Prognostic factors associated with failure of total elbow replacement: a protocol for analysis of National Joint Registry data in England

TL;DR

This study aims to identify factors that predict failure of elbow replacement surgery using data from England's National Joint Registry.

Contribution

The study introduces a protocol for analyzing prognostic factors of total elbow replacement failure using linked national registry data.

Findings

The study will examine the overall prognosis of total elbow replacement using Kaplan-Meier analysis.

Potential prognostic factors will be assessed using univariable and multivariable regression methods.

The research will explore missing data patterns and use complete case analysis as the primary method.

Abstract

Understanding the prognostic factors associated with the failure of total elbow replacement (TER) is crucial for informing patients about risks and enabling shared decision-making regarding TER as a definitive management option. This protocol outlines the planned analysis of National Joint Registry (NJR) data to investigate prognostic factors for TER failure.

The primary analysis will use the NJR elbow dataset, including all eligible patients who underwent TER surgery between April 2012 and December 2023. To incorporate ethnicity and comorbidities as potential prognostic factors, the NJR will be linked to the National Health Service (NHS) England Hospital Episode Statistics-Admitted Patient Care (HES-APC) data for a secondary analysis. The analysis will adhere to the REporting recommendations for tumour MARKer prognostic studies guidelines. The primary outcome under investigation is TER failure, defined as requiring revision surgery. Initially, the overall prognosis of TER will be examined using unadjusted net implant failure via the Kaplan-Meier method. The list of potential prognostic factors to be investigated in this study has been informed by a systematic review on this topic, input from patient and public involvement and engagement (PPIE) groups and a survey shared with healthcare professionals providing TER services. The relationship between each potential prognostic factor and failure will be assessed using univariable regression methods. Based on the findings from our systematic review, the univariable association will also be adjusted for age, sex and indication for TER surgery using multivariable regression methods. The extent of missing data will be reported, and the reasons for missing data will be explored. A very high degree of data completeness is expected, and a complete case analysis will be performed as the primary analysis. Multiple imputations will be considered as a sensitivity analysis.

The NJR research committee approved this analysis, and the NHS Health Research Authority tool guidance dictates that the secondary use of such data for research does not require approval from a research ethics committee. The results from this analysis will be published in a peer-reviewed journal and presented at scientific conferences.

NCT06760585.