Machine-learning-based patient-specific prediction models for knee osteoarthritis

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Abstract

Osteoarthritis (OA) is an extremely common musculoskeletal disease. However, current guidelines are not well suited for diagnosing patients in the early stages of disease and do not discriminate patients for whom the disease might progress rapidly. The most important hurdle in OA management is identifying and classifying patients who will benefit most from treatment. Further efforts are needed in patient subgrouping and developing prediction models. Conventional statistical modelling approaches exist; however, these models are limited in the amount of information they can adequately process. Comprehensive patient-specific prediction models need to be developed. Approaches such as data mining and machine learning should aid in the development of such models. Although a challenging task, technology is now available that should enable subgrouping of patients with OA and lead to improved clinical decision-making and precision medicine.

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Osteoarthritis.

Johanne Martel-Pelletier, Andrew J Barr, Flavia Cicuttini … (2017)

Osteoarthritis (OA) is the most common joint disorder, is associated with an increasing socioeconomic impact owing to the ageing population and mainly affects the diarthrodial joints. Primary OA results from a combination of risk factors, with increasing age and obesity being the most prominent. The concept of the pathophysiology is still evolving, from being viewed as cartilage-limited to a multifactorial disease that affects the whole joint. An intricate relationship between local and systemic factors modulates its clinical and structural presentations, leading to a common final pathway of joint destruction. Pharmacological treatments are mostly related to relief of symptoms and there is no disease-modifying OA drug (that is, treatment that will reduce symptoms in addition to slowing or stopping the disease progression) yet approved by the regulatory agencies. Identifying phenotypes of patients will enable the detection of the disease in its early stages as well as distinguish individuals who are at higher risk of progression, which in turn could be used to guide clinical decision making and allow more effective and specific therapeutic interventions to be designed. This Primer is an update on the progress made in the field of OA epidemiology, quality of life, pathophysiological mechanisms, diagnosis, screening, prevention and disease management.

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Incidence and risk factors for clinically diagnosed knee, hip and hand osteoarthritis: influences of age, gender and osteoarthritis affecting other joints.

Daniel Prieto-Alhambra, Andrew Judge, M. Javaid … (2014)

Data on the incidence of symptomatic osteoarthritis (OA) are scarce. We estimated incidence of clinical hip, knee and hand OA, and studied the effect of prevalent OA on joint-specific incident OA. SIDIAP contains primary care records for>5 million people from Catalonia (Spain). Participants aged ≥40 years with an incident diagnosis of knee, hip or hand OA between 2006 and 2010 were identified using International Classification of Diseases (ICD)-10 codes. Incidence rates and female-to-male rate ratios (RRs) for each joint site were calculated. Age, gender and body mass index-adjusted HR for future joint-specific OA according to prevalent OA at other sites were estimated using Cox regression. 3 266 826 participants were studied for a median of 4.45 years. Knee and hip OA rates increased continuously with age, and female-to-male RRs were highest at age 70-75 years. In contrast, female hand OA risk peaked at age 60-64 years, and corresponding female-to-male RR was highest at age 50-55 years. Adjusted HR for prevalent knee OA on risk of hip OA was 1.35 (99% CI 1.28 to 1.43); prevalent hip OA on incident knee OA: HR 1.15 (1.08 to 1.23). Prevalent hand OA predicted incident knee and hip OA: HR 1.20 (1.14 to 1.26) and 1.23 (1.13 to 1.34), respectively. The effect of age is greatest in the elderly for knee and hip OA, but around the menopause for hand OA. OA clusters within individuals, with higher risk of incident knee and hip disease from prevalent lower limb and hand OA. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.