As exhibited in Supplementary Fig. 2, no discernible trend shift in mortality rates was detected among ESOS patients. Moreover, Fig. 2 D provides an exposition of the observed survival and cancer-specific survival rates for ESOS. Both observed survival and cancer-specific survival rates for ESOS proved inferior to their counterparts in bone-originating osteosarcoma. Notably, the 1-year, 3-year, and 5-year cancer-specific survival rates for osteosarcoma (C40.0-C41.9) stood at 88.0%, 68.7%, and 61.3% respectively, whereas the corresponding rates for ESOS patients were 71.5%, 49.4%, and 45.7%. 2.3 Prognosis and independent prognostic factors of ESOS The outcomes of the Cox proportional hazard regression analysis are presented in Table 3 . As discerned through univariate analysis, factors influencing ESOS survival encompassed age, primary tumour site, clinical stage, T stage, N stage, the presence of bone metastasis, brain metastasis, liver metastasis, lung metastasis, and the implementation of surgical intervention. Upon adjusting for confounding variables, the multivariate analysis revealed that advancing age at diagnosis (HR = 1.03, 95%CI: 1.02–1.04; P < 0.001), distant stage (HR = 3.04, 95%CI: 1.66–5.58; P < 0.001), and the presence of bone metastasis (HR = 4.71, 95%CI: 1.95–11.39; P = 0.001) stood as independent adverse prognostic factors. Notably, primary tumour surgery (HR = 0.19, 95%CI: 0.12–0.29; P < 0.001) emerged as an autonomous factor indicative of enhanced survival outcomes. Table 3 The prognostic factors of patients with extraskeletal osteosarcoma. Characteristics Univariate Multivariate HR (95% CI) P value HR (95% CI) P value Age 1.027 (1.017–1.036) < 0.001 1.032 (1.023–1.042) < 0.001 Gender Male 1.00 (Reference) Female 1.094 (0.792–1.511) 0.586 Marital status Married 1.00 (Reference) Unmarried 0.974 (0.698–1.360) 0.878 Unknown 1.277 (0.589–2.767) 0.536 Race White 1.00 (Reference) Black 0.859 (0.517–1.428) 0.559 Others 0.82 (0.401–1.678) 0.588 Unknown NA 0.959 Median household income $ 75,000 0.671 (0.447–1.009) 0.056 Primary tumor site Conn, subcutaneous, other soft tissue 1.00 (Reference) 1.00 (Reference) Other sites 1.637 (1.171–2.288) 0.004 1.112 (0.699–1.769) 0.653 Grade Well differentiated; Grade I 1.00 (Reference) Moderately differentiated; Grade II NA 0.953 Poorly differentiated; Grade III 1.033 (0.318–3.357) 0.956 Undifferentiated; anaplastic; Grade IV 1.387 (0.436–4.415) 0.580 Unknown 1.728 (0.534–5.592) 0.361 SEER Stage Localized 1.00 (Reference) 1.00 (Reference) Regional 1.666 (1.046–2.654) 0.032 1.442 (0.874–2.379) 0.152 Distant 3.625 (2.271–5.787) < 0.001 3.042 (1.658–5.579) < 0.001 Unknown 1.598 (1.010–2.527) 0.045 0.858 (0.447–1.647) 0.645 T stage T1 1.00 (Reference) 1.00 (Reference) T2 2.684 (1.328–5.424) 0.006 1.525 (0.776–2.998) 0.221 T3 2.995 (0.805–11.145) 0.102 0.808 (0.208–3.142) 0.759 T4 3.492 (1.163–10.486) 0.026 1.797 (0.594–5.433) 0.299 Unknown 3.071 (1.536–6.143) 0.002 1.300 (0.499–3.384) 0.591 N stage N0 1.00 (Reference) 1.00 (Reference) N1 2.222 (1.018–4.848) 0.045 1.685 (0.617–4.602) 0.309 Unknown 1.375 (0.986–1.918) 0.061 1.597 (0.782–3.264) 0.199 Bone metastasis No 1.00 (Reference) 1.00 (Reference) Yes 4.617 (2.103–10.14) < 0.001 4.711 (1.948–11.393) 0.001 Unknown 1.078 (0.766–1.516) 0.667 18.823 (0.002-168650.242) 0.527 Brain metastasis No 1.00 (Reference) 1.00 (Reference) Yes 41.579 (4.979–347.25) 0.001 NA NA Unknown 1.004 (0.719–1.402) 0.980 0.061 (0-538.293) 0.546 Liver metastasis No 1.00 (Reference) 1.00 (Reference) Yes 4.368 (1.37-13.932) 0.013 0.932 (0.154–5.652) 0.939 Unknown 1.031 (0.737–1.444) 0.858 NA NA Lung metastasis No 1.00 (Reference) 1.00 (Reference) Yes 2.459 (1.44–4.202) 0.001 NA NA Unknown 1.168 (0.817–1.672) 0.395 0.858 (0.429–1.715) 0.665 Surgery No 1.00 (Reference) 1.00 (Reference) Yes 0.269 (0.175–0.415) < 0.001 0.185 (0.117–0.293) < 0.001 Unknown 0.58 (0.261–1.288) 0.181 0.433 (0.153–1.225) 0.115 Chemotherapy Yes 1.00 (Reference) No/Unknown 0.734 (0.531–1.015) 0.062 Radiation therapy Yes 1.00 (Reference) No/Unknown 0.935 (0.641–1.363) 0.727 The examination of the impact of diverse surgical approaches on survival outcomes across different primary tumour sites was undertaken via subgroup analyses. As delineated in Table 4 , observable variations in survival durations were noted among patients subjected to distinct surgical interventions, with particular prominence within the subset of patients presenting with tumours originating from soft tissue (P-value < 0.001). Within the 'Soft Tissue including Heart' subgroup, the mean overall survival (OS) extended to 123.3 (89.8-156.7) months for individuals undergoing partial resection and 117.6 (92.2-143.1) months for those undergoing radical excision. Notably, patients subjected to amputation exhibited a considerably less favourable mean OS of 21.5 (10.3–32.6) months. The survival trajectories of the total cohort, as well as those for patients harboring distinct primary tumour sites, are graphically depicted in Fig. 3 . Table 4 The summarized information of survival outcome in patients with ESOS in SEER database, grouped by primary tumor sites and surgery types. Site Group Surgery Type Mean OS [95%CI] (months) Median OS [95%CI] (months) 1-year OS (%) 3-year OS (%) 5-year OS (%) Log-rank P-value Breslow P-value Soft Tissue including Heart No surgery 30.3 (1.8–58.7) 4.0 (1.0–12.0) 22.5 7.5 7.5 < 0.001 < 0.001 Partial resection 123.3 (89.8-156.7) 88.0 (34.0-173.0) 78.0 60.5 52.1 Radical excision 117.6 (92.2-143.1) 38.0 (24.0-174.0) 82.6 50.2 48.7 Amputation 21.5 (10.3–32.6) 15.0 (5.0–29.0) 54.5 18.2 NA Unknown or others 22.3 (8.7–35.8) 21.0 (4.0–37.0) 75.0 25.0 0 Breast No surgery or others 18.0 (NA) 3.0 (1.0–3.0) 33.3 33.3 NA 0.699 0.599 Partial mastectomy 89.4 (17.5-161.3) 36.0 (1.0–36.0) 66.7 44.4 44.4 Total/radical mastectomy 59.3 (16.6–102.0) 12.0 (6.0-143.0) 46.7 38.9 29.2 Respiratory System No surgery 7.5 (NA) 2.0 (0.0–19.0) 25 0 0 0.044 0.056 Radical surgery/total removal 114.3 (27.4-201.1) 21.0 (2.0–21.0) 58.3 43.8 43.8 Unknown or others 20.3 (10.5–30.0) NA 75 NA NA Digestive System No surgery or unknown 15.5 (0.8–30.2) 8 (8.0–23.0) 50 0 0 0.454 0.612 With surgery 129.6 (49.6-209.5) NA 57.1 57.1 57.1 Other sites No surgery or unknown 54.3 (NA) 8.0 (0.0–16.0) 33.3 22.2 22.2 0.451 0.391 With surgery 59.6 (15.3-103.9) 26.0 (2.0–75.0) 51.0 36.4 27.3 2.4 Construction and validation of prognostic nomogram of ESOS Inclusion of the aforementioned independent prognostic factors was undertaken for the formulation of the predictive nomogram, as illustrated in Fig. 4 A. The temporal receiver operating characteristic (ROC) curves in Fig. 4 B depict commendable discriminatory capacity of the model, with corresponding area under the curve (AUC) values at 1-year, 3-year, and 5-year intervals standing at 0.848, 0.793, and 0.805 respectively. Evaluation of calibration prowess, as illustrated in Fig. 4 C, showcased a harmonious alignment between anticipated and observed probabilities, with all calibration curves closely mirroring the 45-degree reference line. Importantly, this predictive fidelity extended to the validation cohort, as corroborated by Figs. 4 D and 3 E. In this context, the nomogram consistently exhibited pronounced discriminatory strength and adept calibration (Fig. 4 D-E). Noteworthy AUC values for the nomogram across the 1-year, 3-year, and 5-year spans were observed at 0.778, 0.800, and 0.748 correspondingly. To furnish a visual and comprehensive validation of our predictive model, we classified all ESOS patients into high-risk and low-risk groups in accordance with their assigned risk scores. Figure 5 , comprising Fig. 5 A for the construction cohort and Fig. 5 B for the validation cohort, encompasses scatter plots illustrating the juxtaposition of risk scores and survival status for ESOS patients, accompanied by corresponding predictive factors information. 3 Discussion Our investigation presents an analysis concerning a population-based cohort of ESOS patients derived from the SEER database. It delineates the incidence and prevalence of these patients and characterizes the pattern of survival. In this study grounded in the population, we discerned that the age-adjusted annual prevalence of ESOS escalated from 0.02 per 100,000 in the year 2000 to 0.11 per 100,000 in 2019, signifying a remarkable 5.5-fold surge. Meanwhile, the incidence and mortality of this condition exhibited no noteworthy alteration. Considering that prevalence encompasses both incidence and survival, one may deduce that the overall survival rate of ESOS patients experienced a slight enhancement during this temporal span. The broad-spectrum therapeutic approaches might plausibly contribute to the advancement in prognosis for ESOS patients. The preeminence of the surgical cohort over their non-surgical counterparts within this study underscores the pivotal role of treatment, particularly surgical intervention. Despite the prognosis for ESOS patients remaining relatively unfavourable, there is discernible improvement in overall survival over the temporal course, mirroring advancements in anticancer therapeutics. The patients afflicted by ESOS exhibited an age range of 47 to 61 years, with an average age of 60.7[8]. Within the present study, the proportion of patients surpassing 50 years of age reached 64.8% among ESOS cases, while it stood at a mere 18.2% for those grappling with osseous osteosarcoma. In alignment with prior reports, advanced age emerged as an independent prognostic peril[16, 17]. This phenomenon could be attributed to the relatively diminished tolerance towards comprehensive therapeutic regimens among elderly patients. Furthermore, older patients are prone to multiple comorbidities, including cardiovascular ailments and diabetes, which are known to exacerbate their prognosis. Notably, there existed no appreciable variance in the male-to-female ratio within the ESOS cohort. In our study, the male-to-female ratio for ESOS closely approximated 1:1, a proportion akin to previously documented observations[16]. Intriguingly, within our dataset, 12.4% of ESOS cases emanated from the female breast and reproductive organs, whereas there existed a solitary instance occurring within the male reproductive organ. This incongruity could potentially be ascribed to the annual influx of cases into the system. ESOS, by its nature, presents an unfavorable prognosis. According to Chung et al.[17], patients diagnosed with ESOS exhibited a three-year mortality rate exceeding 50%. A European multicenter study involving 266 ESOS patients reported a five-year overall survival rate of 47%[14]. Our study yielded similar findings, with corresponding three-year and five-year overall survival rates of 49.4% and 45.7%, respectively. The potential for enhanced prognosis through primary lesion resection by means of surgical intervention has been documented[5, 13, 14, 18, 19, 20]. Goldstein et al.[21] concluded that complete resection stood as the singular positive prognostic determinant for ESOS. In our current investigation, a noteworthy 84% of ESOS patients underwent surgical procedures, emerging as an independent prognostic factor associated with favorable survival outcomes in multivariate Cox regression analysis. Within the 'Soft Tissue including Heart' subgroup, patients subjected to surgery evidenced one-, three-, and five-year overall survival rates of 78.0%, 60.5%, and 52.1%, respectively. These figures notably surpassed those observed in non-surgically treated patients (22.5%, 7.5%, and 7.5%, respectively). Our findings resonate with prior research conducted by others[15, 22]. Additionally, survival prognoses exhibit variation when stratified according to originating systemic tissues or organs. In our study, 250 ESOS patients were distributed across 11 systemic tissues or organs, with 70% of cases manifesting in the 'Soft Tissue including Heart' category (with over a third localized in the lower limbs). Fewer instances occurred within other systemic tissues, comprising 24 cases within breast tissues and 16 cases in the respiratory system. Notably, patients with ESOS originating in the 'Soft Tissue including Heart' category demonstrated a median survival of 33.0 months, markedly outperforming their counterparts originating from other sites (12.0 months for breast and 19.9 months for lung, respectively). This concurs with previously reported findings[4, 8, 23, 24, 25]. Superficial ESOS masses, being more readily detectable, facilitate early-stage diagnosis and subsequent intervention. Moreover, due to their comparatively modest vascular and lymphatic networks, the likelihood of local progression and distinct metastasis diminishes, thereby enhancing patients' prognostic survival rates and reducing the incidence of local recurrence post-treatment[7, 16, 19, 26, 27, 28, 29]. Additionally, ESOS originating from diverse systemic sites exhibit disparate tissue origins, consequently engendering distinct biological behaviours and, by extension, discernible differences in survival outcomes. ESOS shares a nomenclature and histological resemblances with osseous osteosarcoma, yet diverges in terms of occurrence sites and clinicopathological attributes. Regrettably, ESOS displays a notable insensitivity to chemotherapy, as evidenced in previous reports[5, 18, 30, 31]. The role of chemotherapy in managing ESOS patients remains a contentious topic[13, 14, 32, 33]. In the context of localised ESOS, the amalgamation of surgical intervention with diverse chemotherapy regimens appears to hold promise for enhancing overall survival[21, 34]. A comprehensive examination by Longhi et al.[14] across multiple centres illustrated elevated survival rates among individuals subjected to perioperative chemotherapy, with an inclination towards potential effectiveness of osteosarcoma chemotherapy protocols. Conversely, Lin Qi et al.[35] partitioned 310 ESOS patients into cohorts with and without chemotherapy exposure, arriving at the conclusion that the chemotherapy group didn't manifest significant prognostic amelioration. For advanced ESOS cases marked by distant metastases, assorted chemotherapeutic protocols offer feasible alternatives, yet these regimens fail to impart a survival advantage[5, 36]. Furthermore, given the advanced age demographic and potential for systemic dysfunction among ESOS patients, the associated complexities of chemotherapy pose an unsuitable proposition for elderly cohorts[14]. Consequently, there exists a rationale to abstain from routinely endorsing chemotherapy as a standard ESOS treatment[37]. Within this study, the utilization of chemotherapy accounted for 49.2%, a percentage notably lower than that of surgery. Multivariate Cox regression analysis corroborated that chemotherapy failed to emerge as an independent, favorable prognostic factor. The therapeutic scope of radiotherapy within ESOS remains circumscribed, resulting in its non-routine adoption[18, 30, 38]. Generally, radiotherapy serves a palliative function for ESOS patients either burdened with inoperable primary lesions or grappling with metastatic afflictions[31, 34, 39, 40]. The coupling of surgical intervention with radiotherapy has demonstrated efficacy in diminishing tumour size and local recurrence rates. However, it falls short of significantly influencing ESOS prognosis[15, 16]. Wang Hao-tong et al.[15] demonstrated an augmentation in the overall survival rate among patients harbouring ESOS with surgically positive margins who underwent radiotherapy. Within our study, over two-thirds of ESOS patients received radiotherapy, a practice ostensibly aimed at curtailing tumour recurrence and attaining negative surgical margins. ESOS represents an exceedingly uncommon malignancy, marked by a dearth of clinical evidence elucidating its prognosis. Furthermore, prior investigations have often concentrated on therapeutic aspects, neglecting the utilization of a nomogram for prognostic prediction[14]. Thus, our initiative encompassed the construction of a nomogram, designed to prognosticate outcomes for ESOS patients. Following univariate and multivariate Cox regression analysis, four key variables emerged as predictive factors: advanced age at diagnosis, metastatic disease stage, the presence of bone metastasis, and primary tumour surgical intervention. The validation of this nomogram underscored its robust discriminative and calibration capabilities. The visually intuitive format of the nomogram aptly conveys predictive model outcomes, simplifying the intricate task of simultaneous prognostic assessment. This tool not only offers a straightforward and precise means of prognosticating outcomes for ESOS patients, but also equips clinicians with a point of reference to inform subsequent medical decisions. While our study shares limitations akin to preceding research endeavours, its retrospective design being one. Future prospects necessitate prospective randomised clinical trials to furnish high-calibre clinical evidence for application. Additionally, the SEER database omits certain data points, including tumour size, growth depth, and resection specimen margin status. Neglecting these factors could potentially overlook facets with bearing upon patient prognosis. It is noteworthy, however, that our present study holds the distinction of being the most expansive of its kind, and the first to pioneer a survival prognostic model for ESOS. As the database accumulates a greater corpus of cases, this to a considerable extent addresses the scarcity of ESOS studies, thereby furnishing a more comprehensive epidemiological perspective. In conclusion, our retrospective analysis of a sizeable, population-based, single-institution dataset offers insights into the distinguishing features of ESOS compared to osseous osteosarcoma. Discerned through our investigation, advanced age at diagnosis, distant disease stage, and the presence of bone metastasis independently emerged as adverse prognostic determinants, while primary tumour excision surgery displayed potential to enhance ESOS patient outcomes. Our observations also indicate that neither radiotherapy nor chemotherapy confers survival advantages in ESOS cases. Thus, our findings advocate for the prioritisation of primary lesion excision surgery in ESOS, coupled with adjuvant radiotherapy contingent on individual patient circumstances. Furthermore, the employment of our nomogram aids clinicians in anticipating patient prognoses, facilitating the tailoring of treatment strategies accordingly. 4 Materials and Methods 4.1 Data sources 4.1.1 Data Employed for Characterization Description, Identification of Prognostic Factors, and Nomogram Construction (Case Compilation); Data Utilized for Age-Adjusted Incidence Estimation of Osteosarcoma; Data Employed for Depicting Osteosarcoma Survival Outcomes : Surveillance, Epidemiology, and End Results (SEER) Program ( www.seer.cancer.gov ) SEER*Stat Database: Incidence - SEER Research Data, 17 Registries, Nov 2022 Sub (2000–2020) - Linked To County Attributes - Time Dependent (1990–2021) Income/Rurality, 1969–2021 Counties, National Cancer Institute, DCCPS, Surveillance Research Program, released April 2023, based on the November 2022 submission. 4.1.2 Data used for calculating the prevalence of osteosarcoma : Surveillance, Epidemiology, and End Results (SEER) Program ( www.seer.cancer.gov ) SEER*Stat Database: Incidence - SEER Research Data, 17 Registries, Nov 2022 Sub (2000–2020), National Cancer Institute, DCCPS, Surveillance Research Program, released April 2023, based on the November 2022 submission. 4.1.3 Data used for estimating the age-adjusted mortality of osteosarcoma : Surveillance, Epidemiology, and End Results (SEER) Program ( www.seer.cancer.gov ) SEER*Stat Database: Incidence-Based Mortality - SEER Research Data, 17 Registries, Nov 2022 Sub (2000–2020) - Linked to County Attributes - Time Dependent (1990–2021) Income/Rurality, 1969–2021 Counties, National Cancer Institute, DCCPS, Surveillance Research Program, released April 2023, based on the November 2022 submission. 4.2 Patient selection As depicted in Fig. 1 , the variable 'AYA site recode 2020 Revision' within the SEER program was limited to '4.1 osteosarcoma' for the purpose of selecting osteosarcoma patients from the SEER database. Patients diagnosed between the years 2000 and 2020 were initially encompassed. Subsequently, those patients afflicted with multiple malignant primary cancers and individuals diagnosed posthumously or via death certificate were excluded from consideration. Ultimately, a total cohort of 4,567 osteosarcoma patients was included for the present study. According to the 'Primary Site - labeled' variable, patients were categorised into two groups based on the primary site of the tumour: osteosarcoma patients with tumours originating from bones and joints, designated as the 'osteosarcoma (C40.0-C41.9)' group; osteosarcoma patients with tumours originating from sites beyond the skeletal framework, defined as the 'extra-skeletal osteosarcoma (ESOS)' group. 4.3 Statistics analysis Patient characteristics were presented as categorical variables, and distinctions between the groups were evaluated using Pearson's chi-squared test within IBM SPSS Statistics (version 26.0, Armonk, NY, USA). Epidemiological data pertaining to osteosarcoma (prevalence, incidence, mortality, and survival) were computed using SEER software (version 8.4.1), with data visualisation performed using GraphPad Prism (version 8.0.2). In the current investigation, prevalence, incidence, and mortality rates were adjusted by employing weighted proportions derived from the corresponding age groups within the 2000 US standard population, thereby mitigating the confounding influence of age.Overall survival (OS) encompassed the interval from the point of diagnosis until death from any cause, encompassing both causes attributed to cancer and those unrelated to cancer. The estimation of survival was undertaken using the Kaplan-Meier (KM) method, while the comparison of curves between distinct groups employed both the Mantel-Cox (log-rank) and Wilcoxon-Breslow-Gehan tests. The identification of independent prognostic factors among ESOS patients was achieved through the application of Cox proportional hazard regression analysis. Variables displaying a P-value below 0.05 in the univariate analysis were subjected to further scrutiny via multivariate regression analysis. The entirety of ESOS patients was randomly partitioned into construction and validation cohorts at a ratio of 7:3. The assessment of the prognostic nomogram's efficacy was conducted via discrimination and calibration analyses. Temporal receiver operating characteristic (tROC) curves were constructed, with corresponding area under the curve (AUC) values computed at intervals of 1, 3, and 5 years. The evaluation of the nomogram's calibration capacity was performed using calibration curves. The creation and subsequent validation of the prognostic nomogram were undertaken within R version 4.2.1 ( http://www.r-project.org/ ). Abbreviations AUC Area under the curve CI Confidence interval DFS Disease-free survival ESOS Extra-skeletal Osteosarcoma HR Ratio OS Overall survival ROC Receiver operating characteristic SD Standard deviation SEER Surveillance Epidemiology and End Results Declarations 6 Author Contributions Conceptualization: Chao Zhang and Zheng Liu; methodology: Zheng Liu , Zhengzhong Liu and Fapeng Gao; software: Zheng Liu and Li Du; investigation: Chenhua Zhu and Yinan Wang; writing-original draft preparation: Zheng Liu, Zhengzhong Liu and Li Du; writing-review and editing: Elmar R. Musaev; visualization: Haixiao Wu and Jun Wang; supervision: Chao Zhang. The work reported in the paper has been performed by the authors, unless clearly specified in the text. All authors have read and agreed to the published version of the manuscript. 7 Acknowledgments The authors acknowledged the contributions made by the National Cancer Institute and the Surveillance, Epidemiology, and End Results (SEER) Program tumor registries in the creation of the SEER database. 8 Conflict of Interest All authors have read and approved the final submitted manuscript. Each author certifies that he or she has no commercial associations (e.g., consultancies, stock ownership, equity interest, patent/licensing arrangements, etc.) that might pose a conflict of interest in connection with the submitted article. Institutional review board approval was not needed for this study and therefore not obtained prior to initiation. 9 Ethics statement The study was conducted in accordance with the Declaration of Helsinki while ethical board approval was not required because the SEER program provides public domain data without personal medical identifiers. 10 Consent The study was conducted in accordance with the Declaration of Helsinki while ethical board approval was not required because the SEER program provides public domain data without personal medical identifiers. The data used and analyzed in this study are available in the Surveillance, Epidemiology, and End Results (SEER) Database of the National Cancer Institute (http://seer.cancer.gov). Further information is available from the corresponding author upon request. 11 Funding The present study was sponsored by Joint Guidance Project of Provincial Natural Science Foundation (LH2020H119), Heilongjiang Medical and Health Research Project (2020-257), and Traditional Chinese medicine research project in Heilongjiang Province (ZHY2020-066). 12 Data availability statement The datasets used and/or analysed during the current study available from the corresponding author on reasonable request. References Bane BL, Evans HL, Ro JY, Carrasco CH, Grignon DJ, Benjamin RS and Ayala AG. Extraskeletal osteosarcoma. A clinicopathologic review of 26 cases. Cancer-Am Cancer Soc. 1990; 65(12):2762–2770. Thampi S, Matthay KK, Boscardin WJ, Goldsby R and DuBois SG. Clinical Features and Outcomes Differ between Skeletal and Extraskeletal Osteosarcoma. Sarcoma. 2014; 2014:902620. Nie X, Fu W, Li C, Lu L and Li W. 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J Thorac Dis. 2017; 9(12):E1088-E1095. Torigoe T, Yazawa Y, Takagi T, Terakado A and Kurosawa H. Extraskeletal osteosarcoma in Japan: multiinstitutional study of 20 patients from the Japanese Musculoskeletal Oncology Group. J Orthop Sci. 2007; 12(5):424–429. Qi L, Wan L, Ren X, Zhang W, Tu C and Li Z. The Role of Chemotherapy in Extraskeletal Osteosarcoma: A Propensity Score Analysis of the Surveillance Epidemiology and End Results (SEER) Database. Med Sci Monitor. 2020; 26:e925107. Hui J, Zhao Y, Zhang L, Lin J and Zhao H. Primary orbital extraskeletal osteosarcoma and review of literature. Bmc Ophthalmol. 2020; 20(1):425. Heng M, Gupta A, Chung PW, Healey JH, Vaynrub M, Rose PS, Houdek MT, Lin PP, Bishop AJ, Hornicek FJ, Chen YL, Lozano-Calderon S and Holt GE, et al. The role of chemotherapy and radiotherapy in localized extraskeletal osteosarcoma. Eur J Cancer. 2020; 125:130–141. Wiklund TA, Blomqvist CP, Raty J, Elomaa I, Rissanen P and Miettinen M. Postirradiation sarcoma. Analysis of a nationwide cancer registry material. Cancer-Am Cancer Soc. 1991; 68(3):524–531. Hoch M, Ali S, Agrawal S, Wang C and Khurana JS. Extraskeletal osteosarcoma: a case report and review of the literature. J Radiol Case Rep. 2013; 7(7):15–23. Luczynska E, Kasperkiewicz H, Domalik A, Cwierz A and Bobek-Billewicz B. Myositis ossificans mimicking sarcoma, the importance of diagnostic imaging - case report. Pol J Radiol. 2014; 79:228–232. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted 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. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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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-4072434","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":283839499,"identity":"8f4caa4d-6fb0-4438-b21c-0a613a11ca96","order_by":0,"name":"Zhengzhong Liu","email":"","orcid":"","institution":"Department of Orthopedics, Heilongjiang province Hospital, Harbin, Heilongjiang province","correspondingAuthor":false,"prefix":"","firstName":"Zhengzhong","middleName":"","lastName":"Liu","suffix":""},{"id":283839501,"identity":"07d698f1-b8a2-457b-84cd-b3ffba3d433c","order_by":1,"name":"Fapeng Gao","email":"","orcid":"","institution":"Department of Orthopedics, Heilongjiang province Hospital, Harbin, Heilongjiang province","correspondingAuthor":false,"prefix":"","firstName":"Fapeng","middleName":"","lastName":"Gao","suffix":""},{"id":283839503,"identity":"cd4ebf95-4097-4258-b945-7a17999f2a05","order_by":2,"name":"Li Du","email":"","orcid":"","institution":"Department of Hospital-Acquired Infection Control, The Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, Guangdong province","correspondingAuthor":false,"prefix":"","firstName":"Li","middleName":"","lastName":"Du","suffix":""},{"id":283839505,"identity":"1ba521b4-3e9a-4eed-aa74-514970e0f0f9","order_by":3,"name":"Chenhua Zhu","email":"","orcid":"","institution":"Sun Yat-sen University School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Chenhua","middleName":"","lastName":"Zhu","suffix":""},{"id":283839511,"identity":"978672f1-b865-4e72-b81c-ca1d67ad759e","order_by":4,"name":"Yinan Wang","email":"","orcid":"","institution":"Sun Yat-sen University School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Yinan","middleName":"","lastName":"Wang","suffix":""},{"id":283839513,"identity":"553d2006-7f4d-4eea-9c91-31f08057eef9","order_by":5,"name":"Haixiao Wu","email":"","orcid":"","institution":"Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer","correspondingAuthor":false,"prefix":"","firstName":"Haixiao","middleName":"","lastName":"Wu","suffix":""},{"id":283839515,"identity":"7292f65b-7bb5-4342-8a27-b1aed02cb2c7","order_by":6,"name":"Elmar R. Musaev","email":"","orcid":"","institution":"Moscow Oncological Hospital No. 62 of the Moscow Department of Health, 27, Istra, p/o Stepanovskoe, Krasnogorskij Region, Moskovskaya oblast, Russia.","correspondingAuthor":false,"prefix":"","firstName":"Elmar","middleName":"R.","lastName":"Musaev","suffix":""},{"id":283839516,"identity":"41208f4c-3343-4fd2-b405-16d064aa9d34","order_by":7,"name":"Jun Wang","email":"","orcid":"","institution":"Department of Oncology, Radiology and Nuclear Medicine, Medical Institute of Peoples' Friendship University of Russia, Moscow, Russia","correspondingAuthor":false,"prefix":"","firstName":"Jun","middleName":"","lastName":"Wang","suffix":""},{"id":283839517,"identity":"76bef8b1-c6cd-4642-880f-b64f4582bcaf","order_by":8,"name":"Chao Zhang","email":"","orcid":"","institution":"Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer","correspondingAuthor":false,"prefix":"","firstName":"Chao","middleName":"","lastName":"Zhang","suffix":""},{"id":283839518,"identity":"a51d8172-69d1-4230-825e-6515eae54923","order_by":9,"name":"Zheng Liu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA20lEQVRIiWNgGAWjYBACPmYGBmYQg429ASyQQFALG0wLH88BYrUwQLXISSQQq4Wdx/hzQcUduzbJ588kf7bV5TGwHz66Ab/DeAyMZ5x5ltwmnWMmzdt2uJiBJy3tBiEtyUCVyWzSOWzSjG0HEhskeMwIajnM+w+oRfI42GFEaTFs5m04bMcmwWAmwdvGTIwWtmJmnmOHE9h4coytec4dTmwj5Bd+/sObP/PUHLaXbz/+8OaPsrrEfvbDx/BqgYHEBgYGFgmwvcQoBwF7IGb+QKzqUTAKRsEoGFkAAE1BQQGu26yzAAAAAElFTkSuQmCC","orcid":"","institution":"Department of Orthopedics, The Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, Guangdong province","correspondingAuthor":true,"prefix":"","firstName":"Zheng","middleName":"","lastName":"Liu","suffix":""}],"badges":[],"createdAt":"2024-03-11 09:35:40","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4072434/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4072434/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":53745452,"identity":"432be674-5498-4494-b11f-d61f2ca4d9e9","added_by":"auto","created_at":"2024-03-29 17:40:02","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":197880,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe detailed flow-chart for patient selection in the present study.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"image1.png","url":"https://assets-eu.researchsquare.com/files/rs-4072434/v1/4685a2565e2b42f5f7285a3a.png"},{"id":53745939,"identity":"7b8a710d-64df-4d15-a2f6-da05911a1b16","added_by":"auto","created_at":"2024-03-29 17:48:02","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":194301,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe epidemiological performance of patients with ESOS. \u003c/strong\u003e(A) The 20-Year limited-duration prevalence of osseous osteosarcoma (C40.0-C41.9) and Extra-skeletal osteosarcoma (ESOS); (B) The age-adjusted incidence of osseous osteosarcoma (C40.0-C41.9) and Extra-skeletal osteosarcoma (ESOS); (C) The age-adjusted mortality of osseous osteosarcoma (C40.0-C41.9) and Extra-skeletal osteosarcoma (ESOS); (D) The observed survival and cancer specific survival of osseous osteosarcoma (C40.0-C41.9) and Extra-skeletal osteosarcoma (ESOS).\u003c/p\u003e","description":"","filename":"image2.png","url":"https://assets-eu.researchsquare.com/files/rs-4072434/v1/efa0351f29e21d839b3f4517.png"},{"id":53744996,"identity":"62a425ff-dc63-4889-9907-d6f366904b3e","added_by":"auto","created_at":"2024-03-29 17:32:02","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":270714,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe survival curses of patients with ESOS. \u003c/strong\u003e(A) The survival curse of total cohort stratified by different primary tumor sites. (B-F) Subgroup analyses stratified by surgery types in patients with primary tumor originated from soft tissue including heart (B), breast (C), respiratory system (D), digestive system (E), and other sites (F), respectively.\u003c/p\u003e","description":"","filename":"image3.png","url":"https://assets-eu.researchsquare.com/files/rs-4072434/v1/b2bd896e2167c260d9913f0f.png"},{"id":53745000,"identity":"483b312f-fc7a-4433-a4ed-6f3b9d901924","added_by":"auto","created_at":"2024-03-29 17:32:02","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":189111,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe construction and validation of the predictive nomogram for patients with ESOS. \u003c/strong\u003e(A) The nomogram predicting the 1-year, 3-year and 5-year survival for patients with ESOS. (B) The time-dependent receiver operating characteristic (ROC) curve of the nomogram in construction cohort. (C) The calibration curve of the nomogram in construction cohort. (D) The time-dependent receiver operating characteristic (ROC) curve of the nomogram in validation cohort. (C) The calibration curve of the nomogram in validation cohort.\u003c/p\u003e","description":"","filename":"image4.png","url":"https://assets-eu.researchsquare.com/files/rs-4072434/v1/90b5244d373e4d30f2ee1ad3.png"},{"id":53744999,"identity":"83ecd7ee-1dac-4c65-bf40-6f8734265db3","added_by":"auto","created_at":"2024-03-29 17:32:02","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":181879,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe distribution of risk score for ESOS patients and their corresponding actual survival outcome and predictive factors information. \u003c/strong\u003e(A) for construction cohort and (B) for validation cohort, respectively.\u003c/p\u003e","description":"","filename":"image5.png","url":"https://assets-eu.researchsquare.com/files/rs-4072434/v1/2645f4db5353b4d134884fbf.png"},{"id":66144035,"identity":"b76eb4a4-9323-400a-87f4-0ffba4ae62f4","added_by":"auto","created_at":"2024-10-08 06:55:05","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2528297,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4072434/v1/e02192fa-53c1-4818-8850-b61735cb32bc.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Epidemiological and clinicopathologic characteristics, and prognostic factors of patients with Extra-skeletal Osteosarcoma","fulltext":[{"header":"1 Introduction","content":"\u003cp\u003eExtra-skeletal Osteosarcoma (ESOS) stands as a rare malignancy originating in soft tissues and organs, representing a mere 2\u0026ndash;4% of osteosarcoma cases and approximately 1% of soft tissue sarcomas[1, 2, 3, 4, 5]. Distinguished by its tumour cells directly producing a bone-like stroma akin to osteosarcoma, ESOS exhibits a histological resemblance to its skeletal counterpart. Nevertheless, this similarity notwithstanding, ESOS diverges by its lack of origin and attachment to adjacent bone structures[6, 7]. In contrast to skeletal osteosarcoma, ESOS afflicts individuals at a later stage in life, boasting a mean onset age of 60.7 years[7, 8]. Predominantly situated within the depths of the trunk, lower limbs, or upper limbs, ESOS manifests as a challenging entity to diagnose due to its pronounced malignancy and extended diagnostic timeline. Regrettably, the prognosis for ESOS is considerably grimmer than that of skeletal osteosarcoma, often accompanied by a higher propensity for metastasis, predominantly involving local lymph nodes, bone, and lung[9, 10].\u003c/p\u003e \u003cp\u003eSince its initial documentation by Wilson in 1941, the optimal management and prognostic evaluation for ESOS have been subjects of intensive investigation[11]. Given its high malignancy and protracted diagnostic journey, surgical tumour excision currently constitutes a pivotal therapeutic approach. The role of chemotherapy in ESOS remains contentious, and while radiotherapy holds limited efficacy, it is generally not a customary recourse for ESOS management[5]. Comparative to osteosarcoma, ESOS patients face a bleaker prognosis, reflected in a suboptimal 5-year overall survival rate of less than 50%[12, 13, 14]. Earlier studies have underscored the significance of prognostic factors like age, tumour grade, tumour size, surgical intervention, and chemotherapy in shaping the outlook of ESOS patients[13, 15]. However, due to ESOS's low incidence rate, the body of literature surrounding it is limited, predominantly comprising case reports and retrospective analyses characterised by modest sample sizes. The comprehensive delineation of ESOS attributes and a holistic assessment of its population-level prognosis remain incomplete. Hence, the establishment of predictive models designed to prognosticate ESOS patient outcomes emerges as an imperative undertaking.\u003c/p\u003e \u003cp\u003eConsequently, a comprehensive analysis of Extra-skeletal Osteosarcoma (ESOS) was undertaken, encompassing demographic profiles, overall survival trends, and prognostic attributes. This investigation was grounded in data sourced from the Surveillance, Epidemiology, and End Results (SEER) program. In parallel, a prognostic nomogram model was developed, hinging upon impactful factors intrinsic to ESOS outcomes.\u003c/p\u003e"},{"header":"2 Result","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Demographic and clinicopathologic characteristics of patients with ESOS\u003c/h2\u003e \u003cp\u003eA total of 4,567 osteosarcoma patients satisfying the stipulated inclusion criteria were identified. This comprised 4,317 patients presenting with osteosarcoma originating from bones and joints (C40.0-C41.9), and 250 patients with ESOS. The median ages for osteosarcoma (C40.0-C41.9) and ESOS were 19.0 and 58.0 years, respectively. As presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, appreciable disparities were evident in various demographic and clinicopathologic aspects across the groups. These encompassed age at diagnosis, gender distribution, marital status, tumour grade, as well as T and N stages. Notably, discernible distinctions in treatment modalities emerged between the groups, with a greater proportion of ESOS patients receiving chemotherapy and fewer opting for radiation therapy.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDemographic and clinicopathologic characteristics of osteosarcoma patients in SEER database.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOsteosarcoma\u003c/p\u003e \u003cp\u003e(All sites)\u003c/p\u003e \u003cp\u003eN (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOsteosarcoma\u003c/p\u003e \u003cp\u003e(C40.0-C41.9)\u003c/p\u003e \u003cp\u003eN (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eExtraskeletal osteosarcoma\u003c/p\u003e \u003cp\u003e(ESOS)\u003c/p\u003e \u003cp\u003eN (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eχ\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYear of diagnosis\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2000\u0026ndash;2003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e847 (18.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e799 (18.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e48 (19.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e1.081\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cem\u003e0.582\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2004\u0026ndash;2009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1282 (28.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1219 (28.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e63 (25.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e 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colname=\"c4\"\u003e \u003cp\u003e77 (30.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;50 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e832 (18.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e670 (15.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e162 (64.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGender\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2530 (55.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2409 (55.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e121 (48.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e5.214\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003e0.022\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2037 (44.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1908 (44.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e129 (51.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMarital status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarried\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1051 (23.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e914 (21.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e137 (54.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e160.941\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cem\u003e\u0026lt;\u0026thinsp;0.001\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnmarried\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3406 (74.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3304 (76.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e102 (40.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e110 (2.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e99 (2.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11 (4.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRace\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWhite\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3413 (74.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3209 (74.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e204 (81.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e6.712\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u003cem\u003e0.082\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBlack\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e697 (15.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e668 (15.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e29 (11.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOthers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e429 (9.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e413 (9.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16 (6.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28 (0.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27 (0.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (0.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMedian household income\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt; \u003cspan\u003e$\u003c/span\u003e65,000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1332 (29.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1253 (29.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e79 (31.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e2.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u003cem\u003e0.572\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cspan\u003e$\u003c/span\u003e65,000 - \u003cspan\u003e$\u003c/span\u003e75,000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1381 (30.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1301 (30.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e80 (32.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt; \u003cspan\u003e$\u003c/span\u003e75,000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1853 (40.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1762 (40.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e91 (36.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGrade\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWell differentiated; Grade I\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e192 (4.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e188 (4.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4 (1.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e17.097\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e\u003cem\u003e0.002\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModerately differentiated; Grade II\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e254 (5.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e243 (5.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11 (4.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePoorly differentiated; Grade III\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1029 (22.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e954 (22.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e75 (30.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUndifferentiated; anaplastic; Grade IV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1618 (35.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1520 (35.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e98 (39.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1474 (32.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1412 (32.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e62 (24.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSEER Stage\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLocalized\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1343 (29.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1258 (29.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e85 (34.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e4.341\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u003cem\u003e0.227\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRegional\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1352 (29.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1291 (29.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e61 (24.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDistant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e844 (18.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e797 (18.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e47 (18.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1028 (22.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e971 (22.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e57 (22.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eT stage\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1197 (26.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1164 (27.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e33 (13.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e81.673\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e\u003cem\u003e\u0026lt;\u0026thinsp;0.001\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1664 (36.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1573 (36.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e91 (36.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e123 (2.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e116 (2.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7 (2.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e34 (0.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22 (0.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12 (4.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1549 (33.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1442 (33.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e107 (42.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eN stage\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eN0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3255 (71.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3115 (72.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e140 (56.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e30.190\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cem\u003e\u0026lt;\u0026thinsp;0.001\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eN1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e102 (2.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e94 (2.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8 (3.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1210 (26.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1108 (25.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e102 (40.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBone metastasis\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2255 (49.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2124 (49.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e131 (52.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e1.270\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cem\u003e0.530\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e111 (2.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e104 (2.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7 (2.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2201 (48.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2089 (48.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e112 (44.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBrain metastasis\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2356 (51.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2220 (51.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e136 (54.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e1.457\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cem\u003e0.483\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9 (0.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8 (0.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (0.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2202 (48.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2089 (48.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e113 (45.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLiver metastasis\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2350 (51.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2215 (51.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e135 (54.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e5.307\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cem\u003e0.070\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18 (0.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15 (0.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3 (1.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2199 (48.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2087 (48.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e112 (44.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLung metastasis\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1955 (42.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1839 (42.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e116 (46.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e1.453\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cem\u003e0.484\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e409 (9.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e387 (9.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22 (8.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2203 (48.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2091 (48.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e112 (44.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSurgery\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e739 (16.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e709 (16.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e30 (12.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e5.011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cem\u003e0.082\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3708 (81.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3498 (81.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e210 (84.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e120 (2.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e110 (2.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10 (4.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eChemotherapy\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1031 (22.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e908 (21.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e123 (49.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e107.265\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003e\u0026lt;\u0026thinsp;0.001\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo/Unknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3536 (77.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3409 (79.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e127 (50.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRadiation therapy\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4115 (90.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3929 (91.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e186 (74.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e73.131\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003e\u0026lt;\u0026thinsp;0.001\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo/Unknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e452 (9.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e388 (9.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e64 (25.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e provides a comprehensive listing of patient numbers and detailed demographic, clinicopathologic, and survival data for ESOS, organized in accordance with distinct primary tumour sites. The prevalent primary site for ESOS was the soft tissue (N\u0026thinsp;=\u0026thinsp;175), particularly in the upper (25 cases) and lower limbs (94 cases), followed by occurrences in the breast (N\u0026thinsp;=\u0026thinsp;24) and respiratory system (N\u0026thinsp;=\u0026thinsp;16). Notably, the 5-year overall survival rates stood at 42.4% for patients with primary tumours originating from soft tissue and 34.1% for those originating from the breast. It is of significance to mention that ESOS patients stemming from the nasal cavity and sinus were notably younger, with a mean age of 34.7 years. As indicated in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, ESOS manifests across diverse systems, each accompanied by distinct treatment strategies and survival outcomes.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe summarized information of patients with ESOS in SEER database, grouped by primary tumor sites.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"10\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSite\u003c/p\u003e \u003cp\u003eGroup\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003ePrimary tumor site\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNo. of\u003c/p\u003e \u003cp\u003ePatients\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMale/\u003c/p\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eSurgery\u003c/p\u003e \u003cp\u003eType\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eChemotherapy\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eRadiation\u003c/p\u003e \u003cp\u003eTherapy\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eSurvival\u003c/p\u003e \u003cp\u003eOutcome\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"9\" rowspan=\"10\"\u003e \u003cp\u003e\u003cb\u003eSoft Tissue including Heart\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eC49.0 Conn, subcutaneous, other soft tissue: head, face, neck\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e62.4\u003c/p\u003e \u003cp\u003e(mean)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4/1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ePartial resection (5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eYes (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eYes (1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"9\" rowspan=\"10\"\u003e \u003cp\u003e1-year OS: 76.0%\u003c/p\u003e \u003cp\u003e3-year OS:\u003c/p\u003e \u003cp\u003e47.1%\u003c/p\u003e \u003cp\u003e5-year OS:\u003c/p\u003e \u003cp\u003e42.4%\u003c/p\u003e \u003cp\u003eMedian OS:\u003c/p\u003e \u003cp\u003e33.0 months\u003c/p\u003e \u003cp\u003eMean OS:\u003c/p\u003e \u003cp\u003e103.1 months\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eC49.1 Conn, subcutaneous, other soft tissue: upper limb, shoulder\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e55.3 (mean)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e12/13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ePartial resection (10)\u003c/p\u003e \u003cp\u003eRadical excision (9)\u003c/p\u003e \u003cp\u003eAmputation (2)\u003c/p\u003e \u003cp\u003eNo surgery (4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eYes (11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eYes (4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eC49.2 Conn, subcutaneous, other soft tissue: lower limb, hip\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e53.0\u003c/p\u003e \u003cp\u003e(mean)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e52/42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ePartial resection (23)\u003c/p\u003e \u003cp\u003eRadical excision (54)\u003c/p\u003e \u003cp\u003eAmputation (8)\u003c/p\u003e \u003cp\u003eNo surgery (7)\u003c/p\u003e \u003cp\u003eUnknown (2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eYes (56)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eYes (29)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eC49.3 Conn, subcutaneous, other soft tissue: thorax\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e62.1\u003c/p\u003e \u003cp\u003e(mean)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4/11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ePartial resection (5)\u003c/p\u003e \u003cp\u003eRadical excision (6)\u003c/p\u003e \u003cp\u003eNo surgery (4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eYes (9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eYes (2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eC49.4 Conn, subcutaneous, other soft tissue: abdomen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e28; 51; 76; 83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3/1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ePartial resection (1)\u003c/p\u003e \u003cp\u003eRadical excision (2)\u003c/p\u003e \u003cp\u003eAmputation (1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eYes (1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eYes (0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eC49.5 Conn, subcutaneous, other soft tissue: pelvis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e58.1\u003c/p\u003e \u003cp\u003e(mean)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7/7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ePartial resection (3)\u003c/p\u003e \u003cp\u003eRadical excision (10)\u003c/p\u003e \u003cp\u003eNo surgery (1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eYes (6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eYes (5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eC49.6 Conn, subcutaneous, other soft tissue: trunk, NOS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e47.6\u003c/p\u003e \u003cp\u003e(mean)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5/3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ePartial resection (5)\u003c/p\u003e \u003cp\u003eRadical excision (2)\u003c/p\u003e \u003cp\u003eNo surgery (1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eYes (4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eYes (5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eC49.8 Overlap conn, subcutaneous, other soft tissues\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1/0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eRadical excision (1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eYes (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eYes (1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eC49.9 Conn, subcutaneous and other soft tissues, NOS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e63; 68; 67; 20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4/0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eRadical excision (1)\u003c/p\u003e \u003cp\u003eNo surgery (3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eYes (2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eYes (0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eC38.0 Heart\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e52.6\u003c/p\u003e \u003cp\u003e(mean)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2/3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ePartial remove (3)\u003c/p\u003e \u003cp\u003eDebulking (1)\u003c/p\u003e \u003cp\u003eUnknown (1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eYes (2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eYes (0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBreast\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eC50.0-C50.9 Breast\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e69.2\u003c/p\u003e \u003cp\u003e(mean)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0/24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eSubcutaneous mastectomy (1)\u003c/p\u003e \u003cp\u003ePartial mastectomy (6)\u003c/p\u003e \u003cp\u003eTotal mastectomy (9)\u003c/p\u003e \u003cp\u003eModified radical mastectomy (6)\u003c/p\u003e \u003cp\u003eMastectomy, NOS (1)\u003c/p\u003e \u003cp\u003eNo surgery (1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eYes (11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eYes (5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1-year OS: 50.0%\u003c/p\u003e \u003cp\u003e3-year OS:\u003c/p\u003e \u003cp\u003e39.8%\u003c/p\u003e \u003cp\u003e5-year OS:\u003c/p\u003e \u003cp\u003e34.1%\u003c/p\u003e \u003cp\u003eMedian OS:\u003c/p\u003e \u003cp\u003e12.0 months\u003c/p\u003e \u003cp\u003eMean OS:\u003c/p\u003e \u003cp\u003e69.6 months\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u003cb\u003eRespiratory System\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eC30.0-Nasal cavity\u003c/p\u003e \u003cp\u003eC31.0-Maxillary sinus\u003c/p\u003e \u003cp\u003eC31.1-Ethmoid sinus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e34.7\u003c/p\u003e \u003cp\u003e(mean)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6/3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eTotal remove (4)\u003c/p\u003e \u003cp\u003ePartial remove (1)\u003c/p\u003e \u003cp\u003eRadical surgery (2)\u003c/p\u003e \u003cp\u003eExcisional biopsy (1)\u003c/p\u003e \u003cp\u003eUnknown (1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eYes (6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eYes (5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e1-year OS: 54.5%\u003c/p\u003e \u003cp\u003e3-year OS:\u003c/p\u003e \u003cp\u003e37.4%\u003c/p\u003e \u003cp\u003eMedian OS:\u003c/p\u003e \u003cp\u003e19.0 months\u003c/p\u003e \u003cp\u003eMean OS:\u003c/p\u003e \u003cp\u003e98.2 months\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eC34.0-C34.9 Lung and Bronchus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e77.2\u003c/p\u003e \u003cp\u003e(mean)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4/1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eLobectomy with lymph node dissection (1)\u003c/p\u003e \u003cp\u003eNo surgery (4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eYes (1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eYes (1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eC38.4 Pleura\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1/0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eTotal remove (1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eYes (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eYes (0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eC38.3 Mediastinum\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1/0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eRadical surgery (1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eYes (1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eYes (0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u003cb\u003eDigestive System\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eLiver and Intrahepatic Bile Duct\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eC22.0 Liver\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e70; 19;\u003c/p\u003e \u003cp\u003e56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1/2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eLeft lobectomy (1)\u003c/p\u003e \u003cp\u003eWedge or segmental resection (1)\u003c/p\u003e \u003cp\u003eNo surgery (1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eYes (3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eYes (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e1-year OS: 55.6%\u003c/p\u003e \u003cp\u003e3-year OS:\u003c/p\u003e \u003cp\u003e41.7%\u003c/p\u003e \u003cp\u003eMedian OS:\u003c/p\u003e \u003cp\u003e23.0 months\u003c/p\u003e \u003cp\u003eMean OS:\u003c/p\u003e \u003cp\u003e98.7 months\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eC48.0 Retroperitoneum\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e64; 49;\u003c/p\u003e \u003cp\u003e39; 72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3/1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ePartial remove (1)\u003c/p\u003e \u003cp\u003eRadical surgery (2)\u003c/p\u003e \u003cp\u003eExcisional biopsy (1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eYes (1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eYes (1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eC48.1 Specified parts of peritoneum\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0/1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eUnknown (1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eYes (1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eYes (0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eColon and Rectum\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eC18.0 Cecum\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1/0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eColectomy/hemicolectomy (1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eYes (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eYes (0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eFemale Genital System\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eC54.0-C54.9 Corpus Uteri\u003c/p\u003e \u003cp\u003eC55.9 Uterus, NOS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e53; 57;\u003c/p\u003e \u003cp\u003e54; 48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0/4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eHysterectomy (1)\u003c/p\u003e \u003cp\u003eTotal hysterectomy without removal of tube and ovary (3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eYes (1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eYes (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eMedian OS:\u003c/p\u003e \u003cp\u003e4.0 months\u003c/p\u003e \u003cp\u003eMean OS:\u003c/p\u003e \u003cp\u003e11.1 months\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eC56.9 Ovary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e75; 29;\u003c/p\u003e \u003cp\u003e65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0/3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eUnilateral oophorectomy (1)\u003c/p\u003e \u003cp\u003eDebulking (2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eYes (1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eYes (0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eUrinary System\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eC67.0-C67.9 Urinary Bladder\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e90; 71;\u003c/p\u003e \u003cp\u003e57; 68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3/1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eExcisional biopsy (1)\u003c/p\u003e \u003cp\u003ePolypectomy (1)\u003c/p\u003e \u003cp\u003eRadical cystectomy (1)\u003c/p\u003e \u003cp\u003eNo surgery (1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eYes (3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eYes (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eMean OS:\u003c/p\u003e \u003cp\u003e16.8 months\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eC64.9-Kidney, NOS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1/0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNo surgery (1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eYes (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eYes (0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003eOral Cavity and Pharynx\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eC09.9 Tonsil, NOS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1/0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eLaryngectomy (1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eYes (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eYes (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eMean OS:\u003c/p\u003e \u003cp\u003e140.4 months\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eC05.0 Hard palate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e39; 44; 25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1/2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eRadical excision (3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eYes (1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eYes (1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eC03.1 Lower gum\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0/1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eRadical excision (1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eYes (1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eYes (1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003eBrain and Other Nervous System\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eC71.3 Parietal lobe\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0/1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eUnknown (1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eYes (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eYes (1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e22 months (A)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eC71.4 Occipital lobe\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0/1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eUnknown (1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eYes (1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eYes (1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e16 months (D)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eC72.0 Spinal cord\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0/1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNo surgery (1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eYes (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eYes (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e224 months (A)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eMale Genital System\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eC61.9 Prostate gland\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1/0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNo surgery (1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eYes (1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eYes (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e9 months (D)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eC63.1 Spermatic cord\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1/0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eTotal remove (1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eYes (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eYes (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e26 months (D)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSkin excluding Basal and Squamous\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eC44.4 Skin of scalp and neck\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1/0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eMohs with 1-cm margin or less (1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eYes (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eYes (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e59 months (D)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMiscellaneous\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eC80.9 Unknown primary site\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e66; 59; 68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1/2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eUnknown (1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eYes (3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eYes (1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e5 months (D)\u003c/p\u003e \u003cp\u003e8 months (D)\u003c/p\u003e \u003cp\u003e2 months (D)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Epidemiological performance of patients with ESOS\u003c/h2\u003e \u003cp\u003eTo delve into the extent of the cancer burden, the 20-year limited-duration prevalence rates for osteosarcoma and ESOS were computed, incorporating adjustments based on the 2000 US standard population. Illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e2\u003c/span\u003eA, the prevalence of osteosarcoma was 0.00028% in the year 2000, rising notably to 0.00294% by 2019. Correspondingly, the prevalence of ESOS exhibited a slight increment from 0.00002% in 2000 to 0.00011% in 2019. Given the prevalence's potential to mirror the ascending incidence and relatively indolent behaviour of cancers, the incidence and survival rates of both osteosarcoma and ESOS were subjected to calculation. The yearly age-adjusted incidence rate for ESOS hovered at approximately 0.02 per 100,000 individuals, displaying a lack of significant alteration (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e2\u003c/span\u003eB and Supplementary Fig.\u0026nbsp;1). Figure\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e2\u003c/span\u003eC and Supplementary Fig.\u0026nbsp;2 delineate the age-adjusted mortality rates for ESOS. In 2001, the lowest mortality rate was recorded at 0.0027 per 100,000 individuals, while the peak rate reached 0.0132 per 100,000 in 2011. As exhibited in Supplementary Fig.\u0026nbsp;2, no discernible trend shift in mortality rates was detected among ESOS patients. Moreover, Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e2\u003c/span\u003eD provides an exposition of the observed survival and cancer-specific survival rates for ESOS. Both observed survival and cancer-specific survival rates for ESOS proved inferior to their counterparts in bone-originating osteosarcoma. Notably, the 1-year, 3-year, and 5-year cancer-specific survival rates for osteosarcoma (C40.0-C41.9) stood at 88.0%, 68.7%, and 61.3% respectively, whereas the corresponding rates for ESOS patients were 71.5%, 49.4%, and 45.7%.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Prognosis and independent prognostic factors of ESOS\u003c/h2\u003e \u003cp\u003eThe outcomes of the Cox proportional hazard regression analysis are presented in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. As discerned through univariate analysis, factors influencing ESOS survival encompassed age, primary tumour site, clinical stage, T stage, N stage, the presence of bone metastasis, brain metastasis, liver metastasis, lung metastasis, and the implementation of surgical intervention. Upon adjusting for confounding variables, the multivariate analysis revealed that advancing age at diagnosis (HR\u0026thinsp;=\u0026thinsp;1.03, 95%CI: 1.02\u0026ndash;1.04; P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), distant stage (HR\u0026thinsp;=\u0026thinsp;3.04, 95%CI: 1.66\u0026ndash;5.58; P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and the presence of bone metastasis (HR\u0026thinsp;=\u0026thinsp;4.71, 95%CI: 1.95\u0026ndash;11.39; P\u0026thinsp;=\u0026thinsp;0.001) stood as independent adverse prognostic factors. Notably, primary tumour surgery (HR\u0026thinsp;=\u0026thinsp;0.19, 95%CI: 0.12\u0026ndash;0.29; P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) emerged as an autonomous factor indicative of enhanced survival outcomes.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe prognostic factors of patients with extraskeletal osteosarcoma.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCharacteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eUnivariate\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003eMultivariate\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eP value\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eHR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eP value\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.027 (1.017\u0026ndash;1.036)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003e\u0026lt;\u0026thinsp;0.001\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e1.032 (1.023\u0026ndash;1.042)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003e\u0026lt;\u0026thinsp;0.001\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGender\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.00 (Reference)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.094 (0.792\u0026ndash;1.511)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003e0.586\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMarital status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarried\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.00 (Reference)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnmarried\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.974 (0.698\u0026ndash;1.360)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003e0.878\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.277 (0.589\u0026ndash;2.767)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003e0.536\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRace\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWhite\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.00 (Reference)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBlack\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.859 (0.517\u0026ndash;1.428)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003e0.559\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOthers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.82 (0.401\u0026ndash;1.678)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003e0.588\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003e0.959\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMedian household income\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt; \u003cspan\u003e$\u003c/span\u003e65,000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.00 (Reference)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cspan\u003e$\u003c/span\u003e65,000 - \u003cspan\u003e$\u003c/span\u003e75,000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.016 (0.693\u0026ndash;1.488)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003e0.936\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt; \u003cspan\u003e$\u003c/span\u003e75,000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.671 (0.447\u0026ndash;1.009)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003e0.056\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePrimary tumor site\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eConn, subcutaneous, other soft tissue\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.00 (Reference)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e1.00 (Reference)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther sites\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.637 (1.171\u0026ndash;2.288)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003e0.004\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e1.112 (0.699\u0026ndash;1.769)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003e0.653\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGrade\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWell differentiated; Grade I\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.00 (Reference)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModerately differentiated; Grade II\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003e0.953\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePoorly differentiated; Grade III\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.033 (0.318\u0026ndash;3.357)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003e0.956\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUndifferentiated; anaplastic; Grade IV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.387 (0.436\u0026ndash;4.415)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003e0.580\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.728 (0.534\u0026ndash;5.592)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003e0.361\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSEER Stage\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLocalized\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.00 (Reference)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e1.00 (Reference)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRegional\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.666 (1.046\u0026ndash;2.654)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003e0.032\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e1.442 (0.874\u0026ndash;2.379)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003e0.152\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDistant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.625 (2.271\u0026ndash;5.787)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003e\u0026lt;\u0026thinsp;0.001\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e3.042 (1.658\u0026ndash;5.579)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003e\u0026lt;\u0026thinsp;0.001\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.598 (1.010\u0026ndash;2.527)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003e0.045\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e0.858 (0.447\u0026ndash;1.647)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003e0.645\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eT stage\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.00 (Reference)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e1.00 (Reference)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.684 (1.328\u0026ndash;5.424)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003e0.006\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e1.525 (0.776\u0026ndash;2.998)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003e0.221\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.995 (0.805\u0026ndash;11.145)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003e0.102\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e0.808 (0.208\u0026ndash;3.142)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003e0.759\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.492 (1.163\u0026ndash;10.486)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003e0.026\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e1.797 (0.594\u0026ndash;5.433)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003e0.299\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.071 (1.536\u0026ndash;6.143)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003e0.002\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e1.300 (0.499\u0026ndash;3.384)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003e0.591\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eN stage\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eN0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.00 (Reference)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e1.00 (Reference)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eN1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.222 (1.018\u0026ndash;4.848)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003e0.045\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e1.685 (0.617\u0026ndash;4.602)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003e0.309\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.375 (0.986\u0026ndash;1.918)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003e0.061\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e1.597 (0.782\u0026ndash;3.264)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003e0.199\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBone metastasis\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.00 (Reference)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e1.00 (Reference)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.617 (2.103\u0026ndash;10.14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003e\u0026lt;\u0026thinsp;0.001\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e4.711 (1.948\u0026ndash;11.393)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003e0.001\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.078 (0.766\u0026ndash;1.516)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003e0.667\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e18.823 (0.002-168650.242)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003e0.527\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBrain metastasis\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.00 (Reference)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e1.00 (Reference)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e41.579 (4.979\u0026ndash;347.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003e0.001\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eNA\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.004 (0.719\u0026ndash;1.402)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003e0.980\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e0.061 (0-538.293)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003e0.546\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLiver metastasis\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.00 (Reference)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e1.00 (Reference)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.368 (1.37-13.932)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003e0.013\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e0.932 (0.154\u0026ndash;5.652)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003e0.939\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.031 (0.737\u0026ndash;1.444)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003e0.858\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eNA\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLung metastasis\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.00 (Reference)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e1.00 (Reference)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.459 (1.44\u0026ndash;4.202)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003e0.001\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.168 (0.817\u0026ndash;1.672)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003e0.395\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e0.858 (0.429\u0026ndash;1.715)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003e0.665\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSurgery\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.00 (Reference)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e1.00 (Reference)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.269 (0.175\u0026ndash;0.415)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003e\u0026lt;\u0026thinsp;0.001\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e0.185 (0.117\u0026ndash;0.293)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003e\u0026lt;\u0026thinsp;0.001\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.58 (0.261\u0026ndash;1.288)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003e0.181\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e0.433 (0.153\u0026ndash;1.225)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003e0.115\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eChemotherapy\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.00 (Reference)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo/Unknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.734 (0.531\u0026ndash;1.015)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003e0.062\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRadiation therapy\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.00 (Reference)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo/Unknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.935 (0.641\u0026ndash;1.363)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003e0.727\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe examination of the impact of diverse surgical approaches on survival outcomes across different primary tumour sites was undertaken via subgroup analyses. As delineated in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, observable variations in survival durations were noted among patients subjected to distinct surgical interventions, with particular prominence within the subset of patients presenting with tumours originating from soft tissue (P-value\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Within the 'Soft Tissue including Heart' subgroup, the mean overall survival (OS) extended to 123.3 (89.8-156.7) months for individuals undergoing partial resection and 117.6 (92.2-143.1) months for those undergoing radical excision. Notably, patients subjected to amputation exhibited a considerably less favourable mean OS of 21.5 (10.3\u0026ndash;32.6) months. The survival trajectories of the total cohort, as well as those for patients harboring distinct primary tumour sites, are graphically depicted in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe summarized information of survival outcome in patients with ESOS in SEER database, grouped by primary tumor sites and surgery types.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSite\u003c/p\u003e \u003cp\u003eGroup\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSurgery\u003c/p\u003e \u003cp\u003eType\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMean OS\u003c/p\u003e \u003cp\u003e[95%CI]\u003c/p\u003e \u003cp\u003e(months)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMedian OS\u003c/p\u003e \u003cp\u003e[95%CI]\u003c/p\u003e \u003cp\u003e(months)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1-year OS\u003c/p\u003e \u003cp\u003e(%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3-year OS\u003c/p\u003e \u003cp\u003e(%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5-year OS\u003c/p\u003e \u003cp\u003e(%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cem\u003eLog-rank\u003c/em\u003e\u003c/p\u003e \u003cp\u003e\u003cem\u003eP-value\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cem\u003eBreslow\u003c/em\u003e\u003c/p\u003e \u003cp\u003e\u003cem\u003eP-value\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e\u003cb\u003eSoft Tissue including Heart\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo surgery\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30.3 (1.8\u0026ndash;58.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.0 (1.0\u0026ndash;12.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e22.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e7.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e\u003cem\u003e\u0026lt;\u0026thinsp;0.001\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e\u003cem\u003e\u0026lt;\u0026thinsp;0.001\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePartial resection\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e123.3 (89.8-156.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e88.0 (34.0-173.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e78.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e60.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e52.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRadical excision\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e117.6 (92.2-143.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e38.0 (24.0-174.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e82.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e50.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e48.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAmputation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21.5 (10.3\u0026ndash;32.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15.0 (5.0\u0026ndash;29.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e54.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e18.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUnknown or others\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22.3 (8.7\u0026ndash;35.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21.0 (4.0\u0026ndash;37.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e75.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e25.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003eBreast\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo surgery or others\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18.0 (NA)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.0 (1.0\u0026ndash;3.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e33.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e33.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cem\u003e0.699\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cem\u003e0.599\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePartial mastectomy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e89.4 (17.5-161.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e36.0 (1.0\u0026ndash;36.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e66.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e44.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e44.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal/radical mastectomy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e59.3 (16.6\u0026ndash;102.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12.0 (6.0-143.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e46.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e38.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e29.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003eRespiratory System\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo surgery\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.5 (NA)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.0 (0.0\u0026ndash;19.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cem\u003e0.044\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cem\u003e0.056\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRadical surgery/total removal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e114.3 (27.4-201.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21.0 (2.0\u0026ndash;21.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e58.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e43.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e43.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUnknown or others\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20.3 (10.5\u0026ndash;30.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eDigestive System\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo surgery or unknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15.5 (0.8\u0026ndash;30.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8 (8.0\u0026ndash;23.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003e0.454\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003e0.612\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWith surgery\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e129.6 (49.6-209.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e57.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e57.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e57.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eOther sites\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo surgery or unknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e54.3 (NA)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.0 (0.0\u0026ndash;16.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e33.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e22.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e22.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003e0.451\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003e0.391\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWith surgery\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e59.6 (15.3-103.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e26.0 (2.0\u0026ndash;75.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e51.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e36.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e27.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Construction and validation of prognostic nomogram of ESOS\u003c/h2\u003e \u003cp\u003eInclusion of the aforementioned independent prognostic factors was undertaken for the formulation of the predictive nomogram, as illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e4\u003c/span\u003eA. The temporal receiver operating characteristic (ROC) curves in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e4\u003c/span\u003eB depict commendable discriminatory capacity of the model, with corresponding area under the curve (AUC) values at 1-year, 3-year, and 5-year intervals standing at 0.848, 0.793, and 0.805 respectively. Evaluation of calibration prowess, as illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e4\u003c/span\u003eC, showcased a harmonious alignment between anticipated and observed probabilities, with all calibration curves closely mirroring the 45-degree reference line. Importantly, this predictive fidelity extended to the validation cohort, as corroborated by Figs.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e4\u003c/span\u003eD and \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e3\u003c/span\u003eE. In this context, the nomogram consistently exhibited pronounced discriminatory strength and adept calibration (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e4\u003c/span\u003eD-E). Noteworthy AUC values for the nomogram across the 1-year, 3-year, and 5-year spans were observed at 0.778, 0.800, and 0.748 correspondingly. To furnish a visual and comprehensive validation of our predictive model, we classified all ESOS patients into high-risk and low-risk groups in accordance with their assigned risk scores. Figure\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e5\u003c/span\u003e, comprising Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e5\u003c/span\u003eA for the construction cohort and Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e5\u003c/span\u003eB for the validation cohort, encompasses scatter plots illustrating the juxtaposition of risk scores and survival status for ESOS patients, accompanied by corresponding predictive factors information.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"3 Discussion","content":"\u003cp\u003eOur investigation presents an analysis concerning a population-based cohort of ESOS patients derived from the SEER database. It delineates the incidence and prevalence of these patients and characterizes the pattern of survival. In this study grounded in the population, we discerned that the age-adjusted annual prevalence of ESOS escalated from 0.02 per 100,000 in the year 2000 to 0.11 per 100,000 in 2019, signifying a remarkable 5.5-fold surge. Meanwhile, the incidence and mortality of this condition exhibited no noteworthy alteration. Considering that prevalence encompasses both incidence and survival, one may deduce that the overall survival rate of ESOS patients experienced a slight enhancement during this temporal span. The broad-spectrum therapeutic approaches might plausibly contribute to the advancement in prognosis for ESOS patients. The preeminence of the surgical cohort over their non-surgical counterparts within this study underscores the pivotal role of treatment, particularly surgical intervention. Despite the prognosis for ESOS patients remaining relatively unfavourable, there is discernible improvement in overall survival over the temporal course, mirroring advancements in anticancer therapeutics.\u003c/p\u003e \u003cp\u003eThe patients afflicted by ESOS exhibited an age range of 47 to 61 years, with an average age of 60.7[8]. Within the present study, the proportion of patients surpassing 50 years of age reached 64.8% among ESOS cases, while it stood at a mere 18.2% for those grappling with osseous osteosarcoma. In alignment with prior reports, advanced age emerged as an independent prognostic peril[16, 17]. This phenomenon could be attributed to the relatively diminished tolerance towards comprehensive therapeutic regimens among elderly patients. Furthermore, older patients are prone to multiple comorbidities, including cardiovascular ailments and diabetes, which are known to exacerbate their prognosis. Notably, there existed no appreciable variance in the male-to-female ratio within the ESOS cohort. In our study, the male-to-female ratio for ESOS closely approximated 1:1, a proportion akin to previously documented observations[16]. Intriguingly, within our dataset, 12.4% of ESOS cases emanated from the female breast and reproductive organs, whereas there existed a solitary instance occurring within the male reproductive organ. This incongruity could potentially be ascribed to the annual influx of cases into the system.\u003c/p\u003e \u003cp\u003eESOS, by its nature, presents an unfavorable prognosis. According to Chung et al.[17], patients diagnosed with ESOS exhibited a three-year mortality rate exceeding 50%. A European multicenter study involving 266 ESOS patients reported a five-year overall survival rate of 47%[14]. Our study yielded similar findings, with corresponding three-year and five-year overall survival rates of 49.4% and 45.7%, respectively. The potential for enhanced prognosis through primary lesion resection by means of surgical intervention has been documented[5, 13, 14, 18, 19, 20]. Goldstein et al.[21] concluded that complete resection stood as the singular positive prognostic determinant for ESOS. In our current investigation, a noteworthy 84% of ESOS patients underwent surgical procedures, emerging as an independent prognostic factor associated with favorable survival outcomes in multivariate Cox regression analysis. Within the 'Soft Tissue including Heart' subgroup, patients subjected to surgery evidenced one-, three-, and five-year overall survival rates of 78.0%, 60.5%, and 52.1%, respectively. These figures notably surpassed those observed in non-surgically treated patients (22.5%, 7.5%, and 7.5%, respectively). Our findings resonate with prior research conducted by others[15, 22]. Additionally, survival prognoses exhibit variation when stratified according to originating systemic tissues or organs. In our study, 250 ESOS patients were distributed across 11 systemic tissues or organs, with 70% of cases manifesting in the 'Soft Tissue including Heart' category (with over a third localized in the lower limbs). Fewer instances occurred within other systemic tissues, comprising 24 cases within breast tissues and 16 cases in the respiratory system. Notably, patients with ESOS originating in the 'Soft Tissue including Heart' category demonstrated a median survival of 33.0 months, markedly outperforming their counterparts originating from other sites (12.0 months for breast and 19.9 months for lung, respectively). This concurs with previously reported findings[4, 8, 23, 24, 25]. Superficial ESOS masses, being more readily detectable, facilitate early-stage diagnosis and subsequent intervention. Moreover, due to their comparatively modest vascular and lymphatic networks, the likelihood of local progression and distinct metastasis diminishes, thereby enhancing patients' prognostic survival rates and reducing the incidence of local recurrence post-treatment[7, 16, 19, 26, 27, 28, 29]. Additionally, ESOS originating from diverse systemic sites exhibit disparate tissue origins, consequently engendering distinct biological behaviours and, by extension, discernible differences in survival outcomes.\u003c/p\u003e \u003cp\u003eESOS shares a nomenclature and histological resemblances with osseous osteosarcoma, yet diverges in terms of occurrence sites and clinicopathological attributes. Regrettably, ESOS displays a notable insensitivity to chemotherapy, as evidenced in previous reports[5, 18, 30, 31]. The role of chemotherapy in managing ESOS patients remains a contentious topic[13, 14, 32, 33]. In the context of localised ESOS, the amalgamation of surgical intervention with diverse chemotherapy regimens appears to hold promise for enhancing overall survival[21, 34]. A comprehensive examination by Longhi et al.[14] across multiple centres illustrated elevated survival rates among individuals subjected to perioperative chemotherapy, with an inclination towards potential effectiveness of osteosarcoma chemotherapy protocols. Conversely, Lin Qi et al.[35] partitioned 310 ESOS patients into cohorts with and without chemotherapy exposure, arriving at the conclusion that the chemotherapy group didn't manifest significant prognostic amelioration. For advanced ESOS cases marked by distant metastases, assorted chemotherapeutic protocols offer feasible alternatives, yet these regimens fail to impart a survival advantage[5, 36]. Furthermore, given the advanced age demographic and potential for systemic dysfunction among ESOS patients, the associated complexities of chemotherapy pose an unsuitable proposition for elderly cohorts[14]. Consequently, there exists a rationale to abstain from routinely endorsing chemotherapy as a standard ESOS treatment[37]. Within this study, the utilization of chemotherapy accounted for 49.2%, a percentage notably lower than that of surgery. Multivariate Cox regression analysis corroborated that chemotherapy failed to emerge as an independent, favorable prognostic factor.\u003c/p\u003e \u003cp\u003eThe therapeutic scope of radiotherapy within ESOS remains circumscribed, resulting in its non-routine adoption[18, 30, 38]. Generally, radiotherapy serves a palliative function for ESOS patients either burdened with inoperable primary lesions or grappling with metastatic afflictions[31, 34, 39, 40]. The coupling of surgical intervention with radiotherapy has demonstrated efficacy in diminishing tumour size and local recurrence rates. However, it falls short of significantly influencing ESOS prognosis[15, 16]. Wang Hao-tong et al.[15] demonstrated an augmentation in the overall survival rate among patients harbouring ESOS with surgically positive margins who underwent radiotherapy. Within our study, over two-thirds of ESOS patients received radiotherapy, a practice ostensibly aimed at curtailing tumour recurrence and attaining negative surgical margins.\u003c/p\u003e \u003cp\u003eESOS represents an exceedingly uncommon malignancy, marked by a dearth of clinical evidence elucidating its prognosis. Furthermore, prior investigations have often concentrated on therapeutic aspects, neglecting the utilization of a nomogram for prognostic prediction[14]. Thus, our initiative encompassed the construction of a nomogram, designed to prognosticate outcomes for ESOS patients. Following univariate and multivariate Cox regression analysis, four key variables emerged as predictive factors: advanced age at diagnosis, metastatic disease stage, the presence of bone metastasis, and primary tumour surgical intervention. The validation of this nomogram underscored its robust discriminative and calibration capabilities. The visually intuitive format of the nomogram aptly conveys predictive model outcomes, simplifying the intricate task of simultaneous prognostic assessment. This tool not only offers a straightforward and precise means of prognosticating outcomes for ESOS patients, but also equips clinicians with a point of reference to inform subsequent medical decisions.\u003c/p\u003e \u003cp\u003eWhile our study shares limitations akin to preceding research endeavours, its retrospective design being one. Future prospects necessitate prospective randomised clinical trials to furnish high-calibre clinical evidence for application. Additionally, the SEER database omits certain data points, including tumour size, growth depth, and resection specimen margin status. Neglecting these factors could potentially overlook facets with bearing upon patient prognosis. It is noteworthy, however, that our present study holds the distinction of being the most expansive of its kind, and the first to pioneer a survival prognostic model for ESOS. As the database accumulates a greater corpus of cases, this to a considerable extent addresses the scarcity of ESOS studies, thereby furnishing a more comprehensive epidemiological perspective.\u003c/p\u003e \u003cp\u003eIn conclusion, our retrospective analysis of a sizeable, population-based, single-institution dataset offers insights into the distinguishing features of ESOS compared to osseous osteosarcoma. Discerned through our investigation, advanced age at diagnosis, distant disease stage, and the presence of bone metastasis independently emerged as adverse prognostic determinants, while primary tumour excision surgery displayed potential to enhance ESOS patient outcomes. Our observations also indicate that neither radiotherapy nor chemotherapy confers survival advantages in ESOS cases. Thus, our findings advocate for the prioritisation of primary lesion excision surgery in ESOS, coupled with adjuvant radiotherapy contingent on individual patient circumstances. Furthermore, the employment of our nomogram aids clinicians in anticipating patient prognoses, facilitating the tailoring of treatment strategies accordingly.\u003c/p\u003e"},{"header":"4 Materials and Methods","content":"\u003ch2\u003e4.1 Data sources\u003c/h2\u003e\n\u003cp\u003e\u003cstrong\u003e4.1.1 Data Employed for Characterization Description, Identification of Prognostic Factors, and Nomogram Construction (Case Compilation); Data Utilized for Age-Adjusted Incidence Estimation of Osteosarcoma; Data Employed for Depicting Osteosarcoma Survival Outcomes\u003c/strong\u003e: Surveillance, Epidemiology, and End Results (SEER) Program (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e\u003ca href=\"http://www.seer.cancer.gov\" target=\"_blank\"\u003ewww.seer.cancer.gov\u003c/a\u003e\u003c/span\u003e\u003c/span\u003e) SEER*Stat Database: Incidence - SEER Research Data, 17 Registries, Nov 2022 Sub (2000\u0026ndash;2020) - Linked To County Attributes - Time Dependent (1990\u0026ndash;2021) Income/Rurality, 1969\u0026ndash;2021 Counties, National Cancer Institute, DCCPS, Surveillance Research Program, released April 2023, based on the November 2022 submission.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4.1.2 Data used for calculating the prevalence of osteosarcoma\u003c/strong\u003e: Surveillance, Epidemiology, and End Results (SEER) Program (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e\u003ca href=\"http://www.seer.cancer.gov\" target=\"_blank\"\u003ewww.seer.cancer.gov\u003c/a\u003e\u003c/span\u003e\u003c/span\u003e) SEER*Stat Database: Incidence - SEER Research Data, 17 Registries, Nov 2022 Sub (2000\u0026ndash;2020), National Cancer Institute, DCCPS, Surveillance Research Program, released April 2023, based on the November 2022 submission.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4.1.3 Data used for estimating the age-adjusted mortality of osteosarcoma\u003c/strong\u003e: Surveillance, Epidemiology, and End Results (SEER) Program (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e\u003ca href=\"http://www.seer.cancer.gov\" target=\"_blank\"\u003ewww.seer.cancer.gov\u003c/a\u003e\u003c/span\u003e\u003c/span\u003e) SEER*Stat Database: Incidence-Based Mortality - SEER Research Data, 17 Registries, Nov 2022 Sub (2000\u0026ndash;2020) - Linked to County Attributes - Time Dependent (1990\u0026ndash;2021) Income/Rurality, 1969\u0026ndash;2021 Counties, National Cancer Institute, DCCPS, Surveillance Research Program, released April 2023, based on the November 2022 submission.\u003c/p\u003e\n\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\n\u003ch2\u003e4.2 Patient selection\u003c/h2\u003e\n\u003cp\u003eAs depicted in Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e, the variable 'AYA site recode 2020 Revision' within the SEER program was limited to '4.1 osteosarcoma' for the purpose of selecting osteosarcoma patients from the SEER database. Patients diagnosed between the years 2000 and 2020 were initially encompassed. Subsequently, those patients afflicted with multiple malignant primary cancers and individuals diagnosed posthumously or via death certificate were excluded from consideration. Ultimately, a total cohort of 4,567 osteosarcoma patients was included for the present study. According to the 'Primary Site - labeled' variable, patients were categorised into two groups based on the primary site of the tumour: osteosarcoma patients with tumours originating from bones and joints, designated as the 'osteosarcoma (C40.0-C41.9)' group; osteosarcoma patients with tumours originating from sites beyond the skeletal framework, defined as the 'extra-skeletal osteosarcoma (ESOS)' group.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\n\u003ch2\u003e4.3 Statistics analysis\u003c/h2\u003e\n\u003cp\u003ePatient characteristics were presented as categorical variables, and distinctions between the groups were evaluated using Pearson's chi-squared test within IBM SPSS Statistics (version 26.0, Armonk, NY, USA). Epidemiological data pertaining to osteosarcoma (prevalence, incidence, mortality, and survival) were computed using SEER software (version 8.4.1), with data visualisation performed using GraphPad Prism (version 8.0.2). In the current investigation, prevalence, incidence, and mortality rates were adjusted by employing weighted proportions derived from the corresponding age groups within the 2000 US standard population, thereby mitigating the confounding influence of age.Overall survival (OS) encompassed the interval from the point of diagnosis until death from any cause, encompassing both causes attributed to cancer and those unrelated to cancer. The estimation of survival was undertaken using the Kaplan-Meier (KM) method, while the comparison of curves between distinct groups employed both the Mantel-Cox (log-rank) and Wilcoxon-Breslow-Gehan tests. The identification of independent prognostic factors among ESOS patients was achieved through the application of Cox proportional hazard regression analysis. Variables displaying a P-value below 0.05 in the univariate analysis were subjected to further scrutiny via multivariate regression analysis. The entirety of ESOS patients was randomly partitioned into construction and validation cohorts at a ratio of 7:3. The assessment of the prognostic nomogram's efficacy was conducted via discrimination and calibration analyses. Temporal receiver operating characteristic (tROC) curves were constructed, with corresponding area under the curve (AUC) values computed at intervals of 1, 3, and 5 years. The evaluation of the nomogram's calibration capacity was performed using calibration curves. The creation and subsequent validation of the prognostic nomogram were undertaken within R version 4.2.1 (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.r-project.org/\u003c/span\u003e\u003c/span\u003e).\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eAUC\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eArea under the curve\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eCI\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eConfidence interval\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eDFS\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eDisease-free survival\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eESOS\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eExtra-skeletal Osteosarcoma\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eHR\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eRatio\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eOS\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eOverall survival\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eROC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eReceiver operating characteristic\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eSD\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eStandard deviation\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eSEER\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eSurveillance Epidemiology and End Results\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003e6 Author Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConceptualization: \u0026nbsp;Chao Zhang and Zheng Liu; methodology: Zheng Liu , Zhengzhong Liu and Fapeng Gao; software: Zheng Liu and Li Du; investigation: Chenhua Zhu and Yinan Wang; writing-original draft preparation: Zheng Liu, Zhengzhong Liu and Li Du; writing-review and editing: Elmar R. Musaev; visualization: Haixiao Wu and Jun Wang; supervision: Chao Zhang. The work reported in the paper has been performed by the authors, unless clearly specified in the text. All authors have read and agreed to the published version of the manuscript.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e7 Acknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors acknowledged the contributions made by the National Cancer Institute and the Surveillance, Epidemiology, and End Results (SEER) Program tumor registries in the creation of the SEER database.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e8 Conflict of Interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors have read and approved the final submitted manuscript. Each author certifies that he or she has no commercial associations (e.g., consultancies, stock ownership, equity interest, patent/licensing arrangements, etc.) that might pose a conflict of interest in connection with the submitted article. Institutional review board approval was not needed for this study and therefore not obtained prior to initiation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e9 Ethics statement\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was conducted in accordance with the Declaration of Helsinki while ethical board approval was not required because the SEER program provides public domain data without personal medical identifiers.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e10 Consent\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was conducted in accordance with the Declaration of Helsinki while ethical board approval was not required because the SEER program provides public domain data without personal medical identifiers. The data used and analyzed in this study are available in the Surveillance, Epidemiology, and End Results (SEER) Database of the National Cancer Institute (http://seer.cancer.gov). Further information is available from the corresponding author upon request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e11 Funding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe present study was sponsored by Joint Guidance Project of Provincial Natural Science Foundation (LH2020H119), Heilongjiang Medical and Health Research Project (2020-257), and Traditional Chinese medicine research project in Heilongjiang Province (ZHY2020-066).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e12 Data availability statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analysed during the current study available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003e Bane BL, Evans HL, Ro JY, Carrasco CH, Grignon DJ, Benjamin RS and Ayala AG. Extraskeletal osteosarcoma. A clinicopathologic review of 26 cases. 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The Role of Chemotherapy in Extraskeletal Osteosarcoma: A Propensity Score Analysis of the Surveillance Epidemiology and End Results (SEER) Database. Med Sci Monitor. 2020; 26:e925107.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e Hui J, Zhao Y, Zhang L, Lin J and Zhao H. Primary orbital extraskeletal osteosarcoma and review of literature. Bmc Ophthalmol. 2020; 20(1):425.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e Heng M, Gupta A, Chung PW, Healey JH, Vaynrub M, Rose PS, Houdek MT, Lin PP, Bishop AJ, Hornicek FJ, Chen YL, Lozano-Calderon S and Holt GE, et al. The role of chemotherapy and radiotherapy in localized extraskeletal osteosarcoma. Eur J Cancer. 2020; 125:130\u0026ndash;141.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e Wiklund TA, Blomqvist CP, Raty J, Elomaa I, Rissanen P and Miettinen M. Postirradiation sarcoma. Analysis of a nationwide cancer registry material. 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Pol J Radiol. 2014; 79:228\u0026ndash;232.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Extra-skeletal Osteosarcoma, Epidemiology, Overall survival, Nomograms, SEER program","lastPublishedDoi":"10.21203/rs.3.rs-4072434/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4072434/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe aim of this study was to investigate the epidemiological characteristics and prognostic factors of Extra-skeletal Osteosarcoma (ESOS) and to establish and validate a prognostic model. The baseline information and survival outcome of patients was illustrated according to different primary tumor sites. The independent prognostic factors for ESOS were analyzed using univariate and multivariate Cox regression analysis. A nomogram was constructed using these prognostic factors to predict the prognostic survival of patients. Kaplan-Meier method was performed to estimate survival and both log-rank test and Wilcoxon-Breslow-Gehan test were used to compare the survival. A total of 4567 patients with osteosarcoma who met the inclusion criteria were enrolled, including 4317 patients with osteosarcoma of bone and joint origin and 250 patients with ESOS. The 1-, 3-, and 5-year tumor-specific survival rates for ESOS were lower than those for skeletal osteosarcoma. Multivariate Cox analysis showed that older age at diagnosis, distant staging, and presence of bone metastases were independent risk factors affecting patient prognosis, and surgery of the primary site was an independent factor suggesting a better survival outcome. A nomogram was created based on these factors to predict OS at 1, 3 and 5 years in patients with ESOS. An internally validated nomogram consistency index showed satisfactory results between predictions. Primary focus surgery is an important factor in improving survival outcomes in patients with ESOS. The nomogram for predicting the prognostic of patients with ESOS was proved to be favorable accuracy and reliability. Such prognostic nomogram may assist clinicians optimize clinical treatment.\u003c/p\u003e","manuscriptTitle":"Epidemiological and clinicopathologic characteristics, and prognostic factors of patients with Extra-skeletal Osteosarcoma","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-03-29 17:31:57","doi":"10.21203/rs.3.rs-4072434/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"04a18328-3c6e-4d8b-aad0-c1725b8eae40","owner":[],"postedDate":"March 29th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":29877796,"name":"Biological sciences/Cancer"},{"id":29877797,"name":"Health sciences/Diseases"},{"id":29877798,"name":"Health sciences/Medical research"},{"id":29877799,"name":"Health sciences/Oncology"},{"id":29877800,"name":"Health sciences/Pathogenesis"},{"id":29877801,"name":"Health sciences/Risk factors"}],"tags":[],"updatedAt":"2024-10-08T06:54:23+00:00","versionOfRecord":[],"versionCreatedAt":"2024-03-29 17:31:57","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4072434","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4072434","identity":"rs-4072434","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}