Predictors of repeated and first-time low-energy fractures in patients with rheumatoid arthritis

Introduction. Low-energy fractures in patients with rheumatoid arthritis (RA) occur more often than in the general population, reduce the quality and life expectancy of patients. Establishment of predictors of fractures will allow to personalize treatment and preventive measures.

Aim. To study the frequency, structure, predictors of new and repeated low-energy fractures that occurred in patients with RA during long-term prospective follow-up.

Materials and methods. 123 women with RA, aged 63.7 ± 8.3 years, were included in an open, prospective, non-interventional study, the follow-up period was 9.4 ± 1.8 years. Initially and in dynamics, laboratory and X-ray examinations were performed (X-ray morphometry of the spine, X-ray densitometry of the lumbar spine (L1-4) and femoral neck (SB)).

Results. During the follow-up period, 101 low-energy fractures occurred in 63 (51%) patients: in 33 (52%) people – for the first time, in 25 (48%) – again. Two or more fractures occurred in 25 (39%) patients. There were 32 (32%) peripheral fractures, 69 (68%) vertebral fractures. A direct relationship was established between fractures and a longer duration of RA course (r = 0.231, p < 0.05), with X-ray stage of RA at baseline (r = 0.280, p < 0.05) and over time (r = 0.819, p < 0.05), intake of glucocorticoids (GC) initially (r = 0.202, p < 0.05) and over time (r = 0.308, p < 0.05), cumulative dose of GC initially (r = 0.239, p < 0.05) and over time (r = 0.268, p < 0.05), duration of GC use (r = 0.270, p < 0.05), history of low-energy fractures (r = 0.291, p < 0.05), and feedback with OP in SB (r = -0.190, p < 0.05).

Conclusions. А high frequency of repeated and first-time low-energy fractures was established in patients with RA, among which fractures of the vertebrae, distal forearm, humerus and lower leg bones predominated. Fracture predictors: GC intake, history of low-energy fractures, baseline radiological stage of RA. A mathematical model for assessing the risk of fractures with good predictive ability has been developed.

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