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


Arthritis Res Ther. 2021;23(65) 

In This Article


We developed and internally validated a model for predicting the 4-year risk of symptomatic KOA among the Chinese population, based on data from the CHARLS cohort. An easy-to-use clinical score model was developed to identify individuals' risk of developing KOA. The model included ten convenient and accessible variables, including age, sex, and waist circumference, which are most commonly included in previous KOA prediction models. Besides we also included the other controversial or new predictors of KOA, which were first time tested in risk model of KOA. To our knowledge, this is the first model for predicting KOA risk in the Chinese population, and our results suggest that this model can be used to aid in the prevention of KOA.

Older age was identified as a risk factor for KOA in our study; the most significant increase in risk was observed in the 60–69 years group. The cumulative incidence of symptomatic KOA gradually increased from 45 years of age, increasing rapidly after 55 years of age, peaking at approximately 65 years of age.[47] After 70 years of age, increases in the cumulative incidence of KOA were no longer significant.[47] Our findings, along with previous, highlight the need to prevent the incident of KOA in individuals between 45 and 70 years of age.

Obesity creates an abnormal loading environment for weight-bearing joints and may contribute to the pathogenesis of KOA.[48] Alternatively, the increased risk of KOA may be caused by the positive energy balance and metaflammation associated with obesity.[49] Although BMI has been illustrated as an important predictor of KOA,[50] Wallace et al. (2019)[48] reported that increased abdomen size is associated with a greater risk of radiographic KOA than high BMI. Further studies are required to determine whether BMI, waist circumference, or metabolic syndrome comprehensively influences KOA risk due to mechaflammation and metaflammation. In this study, we analyzed the effects of BMI, waist circumference, and metabolic syndrome on KOA incident in the Chinese population. None of these three factors were a significant predictor of KOA incident; BMI had relatively low significance compared with waist circumference.

We analyzed the likelihood that the damage by BMI on joint tissues and pain symptoms would not reach a significant effect in the short term. Only the 12-year Nottingham KOA model investigated BMI related to symptomatic KOA,[16] and the 9-year Rotterdam model[21] and 4-year Chingford model[22] were predictive for radiographic KOA. BMI was also not included in final 4-year Chingford model. Zheng & Chen[50] synthesized that BMI was a significant factor for incident KOA, but the diagnosis of KOA was radiographic KOA or severe KOA or replacement of KOA in 13 of 14 included studies. Among the eight studies with follow-up duration less than 10 years, none focused on symptomatic KOA. Another possible reason was that abnormal waist circumference was much prevalent than abnormal BMI in the Chinese population because body feature is prone to be small in the Asian race compared with the European or American population,[51] thus waist circumference was much significant with incident KOA than BMI in this study. The results imply that the sensitivity of index of obesity might vary with race when evaluating the risk of KOA. Additional studies focusing on risk model of KOA are required to verify the significance of BMI with the incident of symptomatic KOA in Chinese population and other ethnic populations.

Another conventional risk factor for KOA was physical activity. In the present study, no significant association was observed between VPA/light physical activity (LPA) and the incident of KOA; however, MPA positively predicted the incident of KOA. The reported associations between physical activity and the incident of KOA were inconsistent, resulting from a variation in assessment methods, activity categories, or populations. Felson et al.[28] reported walking and other recreational activities did not increase the risk of OA in older adults. Results from the Chingford cohort demonstrated that physical activities related to work and sports increase the risk of osteophytes, while walking decreases the risk of osteophytes in middle-aged women;[52] however, all effects were not statistically significant. Findings from the Framingham Heart Study[53] indicate that performing over 2 h/day would increase risk symptomatic KOA (OR, 5.3; 95% CI, 1.2–24) and the association was also significant for radiographic KOA (OR, 1.3 per hour; 95% CI, 1.1–1.6), while the effects of MPA and LPA were insignificant. Given the discrepancy between studies, additional studies should aim to verify the influence of different types of physical activity on the risk of KOA. Such studies should seek to determine the most appropriate type, duration, frequency, and intensity of physical activity for preventing KOA in different populations.

In our model, health-related variables are addressed and our findings provide evidence that these variables contribute essential values to the prediction of symptomatic KOA. Depressive symptoms, comorbidities, and history of hip fracture are psychologically and physiologically objective factors related to KOA. Self-rated health and difficulty with ADL/IADLs were mainly subjective, which was reflected in the patient's knowledge and ability to cope with disease.

Patients with KOA are prone to be comorbid with depression and other chronic comorbidities, and chronic diseases often exhibit interactions with comorbidities in complex ways.[54] Hence, previous studies have assumed that there may be a potential effect of depression and chronic comorbidities on incident of KOA. Seavey et al.[34] indicated that depressive symptoms represented a risk factor for arthritis incident (OR, 1.72; 95% CI, 1.27–2.35). Jinks et al.[55] also reported that depression was a significant predictor of knee pain (OR, 1.4; 95% CI, 1.1–1.8), where pain is the dominant physical symptom among patients with symptomatic KOA. Our study is the first model involving depression as predictor in a prediction model of symptomatic KOA. Patients with mild or moderate-to-severe depression were two or three times more likely to develop KOA than those without depression. Although a bidirectional causal association has rarely been illustrated either between arthritis and depression or between any other chronic disease and depression, targeted strategies for addressing depressive symptoms may therefore aid in reducing the incident of KOA. We also assessed relationships for 12 main types of comorbidities with incident of KOA. KOA and comorbidities may accelerate the progression of one another.[24] Results showed that patients with comorbidities had a significantly increased risk of developing KOA within 4 years. This addressed the effect of comorbidities in developing KOA in the Chinese population; this might have some value for developing prediction model of KOA in other ethnic groups.

Related studies[56,57] have demonstrated that rheumatoid arthritis increases the risk of hip fracture due to bone loss induced by chronic inflammation, use of glucocorticoids, and physical inactivity. However, rare studies indicated the association between hip fracture and KOA incident. Given that the knee and hip joints are the two most important weight-bearing joints, we sought to determine whether a history of hip fracture increases the risk of developing KOA. Our findings indicated that a history of hip fracture was associated with a 53% increase in the risk of KOA. Identifying the potential mechanisms underlying this association should be helpful for development of risk model in further studies.

Patient-reported outcome (PRO) has been emphasized in multiple studies because PROs may capture important disease-related information prior to the onset of clinical signs or pathophysiological changes.[58] Silverwood et al.[24] noted that poor self-rated health status was a potential risk factor for KOA in an earlier study, although the association was insignificant. Our model showed that the likelihood of developing KOA increased as health status worsened and impairments in ADLs/IADLs. Self-rated health status and assessments of difficulty with ADLs/IADLs could be significant predictors for incident of symptomatic KOA. Self-ratings of health status comprehensively reflect one's physical and psychological function, as well as one's knowledge and ability to cope with diseases and self-efficiency. Most of the existing potential risk factors were pooled from epidemiological analyses or clinicians' experience. Our findings highlight the need to consider the patient's perspective, as this may aid in furthering our understanding of KOA while reducing the incidence of the disease. Symptomatic KOA progressively decreases self-care ability, causing knee pain or stiffness. Our results implied that impairments in ADLs/IADLs prior to KOA onset may represent a predictive signal for KOA. Hence, preventive interventions may be useful in reducing the incident of KOA in those who have difficulty with ADL/IADL. Improving ADLs/IADLs might become a new interventional target to prevent KOA.

Preventing KOA or other chronic disease in rural area is the biggest challenge in China because of large population.[36] Our model included resident area as one predictor for KOA aiming to improve the prevention of KOA in rural population. Factors related to the high prevalence in rural areas may be multiple, including limited access to knowledge regarding the prevention of KOA and other chronic diseases, a lack of economic resources for timely treatment of chronic diseases, poor ability to manage one's health, and earlier impairments in physical function due to strenuous farm work. We hope that our results could promote policies and resources directed toward preventing KOA in Chinese rural areas in future.

We developed an easy-to-use clinical score model to identify risk of symptomatic KOA within 4 years and to identify individuals at high risk. This model involved ten commonly available variables. This simple model involved ten commonly available variables, the assessment of variables, and the calculation of risk score, which are both easily understood and handled in practice. Clinicians or the patients themselves could use this tool to assess the risk of KOA in 4-year term. While the score model showed a good performance in assessing risk of KOA (AUC = 0.713; 95% CI 0.695–0.731), the ability to identify individuals at high risk was moderate using a − 20.5 cut-off. Hence, this model should be improved and adjusted when applied in other populations. Adding other clinical biomarkers would provide further insight.

Limitations of the study include the incomplete data, though which was handed using the imputation method and a bootstrap strategy, may have biased our findings, especially the physical activity with a high percentage missing. Second, while new variables included in the study were significantly associated with the incident of KOA, further studies are required to elucidate the mechanisms underlying these associations. Lastly, our model was internally validated; therefore, external validation in other Chinese populations and different ethnic groups remains necessary.