Epidemiological and clinicopathologic characteristics, and prognostic factors of patients with extra-skeletal osteosarcoma: a Surveillance, Epidemiology, and End Results population study

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 (1-5). Distinguished by its tumor 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 tumor 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 (12). Compared to osteosarcoma, ESOS patients face a bleaker prognosis, reflected in a suboptimal 5-year overall survival (OS) rate of less than 50% (13-15). While earlier studies have underscored the significance of prognostic factors like age, tumor grade, tumor size, surgical intervention, and chemotherapy in shaping ESOS patients’ outlook (16,17), ESOS’s low incidence has limited related literature to mostly case reports and small-sample retrospective analyses, leaving its comprehensive attributes and population-level prognosis incompletely delineated. Thus, this study aims to address this gap by using large-scale SEER population-based data to systematically characterize ESOS’s epidemiological (prevalence, incidence, mortality) and clinicopathologic features, identify its independent prognostic factors via Cox regression analyses, and construct and internally validate a nomogram for predicting 1-, 3-, and 5-year OS in ESOS patients—providing actionable clinical guidance. Hence, the establishment of predictive models designed to prognosticate ESOS patient outcomes emerges as an imperative undertaking.

Consequently, a comprehensive analysis of ESOS was undertaken, encompassing demographic profiles, OS 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. We present this article in accordance with the TRIPOD reporting checklist (available at https://tcr.amegroups.com/article/view/10.21037/tcr-2025-605/rc).

Methods

Data sources

• 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: 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, Division of Cancer Control and Population Sciences (DCCPS), Surveillance Research Program, released April 2023, based on the November 2022 submission.
• Data used for calculating the prevalence of osteosarcoma: SEER Program. 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.
• Data used for estimating the age-adjusted mortality of osteosarcoma: SEER Program. 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.

Patient selection

As depicted in Figure 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 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 categorized into two groups based on the primary site of the tumor: osteosarcoma patients with tumors originating from bones and joints, designated as the “osteosarcoma (C40.0-C41.9)” group; osteosarcoma patients with tumors originating from sites beyond the skeletal framework, defined as the “ESOS” group. To ensure comparability between the skeletal osteosarcoma and ESOS cohorts, identical exclusion criteria were applied to both groups. This included the removal of cases with multiple primary malignancies and those diagnosed posthumously or via death certificate. These criteria were implemented to minimize potential confounding factors that might differentially affect survival outcomes in either cohort. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments.

Figure 1 The detailed flow-chart for patient selection in the present study. ESOS, extra-skeletal osteosarcoma.

Statistical 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 visualization 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 2,000 US standard population, thereby mitigating the confounding influence of age.

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-year. 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/).

Results

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, tumor 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 2 provides a comprehensive listing of patient numbers and detailed demographic, clinicopathologic, and survival data for ESOS, organized in accordance with distinct primary tumor 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 OS rates stood at 42.4% for patients with primary tumors 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.

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 2,000 US standard population. Illustrated in Figure 2A, 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 behavior 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 (Figure 2B). Figure 2C delineates 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. Moreover, Figure 2D 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-, 3-, 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%.

Figure 2 The epidemiological performance of patients with ESOS. (A) The 20-year limited-duration prevalence of osseous osteosarcoma (C40.0-C41.9) and ESOS; (B) the age-adjusted incidence of osseous osteosarcoma (C40.0-C41.9) and ESOS; (C) the age-adjusted mortality of osseous osteosarcoma (C40.0-C41.9) and ESOS; (D) the observed survival and cancer-specific survival of osseous osteosarcoma (C40.0-C41.9) and ESOS. ESOS, extra-skeletal osteosarcoma.

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 tumor 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 =1.032, 95% CI: 1.023–1.042; P<0.001), distant stage (HR =3.042, 95% CI: 1.658–5.579; P<0.001), and the presence of bone metastasis (HR =4.711, 95% CI: 1.948–11.393; P=0.001) stood as independent adverse prognostic factors. Notably, primary tumor surgery (HR =0.19, 95% CI: 0.12–0.29; P<0.001) emerged as an autonomous factor indicative of enhanced survival outcomes.

The examination of the impact of diverse surgical approaches on survival outcomes across different primary tumor 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 tumors originating from soft tissue (P<0.001). Within the “Soft Tissue including Heart” subgroup, the mean OS extended to 123.3 (95% CI: 89.8–156.7) months for individuals undergoing partial resection and 117.6 (95% CI: 92.2–143.1) months for those undergoing radical excision. Notably, patients subjected to amputation exhibited a considerably less favorable mean OS of 21.5 (95% CI: 10.3–32.6) months. The survival trajectories of the total cohort, as well as those for patients harboring distinct primary tumor sites, are graphically depicted in Figure 3.

Figure 3 The survival curves of patients with ESOS. (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. ESOS, extra-skeletal osteosarcoma.

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 Figure 4A. The tROC curves in Figure 4B depict commendable discriminatory capacity of the model, with corresponding AUC values at 1-, 3-, and 5-year intervals standing at 0.848, 0.793, and 0.805, respectively. Evaluation of calibration prowess, as illustrated in Figure 4C, 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 Figure 4D,4E. In this context, the nomogram consistently exhibited pronounced discriminatory strength and adept calibration (Figure 4D,4E). Noteworthy AUC values for the nomogram across the 1-, 3-, and 5-year spans were observed at 0.778, 0.800, and 0.748, respectively. 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 Figure 5A for the construction cohort and Figure 5B 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.

Figure 4 The construction and validation of the predictive nomogram for patients with ESOS. (A) The nomogram predicting the 1-, 3-, and 5-year survival for patients with ESOS. (B) The time-dependent ROC curve of the nomogram in the construction cohort. (C) The calibration curve of the nomogram in the construction cohort. (D) The time-dependent ROC curve of the nomogram in the validation cohort. (E) The calibration curve of the nomogram in the validation cohort. AUC, area under the curve; ESOS, extra-skeletal osteosarcoma; FPR, false positive rate; ROC, receiver operating characteristic; TPR, true positive rate.

Figure 5 The distribution of risk scores for ESOS patients and their corresponding actual survival outcomes and predictive factors information. (A) for the construction cohort and (B) for the validation cohort, respectively. ESOS, extra-skeletal osteosarcoma.

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. The rise in ESOS prevalence likely reflects improved diagnostic accuracy, an aging population, and survival prolongation from treatment advancements. 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 OS 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 unfavorable, there is discernible improvement in OS over the temporal course, mirroring advancements in anticancer therapeutics.

The patients afflicted by ESOS exhibited an age range of 47–61 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 (18,19). 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 was 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 (20). 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. Furthermore, marital status exhibited a notable discrepancy between the groups. A higher proportion (54.8%) of ESOS patients were married, a factor that may impact treatment compliance and clinical outcomes. While the median household income did not show a statistically significant association with treatment responses, a trend suggested that higher-income groups tended to have more favorable outcomes, potentially reflecting better access to specialized medical care and comprehensive treatment resources. This observation aligns with the broader understanding that socioeconomic factors can influence healthcare utilization and disease management, underscoring the need for integrated approaches to address both medical and social determinants of health in ESOS patient care.

ESOS, by its nature, presents an unfavorable prognosis. According to Chung et al. (19), patients diagnosed with ESOS exhibited a 3-year mortality rate exceeding 50%. A European multicenter study involving 266 ESOS patients reported a 5-year OS rate of 47% (15). Our study yielded similar findings, with corresponding 3- and 5-year OS 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 (12,15,16,21-24). Goldstein-Jackson et al. (25) 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 1-, 3-, and 5-year OS 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 (13,26). 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 (4,8,27-29). 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 (18,22,30-34). Additionally, ESOS originating from diverse systemic sites exhibit disparate tissue origins, consequently engendering distinct biological behaviors and, by extension, discernible differences in survival outcomes. Notably, amputation patients showed poorer survival, likely due to selection for advanced-stage/tumor-invasiveness (amputation for unresectable lesions). Survival disparity with conservative resection stems from tumor aggressiveness/surgical bias. Amputation applies to large, advanced tumors (worse prognosis) and older patients with lower surgical tolerance.

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 (5,20,24,35). The role of chemotherapy in managing ESOS patients remains a contentious topic (14,15,36,37). In the context of localized ESOS, the amalgamation of surgical intervention with diverse chemotherapy regimens appears to hold promise for enhancing OS (25,38). A comprehensive examination by Longhi et al. (15) across multiple centers illustrated elevated survival rates among individuals subjected to perioperative chemotherapy, with an inclination towards potential effectiveness of osteosarcoma chemotherapy protocols. Conversely, Qi et al. (39) partitioned 310 ESOS patients into cohorts with and without chemotherapy exposure, arriving at the conclusion that the chemotherapy group did not 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 (12,40). 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 (15). Consequently, there exists a rationale to abstain from routinely endorsing chemotherapy as a standard ESOS treatment (41). 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 efficacy of radiotherapy for ESOS is limited, and the constraints of the treatment sites result in its non-routine adoption (18,21,42). Generally, radiotherapy serves a palliative function for ESOS patients either burdened with inoperable primary lesions or grappling with metastatic afflictions. Certain ESOS locations (e.g., abdominal or thoracic sites) present technical challenges for radiotherapy delivery, while the historical emphasis on surgical resection as the primary treatment modality may have contributed to lower radiotherapy utilization (24,38,43,44). The coupling of surgical intervention with radiotherapy has demonstrated efficacy in diminishing tumor size and local recurrence rates. However, it falls short of significantly influencing ESOS prognosis (20). Wang et al. (13) demonstrated an augmentation in the OS rate among patients harboring ESOS with surgically positive margins who underwent radiotherapy. In our study, over two-thirds of ESOS patients received radiotherapy, with one-third of these cases involving the limbs. This practice is ostensibly aimed at reducing tumor recurrence and achieving negative surgical margins. Due to the relatively sparse distribution of blood vessels and nerves in the limbs, radiotherapy poses a lower risk of damage to vital organs, making it more suitable for tumor control in the limbs compared to areas such as the neck, thorax, and abdomen.

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 (15). 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 tumor 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 endeavors, its retrospective design is one. Future prospects necessitate prospective randomized clinical trials to furnish high-caliber clinical evidence for application. Additionally, the SEER database omits certain data points, including tumor size, growth depth, and resection specimen margin status, and lacks detailed chemotherapy regimen information, preventing analysis of specific protocols in treatment approaches for ESOS. Neglecting these factors could potentially overlook facets 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.

Conclusions

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 tumor 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 prioritization 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.

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.

Footnote

Reporting Checklist: The authors have completed the TRIPOD reporting checklist. Available at https://tcr.amegroups.com/article/view/10.21037/tcr-2025-605/rc

Peer Review File: Available at https://tcr.amegroups.com/article/view/10.21037/tcr-2025-605/prf

Funding: The study was supported 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).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tcr.amegroups.com/article/view/10.21037/tcr-2025-605/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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