The development of an algorithm that provides accurate individualised estimates of revision risk could help patients make informed surgical treatment choices. This requires building a survival model based on fixed and modifiable risk factors that predict outcome at the individual level. Here we compare different survival models for predicting prosthesis survivorship after hip replacement for osteoarthritis using data from the National Joint Registry for England, Wales, Northern Ireland and the Isle of Man.

In this comparative study we implemented parametric and flexible parametric (FP) methods and random survival forests (RSF). The overall performance of the parametric models was compared using Akaike information criterion (AIC). The preferred parametric model and the RSF algorithm were further compared in terms of the Brier score, concordance index (C index) and calibration.

The dataset contains 327 238 hip replacements for osteoarthritis carried out in England and Wales between 2003 and 2015. The AIC value for the FP model was the lowest. The averages of survival probability estimates were in good agreement with the observed values for the FP model and the RSF algorithm. The integrated Brier score of the FP model and the RSF approach over 10 years were similar: 0.011 (95% confidence interval: 0.011–0.011). The C index of the FP model at 10 years was 59.4% (95% confidence interval: 59.4%–59.4%). This was 56.2% (56.1%–56.3%) for the RSF method.

The FP model outperformed other commonly used survival models across chosen validation criteria. However, it does not provide high discriminatory power at the individual level. Models with more comprehensive risk adjustment may provide additional insights for individual risk.

Background

Chronic pain after joint replacement is common, affecting approximately 10% of patients after total hip replacement (THR) and 20% of patients after total knee replacement (TKR). Heightened generalised sensitivity to nociceptive input could be a risk factor for the development of this pain. The primary aim of this study was to investigate whether preoperative widespread pain sensitivity was associated with chronic pain after joint replacement.

Background

To investigate whether the interaction between pre-operative widespread hyperalgesia and radiographic osteoarthritis (OA) was associated with pain severity before and after total hip replacement (THR) and total knee replacement (TKR).

Background

While many studies have investigated long-term outcomes after lower limb arthroplasty, rather less is known about the trajectory of short-term outcomes in the first post-operative year. It is difficult for a surgeon to know when, in terms of disease severity, it is best to operate, or to make an accurate prediction of the patient pattern of post-operative recovery. We explored the trajectory of change in pain and function following primary hip and knee arthroplasty and the influence of pre-operative self-reported symptoms on post-operative improvements.

Objective

There is limited information about the extent to which the association between pre-operative and chronic post-operative pain is mediated via pain-on-movement or pain-at-rest. We explored these associations in patients undergoing total hip (THR) and total knee (TKR) replacement.

Background

This article reviews four commonly used approaches to assess patient responsiveness to a treatment or therapy [Return To Normal (RTN), Minimal Important Difference (MID), Minimal Clinically Important Difference (MCID), OMERACT-OARSI (OO)], and demonstrates how each of the methods can be formulated in a multi-level modelling (MLM) framework.