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The Bone & Joint Journal
Vol. 105-B, Issue 6 | Pages 702 - 710
1 Jun 2023
Yeramosu T Ahmad W Bashir A Wait J Bassett J Domson G

Aims. The aim of this study was to identify factors associated with five-year cancer-related mortality in patients with limb and trunk soft-tissue sarcoma (STS) and develop and validate machine learning algorithms in order to predict five-year cancer-related mortality in these patients. Methods. Demographic, clinicopathological, and treatment variables of limb and trunk STS patients in the Surveillance, Epidemiology, and End Results Program (SEER) database from 2004 to 2017 were analyzed. Multivariable logistic regression was used to determine factors significantly associated with five-year cancer-related mortality. Various machine learning models were developed and compared using area under the curve (AUC), calibration, and decision curve analysis. The model that performed best on the SEER testing data was further assessed to determine the variables most important in its predictive capacity. This model was externally validated using our institutional dataset. Results. A total of 13,646 patients with STS from the SEER database were included, of whom 35.9% experienced five-year cancer-related mortality. The random forest model performed the best overall and identified tumour size as the most important variable when predicting mortality in patients with STS, followed by M stage, histological subtype, age, and surgical excision. Each variable was significant in logistic regression. External validation yielded an AUC of 0.752. Conclusion. This study identified clinically important variables associated with five-year cancer-related mortality in patients with limb and trunk STS, and developed a predictive model that demonstrated good accuracy and predictability. Orthopaedic oncologists may use these findings to further risk-stratify their patients and recommend an optimal course of treatment. Cite this article: Bone Joint J 2023;105-B(6):702–710


The Bone & Joint Journal
Vol. 106-B, Issue 2 | Pages 203 - 211
1 Feb 2024
Park JH Won J Kim H Kim Y Kim S Han I

Aims

This study aimed to compare the performance of survival prediction models for bone metastases of the extremities (BM-E) with pathological fractures in an Asian cohort, and investigate patient characteristics associated with survival.

Methods

This retrospective cohort study included 469 patients, who underwent surgery for BM-E between January 2009 and March 2022 at a tertiary hospital in South Korea. Postoperative survival was calculated using the PATHFx3.0, SPRING13, OPTIModel, SORG, and IOR models. Model performance was assessed with area under the curve (AUC), calibration curve, Brier score, and decision curve analysis. Cox regression analyses were performed to evaluate the factors contributing to survival.


The Bone & Joint Journal
Vol. 105-B, Issue 7 | Pages 808 - 814
1 Jul 2023
Gundavda MK Lazarides AL Burke ZDC Focaccia M Griffin AM Tsoi KM Ferguson PC Wunder JS

Aims

The preoperative grading of chondrosarcomas of bone that accurately predicts surgical management is difficult for surgeons, radiologists, and pathologists. There are often discrepancies in grade between the initial biopsy and the final histology. Recent advances in the use of imaging methods have shown promise in the ability to predict the final grade. The most important clinical distinction is between grade 1 chondrosarcomas, which are amenable to curettage, and resection-grade chondrosarcomas (grade 2 and 3) which require en bloc resection. The aim of this study was to evaluate the use of a Radiological Aggressiveness Score (RAS) to predict the grade of primary chondrosarcomas in long bones and thus to guide management.

Methods

A total of 113 patients with a primary chondrosarcoma of a long bone presenting between January 2001 and December 2021 were identified on retrospective review of a single oncology centre’s prospectively collected database. The nine-parameter RAS included variables from radiographs and MRI scans. The best cut-off of parameters to predict the final grade of chondrosarcoma after resection was determined using a receiver operating characteristic curve (ROC), and this was correlated with the biopsy grade.


Bone & Joint Open
Vol. 4, Issue 6 | Pages 424 - 431
5 Jun 2023
Christ AB Piple AS Gettleman BS Duong A Chen M Wang JC Heckmann ND Menendez L

Aims

The modern prevalence of primary tumours causing metastatic bone disease is ill-defined in the oncological literature. Therefore, the purpose of this study is to identify the prevalence of primary tumours in the setting of metastatic bone disease, as well as reported rates of pathological fracture, postoperative complications, 90-day mortality, and 360-day mortality for each primary tumour subtype.

Methods

The Premier Healthcare Database was queried to identify all patients who were diagnosed with metastatic bone disease from January 2015 to December 2020. The prevalence of all primary tumour subtypes was tabulated. Rates of long bone pathological fracture, 90-day mortality, and 360-day mortality following surgical treatment of pathological fracture were assessed for each primary tumour subtype. Patient characteristics and postoperative outcomes were analyzed based upon whether patients had impending fractures treated prophylactically versus treated completed fractures.