Establishing a novel prognostic tool for Ewing sarcoma patients: Surveillance, Epidemiology, and End Results database analysis

Prognostic Modeling for Bone Sarcomas Based on a Large Prospective Cohort From a Tertiary Care Cancer Center in India

PURPOSE

Outcomes of adolescents and young adults (AYA) with bone sarcomas including osteosarcoma (OGS) and Ewing sarcoma (ES) are affected by various factors including inadvertent previous treatment and poor compliance. We aimed to develop a risk-scoring system derived and validated at a tertiary care cancer center in India.

METHODS

All AYA OGS and ES cases treated at our institute with OGS-12 and Ewing's family of tumors-2001 (EFT-2001) protocols from 2011 to 2021 and 2013 to 2018, respectively, were prospectively analyzed. Weighted scores provided to each prognostic variable on the basis of approximate ratios of the beta coefficients of each factor in the multivariable model were summated to divide patients into three clinically discriminatory risk groups, validated by applying separately to derivation, validation, and whole cohorts.

RESULTS

Among 606 (81.0%) of 748 AYA with nonmetastatic OGS, significant factors included in the prognostic model were failure to complete protocol (hazard ratio [HR], 2.65), previous treatment (HR, 2.93), necrosis <90% (HR, 1.63), joint involvement (HR, 2.0), and serum alkaline phosphatase >median (204 U/L; HR, 1.63). Of 104 (39.5%) of 263 AYA with ES, significant factors were failure to complete protocol (HR, 2.84), previous treatment (HR, 6.37), necrosis <100% (HR, 8.73), and tumor size >8 cm (HR, 2.64). For 142 (38.8%) of 366 AYA with metastatic OGS, significant factors were failure to complete protocol (HR, 5.29), metastases not amenable to local treatment (HR, 1.96), necrosis <90% (HR, 1.96), and >10 metastases (HR, 2.44). For 38 (43.6%) of 82 AYA with metastatic extremity ES, significant factors were failure to complete protocol (HR, 3.88) and metastases not amenable to local treatment (HR, 10.6).

CONCLUSION

We developed simple, effective prognostic models for AYA with bone sarcomas with specific potential relevance for low- and middle-income countries.

The development and external validation of a web-based nomogram for predicting overall survival with Ewing sarcoma in children

Background

Ewing sarcoma remains the second most prevalent primary aggressive bone tumor in teens and young adults. The aim of our study was to develop and validate a web-based nomogram to predict the overall survival for Ewing sarcoma in children.

Methods

A total of 698 patients, with 640 cases from the Surveillance, Epidemiology, and End Results (the training set) and 58 cases (the external validation set), were included in this study. Cox analyses were carried out to determine the independent prognostic indicators, which were further included to establish a web-based nomogram. The predictive abilities were tested through the concordance index, calibration curve, decision curve analysis, and area under the receiver operating characteristic curve.

Results

As suggested by univariate and multivariate Cox analyses, age, primary site, tumor size, metastasis stage (M stage), and chemotherapy were included as the independent predictive variables. The area under the receiver operating characteristic curve values, calibration curves, concordance index, and decision curve analysis from training and validation groups suggested the model has great clinical applications.

Conclusion

We developed a convenient and precise web-based nomogram to evaluate overall survival for Ewing sarcoma in children. The application of this nomogram would assist physicians and patients in making decisions.

The Clinical Characteristics, Risk Classification System, and Web-Based Nomogram for Primary Spinal Ewing Sarcoma: A Large Population-Based Cohort Study

BACKGROUND

The goal of this study was to determine the clinical characteristics of patients with primary spinal Ewing sarcoma (PSES) and to create a prognostic nomogram.

METHODS

Clinical information related to patients diagnosed with PSES between 2004 and 2015 was extracted from the Surveillance, Epidemiology, and End Results (SEER) database. Independent prognostic factors were identified using univariate and multivariate Cox analyses to construct nomograms predicting overall survival in patients with PSES. Calibration curves and receiver operating characteristic curves were used to assess the model's prediction accuracy, while decision curve analysis was used to assess the model's clinical utility.

RESULTS

The overall number of 314 patients with PSES were screened from the SEER database between 2004 and 2015. Race, chemotherapy, age, and disease stage were found to be independent predictive factors for overall survival in both univariate and multivariate Cox analyses. The training and validation cohorts' calibration curves, receiver operating characteristic curves, and decision curve analysis showed that the nomogram has strong discrimination and clinical value. Furthermore, a new risk classification system has been constructed that can divide all patients into 2 risk groups.

CONCLUSIONS

Based on a broad population, the research demonstrates statistical evidence for the clinical features and prognostic variables of patients with PSES. The constructed prognostic nomogram provides a more precise prediction of prognosis for PSES patients.

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.

Development and validation of a prognostic score at baseline diagnosis for Ewing sarcoma family of tumors: a retrospective single institution analysis of 860 patients

INTRODUCTION

Prognostic scores in Ewing sarcoma including baseline clinical and laboratory characteristics are necessary for pre-treatment risk stratification. In this study, we formulated and validated a prognostic model for baseline risk categorization in Ewing sarcoma.

MATERIALS AND METHODS

A retrospective single-institutional study was conducted on Ewing sarcoma patients treated uniformly between January 2003 and December 2018. Baseline clinical/pathological characteristics and survival outcomes were noted from medical records. The cohort was randomised into a derivation and validation cohort. A prognostic score was formulated by including independent prognostic factors from the derivation cohort by multivariable analysis. The prognostic model was validated in the validation cohort along with estimation of its predictive ability.

RESULTS

A total of 860 patients were included with 40.3% having baseline metastases. Tumor diameter >5 cm (HR 2.04; P<0.001; score 2), baseline metastases (HR 2.33; P<0.001, score 2), and total leucocyte count >11000/mm3 (HR 1.44; P=0.015; score 1) were independent predictors of overall survival in derivation cohort and included for prognostic score calculation. Patients were categorized into low (score 0), intermediate (score 1-3) and high-risk (score 4-5) groups. Harrell's c-indexes of the model were 0.625, 0.622 and 0.624 in the derivation, validation and whole cohort respectively. The timed AUC of ROC of the prognostic score-group for 5-year survival was 0.72, 0.71 and 0.73 in the derivation, validation and whole cohort respectively.

CONCLUSIONS

We have formulated and validated a prognostic score for Ewing sarcoma incorporating baseline clinical and laboratory parameters, with fair predictive ability for risk stratification and facilitating risk-adapted personalized therapy.