How to develop, validate, and update clinical prediction models using multinomial logistic regression.

Objectives: Multicategory prediction models (MPMs) can be used in health care when the primary outcome of interest has more than two categories. The application of MPMs is scarce, possibly due to added methodological complexities compared to binary outcome models. We provide a guide of how to develop, validate, and update clinical prediction models based on multinomial logistic regression.

Prognostic factors associated with failure of total elbow arthroplasty.

Aims: The aims of this study were to identify and evaluate the current literature examining the prognostic factors which are associated with failure of total elbow arthroplasty (TEA).

Methods: Electronic literature searches were conducted using MEDLINE, Embase, PubMed, and Cochrane. All studies reporting prognostic estimates for factors associated with the revision of a primary TEA were included.

Developing and externally validating multinomial prediction models for methotrexate treatment outcomes in patients with rheumatoid arthritis: results from an international collaboration.

Objectives: In rheumatology, there is a clinical need to identify patients at high risk (>50%) of not responding to the first-line therapy methotrexate (MTX) due to lack of disease control or discontinuation due to adverse events (AEs). Despite this need, previous prediction models in this context are at high risk of bias and ignore AEs. Our objectives were to (i) develop a multinomial model for outcomes of low disease activity and discontinuing due to AEs 6 months after starting MTX, (ii) update prognosis 3-month following treatment initiation, and (iii) externally validate these models.

Prognostic factors associated with failure of total elbow replacement: a protocol for a systematic review.

Introduction: Total elbow replacement (TER) has higher failure rates requiring revision surgery compared with the replacement of other joints. Understanding the factors associated with failure is essential for informed decision-making between patients and clinicians, and for reducing the failure rate. This review aims to identify, describe and appraise the literature examining prognostic factors for failure of TER.

Clinical prediction models for methotrexate treatment outcomes in patients with rheumatoid arthritis: A systematic review and meta-analysis.

Background: In the management of rheumatoid arthritis (RA), there is a clinical need to identify which patients are at high-risk of not responding to methotrexate (MTX), or experiencing adverse events (AEs), to enable earlier alternative treatments. Many clinical prediction models (CPMs) have previously been developed, but a summary of such models and their methodological quality is lacking. This systematic review aimed to (i) identify and summarize previously published CPMs of MTX outcomes in biologic-naïve RA patients, and (ii) critically appraise their methodological properties.