ArticleArthritis research & therapy2017
Risk prediction model for knee pain in the Nottingham community: a Bayesian modelling approach.
Article in Arthritis research & therapy, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.
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Who cites it
13 citing papers in PubMed, 1 synthesis or guideline pooled it, 28 citations in OpenAlex.
- Clinical prediction models for knee pain in patients with knee osteoarthritis: a systematic review.Skeletal radiology · 2024Pooled it
- Predictive Models for Knee Pain in Middle-Aged and Elderly Individuals Based on Machine Learning Methods.Computational and mathematical methods in medicine · 2022Trial
- Beyond the algorithms: Challenges in predicting knee osteoarthritis pain from a machine learning point of view.Osteoarthritis imaging · 2026Article
- Next-Level Prediction of Structural Progression in Knee Osteoarthritis: A Perspective.International journal of molecular sciences · 2025Review
- Obesity and the risk of multiple or severe frequent knee pain episodes: a 4-year follow-up of the ELSA-Brasil MSK cohort.International journal of obesity (2005) · 2024Article
- Development and external validation of multivariable risk models to predict incident and resolved neuropathic pain: a DOLORisk Dundee study.Journal of neurology · 2023Article
- Prediction Models for Knee Osteoarthritis: Review of Current Models and Future Directions.The archives of bone and joint surgery · 2023Review
- Externally validated models for first diagnosis and risk of progression of knee osteoarthritis.PloS one · 2022Observational
- The Application of Artificial Intelligence in Football Risk Prediction.Computational intelligence and neuroscience · 2022Article
- Healthcare Data-Based Prediction Algorithm for Potential Knee Joint Injury of Football Players.Journal of healthcare engineering · 2021Article
- Investigating musculoskeletal health and wellbeing; a cohort study protocol.BMC musculoskeletal disorders · 2020Article
- Early knee osteoarthritis prevalence is highest among middle-aged adult females with obesity based on new set of diagnostic criteria from a large sample cohort study in the Japanese general population.Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA · 2020Article
- Low back pain precedes the development of new knee pain in the elderly population; a novel predictive score from a longitudinal cohort study.Arthritis research & therapy · 2019Article
Corrections and comments
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Authors and funding
6 authors at 4 institutions in 1 country.
Funding
Abstract
backgroundTwenty-five percent of the British population over the age of 50 years experiences knee pain. Knee pain can limit physical ability and cause distress and bears significant socioeconomic costs. The objectives of this study were to develop and validate the first risk prediction model for incident knee pain in the Nottingham community and validate this internally within the Nottingham cohort and externally within the Osteoarthritis Initiative (OAI) cohort.
methodsA total of 1822 participants from the Nottingham community who were at risk for knee pain were followed for 12 years. Of this cohort, two-thirds (n = 1203) were used to develop the risk prediction model, and one-third (n = 619) were used to validate the model. Incident knee pain was defined as pain on most days for at least 1 month in the past 12 months. Predictors were age, sex, body mass index, pain elsewhere, prior knee injury and knee alignment. A Bayesian logistic regression model was used to determine the probability of an OR >1. The Hosmer-Lemeshow χ
resultsA risk prediction model for knee pain incidence was developed using a Bayesian approach. The model had good calibration, with an HLS of 7.17 (p = 0.52) and moderate discriminative ability (ROC 0.70) in the community. Individual scenarios are given using the model. However, the model had poor calibration (HLS 5866.28, p < 0.01) and poor discriminative ability (ROC 0.54) in the OAI cohort.
conclusionsTo our knowledge, this is the first risk prediction model for knee pain, regardless of underlying structural changes of knee osteoarthritis, in the community using a Bayesian modelling approach. The model appears to work well in a community-based population but not in individuals with a higher risk for knee osteoarthritis, and it may provide a convenient tool for use in primary care to predict the risk of knee pain in the general population.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.