Development of a Model for Predicting the 4-year Risk of Symptomatic Knee Osteoarthritis in China

A Longitudinal Cohort Study

Limin Wang; Han Lu; Hongbo Chen; Shida Jin; Mengqi Wang; Shaomei Shang

Disclosures

Arthritis Res Ther. 2021;23(65) 

In This Article

Background

Knee osteoarthritis (KOA) is among the most common chronic diseases leading to disability worldwide, carrying a substantial and increasing health burden.[1,2] The prevalence of symptomatic KOA and radiographic KOA in patients over 60 years of age ranges from 10.0 to 16.0% and 35.0 to 50.0%,[3–7] respectively. Approximately 250 million people have KOA worldwide, with a twofold increased prevalence in men and a threefold increased prevalence in women in the USA over the past 20 years;[5] symptomatic KOA affects approximately 15.1 million individuals in the US population.[8] The estimated number of individuals over 60 years old suffering from symptomatic KOA reached 37.35 million in China.[9] The years lived with disability (YLDs) caused by osteoarthritis ranked tenth in China in 2016[10] and fourth in South Korea in 2015.[11] Osteoarthritis had the fifth greatest relative increase in total YLDs from data of six Nordic countries from 1990 to 2015.[12] KOA was the first leading among osteoarthritis, accounting for 87% YLDs of osteoarthritis.[13] The increasing prevalence of KOA has increased the socioeconomic burden for affected individuals and healthcare systems.[14]

To date, there are no effective therapeutic strategies for KOA. Prediction models for KOA aim to synthesize multiple factors to comprehensively predict the incident risk and may allow for early detection and prevention.[15] The Nottingham KOA model was an early model for the prediction of 12-year KOA risk in middle-aged adults, including easily obtainable factors such as age, sex, family history, body mass index (BMI), occupational risk, and history of knee injury;[16] however, it was developed using data from only two communities in the UK, rather than a random sample of the general population, limiting its validity in other populations.[17] Several studies have developed prediction models based on genomic data[18–21] or radiographic/clinical biomarkers[22] such as hip α-angle and spinal bone mineral density. However, use of these models is limited due to their high cost or complexity.[23]

Primary risk factors for incident KOA include advanced age, female gender, overweight/obesity, knee injury, and smoking.[24–27] Smoking decreases the risk of KOA, while the other factors increase the risk. Although physical activity,[28,29] occupational factors,[24] ethnicity, and genetics[25] have also been associated with the incidence and/or progression of KOA, previous studies have reported inconsistent results due to methodological differences. Other potential risk factors for the development of KOA include metabolic syndrome,[30–32] waist circumference,[33] and depressive symptoms,[24,34] although findings regarding these factors remain controversial. Previous studies have reported a dual association between osteoarthritis and certain comorbidities (e.g., hypertension, ischemic heart disease, diabetes),[24,25] suggesting that these comorbidities can influence the incidence and progression of KOA. Existing risk models of KOA have failed to include these potential risk factors, and there are currently no models for predicting KOA risk in the Chinese population. In this study, we aimed to develop a model for predicting the 4-year risk of KOA based on survey data obtained via a random, nationwide sample of Chinese individuals. This model would consider the potential risk factors.

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