Primary Tumor Resection Prolongs Survival in Spinal Chondrosarcoma Patients With Distant Metastasis

Clinical characteristic-assisted surgical benefit stratification for resection of primary tumor in patients with advanced primary malignant bone neoplasms: a population-based propensity score-matched analysis

Background

Primary tumor resection (PTR) is the standard treatment for patients with primary malignant bone neoplasms (PMBNs). However, it remains unclear whether patients with advanced PMBNs still benefit from PTR. This study aimed to develop a prediction model to estimate the beneficial probability of PTR for this population.

Methods

This study extracted data from patients diagnosed with advanced PMBNs, as recorded in the Surveillance, Epidemiology, and End Results (SEER) database, with the period from 2004 to 2015. The patient cohort was then bifurcated into two groups: those who underwent surgical procedures and the non-surgery group. Propensity score matching (PSM) was utilized to mitigate any confounding factors in the study. The survival rates of patients from both the surgical and non-surgery groups were evaluated using Kaplan-Meier (K-M) curves analysis. Moreover, the study used this method to assess the capacity of the nomogram to distinguish patients likely to derive benefits from surgical intervention. The study was grounded in the hypothesis that patients who underwent PTR and survived beyond the median overall survival (OS) time would potentially benefit from the surgery. Subsequently, logistic regression analysis was performed to ascertain significant predictors, facilitating the development of a nomogram. This nomogram was subjected to both internal and external validation using receiver operating characteristic curves, area under the curve analysis, calibration plots, and decision curve analysis.

Results

The SEER database provided a total of 839 eligible patients for the study, among which 536 (63.9%) underwent PTR. Following a 2:1 PSM analysis, patients were classified into two groups: 364 patients in the surgery group and 182 patients in the non-surgery group. Both K-M curves and multivariate Cox regression analysis revealed that patients who received PTR had a longer survival duration, observed both before and after PSM. Crucial factors such as age, M stage, and tumor size were identified to be significantly correlated with surgical benefits in patients with advanced PMBNs. Subsequently, a nomogram was developed that uses these independent predictors. The validation of this predictive model confirmed its high accuracy and excellent discrimination ability of the nomogram to distinguish patients who would most likely benefit from surgical intervention.

Conclusion

In this study, we devised a user-friendly nomogram to forecast the likehood of surgical benefits for patients diagnosed with advanced PMBNs. This tool facilitates the identification of the most suitable candidates for PTR, thus promoting more discerning and effective use of surgical intervention in this patient population.

Development and validation of a nomogram for predicting prognosis of high-grade chondrosarcoma: A surveillance, epidemiology, and end results-based population analysis

BACKGROUND

The incidence of chondrosarcoma is increasing every year, and the treatment and prognosis of patients with high-grade chondrosarcoma are becoming more and more important. Nomogram is a tool that can quickly and easily predict the overall survival of tumor patients. Therefore, the development and validation of a nomogram to predict overall survival in patients with high-grade chondrosarcoma was desired.

METHODS

We retrospectively collected 396 patients with high-grade chondrosarcoma from the Surveillance, Epidemiology, and End Results (SEER) database from 2004 to 2015. Randomly divided into model and validation groups, the best cut-off values for age and tumor size grouping were derived by using X-tile software. Then, independent prognostic factors for high-grade chondrosarcoma were derived by SPSS.26 univariate and multivariate Cox analyses analysis in the model group, and the model was evaluated by using R software, using C-indix and ROC curves, and finally these independent prognostic factors were included in Nomogram.

RESULTS

396 patients were randomly assigned to the modelling group (n = 280) or the validation group (n = 116). Age, tissue-type, tumor size, AJCC stage, regional expansion and surgery were identified as independent prognostic factors (p < 0.05) which further combined to construct a nomogram. The C-index of internal validation for overall survival(OS) was 0.757, while the C-index of external validation for overall survival(OS) was 0.832. Both internal and external calibration curves show a good agreement between nomogram prediction and actual survival.

CONCLUSION

In this study, we established age, tumour size, AJCC stage, tissue type, surgery and tumor extension as independent prognostic factors for high-grade chondrosarcoma and constructed a nomogram to predict 3- and 5-year survival rates for high-grade chondrosarcoma.

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

BACKGROUND

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

QUESTIONS/PURPOSES

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

METHODS

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

RESULTS

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

CONCLUSION

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

LEVEL OF EVIDENCE

Level III, therapeutic study.

The clinicopathological characteristics and prognosis of young patients with chondrosarcoma of bone

Purpose

Clinicopathologic characteristics and treatment outcomes for young patients (less than 40 years) with chondrosarcoma of bone are rarely documented. The purpose of this study is to determine the clinicopathological characteristics and identify the survival predictors for this rare population.

Patients and Methods

We used the Surveillance, Epidemiology, and End Results (SEER) database to identify young patients with chondrosarcoma of bone between 1973 and 2016. Univariate and multivariate Cox regression analyses were conducted to determine the independent risk factors. Kaplan-Meier method was used to intuitively show the survival difference stratified by different treatments.

Results

A total of 1312 eligible young patients with chondrosarcoma of bone were analyzed this study. The mean age at diagnosis was 28.5 ± 0.2 years old (ranging from 1 to 40 years). 51.1% of cases were located in the extremity. More than two-thirds of patients (71.4%) were high grade. The majority of the patients (92.0%) received surgery, only 11.8% of patients received radiotherapy, and only 10.4% of patients received chemotherapy. The 5-year overall survival (OS) and cancer-specific survival (CSS) rates of this cohort were 88.5% and 89.1%, respectively. According to the results of multivariate analysis, nine variables were significantly correlated with OS and CSS, including gender, year of diagnosis, tumor site, tumor grade, tumor subtype, distant metastasis, tumor size, surgery, and chemotherapy.

Conclusion

Young patients with chondrosarcoma of bone experienced better prognosis. Surgery was significantly correlated with increased survival, while chemotherapy was significantly correlated with decreased survival. Radiotherapy was not a meaningful survival predictor of young patients with chondrosarcoma of bone. Prospective clinical trials are needed in the future to determine the effect of radiotherapy and chemotherapy on prognosis of those patients.

Individualized assessment of risk and overall survival in patients newly diagnosed with primary osseous spinal neoplasms with synchronous distant metastasis

Background

The prognosis of patients with primary osseous spinal neoplasms (POSNs) presented with distant metastases (DMs) is still poor. This study aimed to evaluate the independent risk and prognostic factors in this population and then develop two web-based models to predict the probability of DM in patients with POSNs and the overall survival (OS) rate of patients with DM.

Methods

The data of patients with POSNs diagnosed between 2004 and 2017 were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. Univariate and multivariate logistics regression analyses were used to study the risk factors of DM. Based on independent DM-related variables, we developed a diagnostic nomogram to estimate the risk of DM in patients with POSNs. Among all patients with POSNs, those who had synchronous DM were included in the prognostic cohort for investigating the prognostic factors by using Cox regression analysis, and then a nomogram incorporating predictors was developed to predict the OS of patients with POSNs with DM. Kaplan-Meier (K-M) survival analysis was conducted to study the survival difference. In addition, validation of these nomograms were performed by using receiver operating characteristic (ROC) curves, the area under curves (AUCs), calibration curves, and decision curve analysis (DCA).

Results

A total of 1345 patients with POSNs were included in the study, of which 238 cases (17.70%) had synchronous DM at the initial diagnosis. K-M survival analysis and multivariate Cox regression analysis showed that patients with DM had poorer prognosis. Grade, T stage, N stage, and histological type were found to be significantly associated with DM in patients with POSNs. Age, surgery, and histological type were identified as independent prognostic factors of patients with POSNs with DM. Subsequently, two nomograms and their online versions (https://yxyx.shinyapps.io/RiskofDMin/ and https://yxyx.shinyapps.io/SurvivalPOSNs/) were developed. The results of ROC curves, calibration curves, DCA, and K-M survival analysis together showed the excellent predictive accuracy and clinical utility of these newly proposed nomograms.

Conclusion

We developed two well-validated nomograms to accurately quantify the probability of DM in patients with POSNs and predict the OS rate in patients with DM, which were expected to be useful tools to facilitate individualized clinical management of these patients.

Experience in utilizing a novel 3D digital model with CT and MRI fusion data in sarcoma evaluation and surgical planning

OBJECTIVE

To assess sarcoma margins with more accuracy and aid surgical planning, we constructed three-dimensional (3D) digital models with computed tomography(CT) and magnetic resonance imaging (MRI) image fusion data and validated the preciseness of the models by comparing them with 3D models constructed with CT only data.

MATERIALS AND METHODS

We retrospectively reviewed a consecutive set of patients treated in our center who were preoperatively evaluated with the fusion image model. Models based on fusion images or CT-only data were constructed. Volumes of both tumors were calculated and the tumors were overlapped to see the location of differences between the two models.

RESULTS

A consecutive 12 cases (4 male vs. 8 female) were included in this study. Most of the tumors were located in the pelvic bone or spine. The volume of the two tumor models was different and the differences were mainly in the peripheral region of the tumor.

CONCLUSION

CT and MRI fusion image 3D models are more accurate than models with CT-only data and can be very helpful in preoperative planning of sarcoma patients.

Trends in Tumor Site-Specific Survival of Bone Sarcomas from 1980 to 2018: A Surveillance, Epidemiology and End Results-Based Study

OBJECTIVES

As diagnosis and treatment guidelines for bone sarcomas continue updating, it is important to examine whether, when, and which kinds of patients have had a survival improvement over the last four decades.

METHODS

This cohort study included 9178 patients with primary bone and joint sarcomas from 1 January 1980 to 31 December 2018 using data from Surveillance, Epidemiology and End Results (SEER)-9 Registries. The follow-up period was extended to November 2020. Patients were divided by decade into four time periods: 1980-1989, 1990-1999, 2000-2009, and 2010-2018. The primary endpoint was bone sarcomas-specific mortality (CSM). The 5-year bone sarcomas-specific survival (CSS) rate was determined stratified by demographic, neoplastic, temporal, economic, and geographic categories. The associations between time periods and CSM were examined using a multivariable Cox regression model, with reported hazard ratio (HR) and 95% confidence interval (CI).

RESULTS

The 5-year CSS rate for bone sarcomas was 58.7%, 69.9%, 71.0%, and 69.2%, in the 1980s, 1990s, 2000s, and 2010s, respectively. Older age, male gender, tumor sites at pelvic bones, sacrum, coccyx and associated joints, as well as vertebral column, osteosarcoma and Ewing tumor, and residence in non-metropolitan areas were independently associated with higher CSM risk. After adjusting for the covariates above, patients in the 1990s (HR = 0.74, 95% CI = 0.68-0.82), 2000s (HR = 0.71, 95% CI = 0.65-0.78), and 2010s (HR = 0.68, 95% CI = 0.62-0.76) had significantly lower CSM risks than patients in the 1980s. However, patients in the 2000s and 2010s did not have lower CSM risks than those in the 1990s (both p > 0.05).

CONCLUSIONS

Although bone sarcomas survival has significantly improved since 1990, it almost halted over the next three decades. Bone sarcomas survival should improve over time, similar to common cancers. New diagnostic and therapeutic strategies such as emerging immune and targeted agents are warranted to overcome this survival stalemate.