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Bone & Joint Open
Vol. 2, Issue 4 | Pages 236 - 242
1 Apr 2021
Fitzgerald MJ Goodman HJ Kenan S Kenan S

Aims

The aim of this study was to assess orthopaedic oncologic patient morbidity resulting from COVID-19 related institutional delays and surgical shutdowns during the first wave of the pandemic in New York, USA.

Methods

A single-centre retrospective observational study was conducted of all orthopaedic oncologic patients undergoing surgical evaluation from March to June 2020. Patients were prioritized as level 0-IV, 0 being elective and IV being emergent. Only priority levels 0 to III were included. Delay duration was measured in days and resulting morbidities were categorized into seven groups: prolonged pain/disability; unplanned preoperative radiation and/or chemotherapy; local tumour progression; increased systemic disease; missed opportunity for surgery due to progression of disease/lost to follow up; delay in diagnosis; and no morbidity.


The Bone & Joint Journal
Vol. 103-B, Issue 11 | Pages 1725 - 1730
1 Nov 2021
Baumber R Gerrand C Cooper M Aston W

Aims

The incidence of bone metastases is between 20% to 75% depending on the type of cancer. As treatment improves, the number of patients who need surgical intervention is increasing. Identifying patients with a shorter life expectancy would allow surgical intervention with more durable reconstructions to be targeted to those most likely to benefit. While previous scoring systems have focused on surgical and oncological factors, there is a need to consider comorbidities and the physiological state of the patient, as these will also affect outcome. The primary aim of this study was to create a scoring system to estimate survival time in patients with bony metastases and to determine which factors may adversely affect this.

Methods

This was a retrospective study which included all patients who had presented for surgery with metastatic bone disease. The data collected included patient, surgical, and oncological variables. Univariable and multivariable analysis identified which factors were associated with a survival time of less than six months and less than one year. A model to predict survival based on these factors was developed using Cox regression.