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Background: Approximately 12-20% of those with osteoarthritis (OA) in Australia who undergo total knee replacement (TKR) surgery do not report any clinical improvement. There is a need to develop prediction tools for use in general practice that allow early identification of patients likely to undergo TKR and those unlikely to benefit from the surgery. First-line treatment strategies can then be implemented and optimised to delay or prevent the need for TKR. The identification of potential non-responders to TKR may provide the opportunity for new treatment strategies to be developed and help ensure surgery is reserved for those most likely to benefit. This statistical analysis plan (SAP) details the statistical methodology used to develop such prediction tools., Objective: To describe in detail the statistical methods used to develop and validate prediction models for TKR surgery in Australian patients with OA for use in general practice., Methods: This SAP contains a brief justification for the need for prediction models for TKR surgery in general practice. A description of the data sources that will be linked and used to develop the models, and estimated sample sizes is provided. The planned methodologies for candidate predictor selection, model development, measuring model performance and internal model validation are described in detail. Intended table layouts for presentation of model results are provided., Conclusion: Consistent with best practice guidelines, the statistical methodologies outlined in this SAP have been pre-specified prior to data pre-processing and model development., (© 2020 The Authors.)

Objective: Patient satisfaction is considered an important outcome measure after total knee replacement, but the construct is complex. There is large variation both in how satisfaction is measured and estimates of the proportion of people who are satisfied after surgery. The aim of this systematic review was to i) evaluate the proportion of people reported to be satisfied after total knee replacement for osteoarthritis; and ii) assess the content validity of the utilised satisfaction measures., Methods: We searched four literature databases with search phrases 'Total Knee Arthroplasty' OR 'Total Knee Replacement' AND 'Patient satisfaction' for studies that measured satisfaction at least 6 month post-unilateral primary total knee replacement for knee osteoarthritis. Identified studies were assessed for risk of bias, and studies at high risk of bias were excluded (PROSPERO: CRD42017058936). Meta-analysis was not appropriate due to the heterogeneity in satisfaction instruments, thus satisfaction scores were described. The content validity of satisfaction questionnaires was assessed using the COnsensus-based Standards for the selection of health status Measurement Instruments criteria., Results: The present review found heterogeneity in the satisfaction questions used, as well as the satisfaction estimates from the various studies. Only two satisfaction instruments were relevant for a Total Knee Replacement population and both failed assessment for content validity due to lack of patient involvement during development and testing in accordance with the COnsensus-based Standards for the selection of health status Measurement Instruments criteria., Conclusion: Future research should focus on qualitative methods to elicit patients' perspectives of satisfaction to build theoretical understanding., Competing Interests: This work was supported by the Centre for Research Excellence in Total Joint Replacement (APP1116325), under a 10.13039/501100000925National Health & Medical Research Council, Australia, grant. In addition, personal declarations are as follows: COI Anne Smith reports grants from 10.13039/501100000925National Health & Medical Research Council, during the conduct of the study. COI Peter O'Sullivan reports grants from 10.13039/501100000925National Health & Medical Research Council, during the conduct of the study. COI Peter Choong reports grants from 10.13039/501100000925National Health & Medical Research Council, during the conduct of the study; personal fees from 10.13039/100008894Stryker, personal fees from 10.13039/100004331Johnson & Johnson, grants from Medacta, personal fees from Kluwer, outside the submitted work. Additionally, COI Peter Choong is supported by a 10.13039/501100000925National Health & Medical Research Council Practitioner Fellowship (APP1154203). COI Michelle Dowsey reports grants from 10.13039/501100000925National Health & Medical Research Council, during the conduct of the study; grants from Medacta, outside the submitted work. Additionally, COI Michelle Dowsey is supported by a 10.13039/501100000925National Health & Medical Research Council Career Development Fellowship (APP1122526)., (© 2020 The Authors.)