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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. Results. The SORG model demonstrated the highest discriminatory accuracy with AUC (0.80 (95% confidence interval (CI) 0.76 to 0.85)) at 12 months. In calibration analysis, the PATHfx3.0 and OPTIModel models underestimated survival, while the SPRING13 and IOR models overestimated survival. The SORG model exhibited excellent calibration with intercepts of 0.10 (95% CI -0.13 to 0.33) at 12 months. The SORG model also had lower Brier scores than the null score at three and 12 months, indicating good overall performance. Decision curve analysis showed that all five survival prediction models provided greater net benefit than the default strategy of operating on either all or no patients. Rapid growth cancer and low serum albumin levels were associated with three-, six-, and 12-month survival. Conclusion. State-of-art survival prediction models for BM-E (PATHFx3.0, SPRING13, OPTIModel, SORG, and IOR models) are useful clinical tools for orthopaedic surgeons in the decision-making process for the treatment in Asian patients, with SORG models offering the best predictive performance. Rapid growth cancer and serum albumin level are independent, statistically significant factors contributing to survival following surgery of BM-E. Further refinement of survival prediction models will bring about informed and patient-specific treatment of BM-E. Cite this article: Bone Joint J 2024;106-B(2):203–211


The Bone & Joint Journal
Vol. 99-B, Issue 4 | Pages 516 - 521
1 Apr 2017
Willeumier JJ van der Hoeven NMA Bollen L Willems LNA Fiocco M van der Linden YM Dijkstra PDS

Aims. This study aims to assess first, whether mutations in the epidermal growth factor receptor (EGFR) and Kirsten rat sarcoma (kRAS) genes are associated with overall survival (OS) in patients who present with symptomatic bone metastases from non-small cell lung cancer (NSCLC) and secondly, whether mutation status should be incorporated into prognostic models that are used when deciding on the appropriate palliative treatment for symptomatic bone metastases. Patients and Methods. We studied 139 patients with NSCLC treated between 2007 and 2014 for symptomatic bone metastases and whose mutation status was known. The association between mutation status and overall survival was analysed and the results applied to a recently published prognostic model to determine whether including the mutation status would improve its discriminatory power. Results. The median OS was 3.9 months (95% confidence interval (CI) 2.1 to 5.7). Patients with EGFR (15%) or kRAS mutations (34%) had a median OS of 17.3 months (95% CI 12.7 to 22.0) and 1.8 months (95% CI 1.0 to 2.7), respectively. Compared with EGFR-positive patients, EGFR-negative patients had a 2.5 times higher risk of death (95% CI 1.5 to 4.2). Incorporating EGFR mutation status in the prognostic model improved its discriminatory power. Conclusion. Survival prediction models for patients with symptomatic bone metastases are used to determine the most appropriate (surgical) treatment for painful or fractured lesions. This study shows that NSCLC should not be regarded as a single entity in such models. Cite this article: Bone Joint J 2017;99-B:516–21


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.


The Bone & Joint Journal
Vol. 102-B, Issue 12 | Pages 1752 - 1759
1 Dec 2020
Tsuda Y Tsoi K Stevenson JD Laitinen M Ferguson PC Wunder JS Griffin AM van de Sande MAJ van Praag V Leithner A Fujiwara T Yasunaga H Matsui H Parry MC Jeys LM

Aims

Our aim was to develop and validate nomograms that would predict the cumulative incidence of sarcoma-specific death (CISSD) and disease progression (CIDP) in patients with localized high-grade primary central and dedifferentiated chondrosarcoma.

Methods

The study population consisted of 391 patients from two international sarcoma centres (development cohort) who had undergone definitive surgery for a localized high-grade (histological grade II or III) conventional primary central chondrosarcoma or dedifferentiated chondrosarcoma. Disease progression captured the first event of either metastasis or local recurrence. An independent cohort of 221 patients from three additional hospitals was used for external validation. Two nomograms were internally and externally validated for discrimination (c-index) and calibration plot.


The Bone & Joint Journal
Vol. 102-B, Issue 1 | Pages 72 - 81
1 Jan 2020
Downie S Lai FY Joss J Adamson D Jariwala AC

Aims

The early mortality in patients with hip fractures from bony metastases is unknown. The objectives of this study were to quantify 30- and 90-day mortality in patients with proximal femoral metastases, and to create a mortality prediction tool based on biomarkers associated with early death.

Methods

This was a retrospective cohort study of consecutive patients referred to the orthopaedic department at a UK trauma centre with a proximal femoral metastasis (PFM) over a seven-year period (2010 to 2016). The study group were compared to a matched control group of non-metastatic hip fractures. Minimum follow-up was one year.


The Bone & Joint Journal
Vol. 98-B, Issue 2 | Pages 271 - 277
1 Feb 2016
Sørensen MS Gerds TA Hindsø K Petersen MM

Aims

The purpose of this study was to develop a prognostic model for predicting survival of patients undergoing surgery owing to metastatic bone disease (MBD) in the appendicular skeleton.

Methods

We included a historical cohort of 130 consecutive patients (mean age 64 years, 30 to 85; 76 females/54 males) who underwent joint arthroplasty surgery (140 procedures) owing to MBD in the appendicular skeleton during the period between January 2003 and December 2008. Primary cancer, pre-operative haemoglobin, fracture versus impending fracture, Karnofsky score, visceral metastases, multiple bony metastases and American Society of Anaesthesiologist’s score were included into a series of logistic regression models. The outcome was the survival status at three, six and 12 months respectively. Results were internally validated based on 1000 cross-validations and reported as time-dependent area under the receiver-operating characteristic curves (AUC) for predictions of outcome.