Statistically based algorithm for differential diagnosis of arthropathies based on quantitative osteoscintigraphy - E. G. Prokhorova; E. A. Shikina; G. E. Zhilyaev; E. V. Zhilyaev (Научно-практическая ревматология, 2021)
Background. EULAR experts include osteoscintigraphy of joints in the list of promising methods for the diagnosis of joint diseases. However, the method remains little used in rheumatology in our country.Aim of the study – to develop an algorithm for differential diagnosis for the most common arthropathies based on quantitative osteoscintigraphy.Materials and methods. 3 hours after the injection of pyrophosphate labeled with Tc-99m, scintigraphy of skeletal bones was performed according to the “whole body” program. The joint/adjacent bone uptake ratio was calculated. The CHAID algorithm was used for classification tree constructing.Results. The study included 266 patients aged 46.6±14.3 years, 134 men (50.4%). Axial spondyloarthritis (including ankylosing spondylitis) was diagnosed in 40 patients, peripheral spondyloarthritis (including reactive arthritis) – in 87, rheumatoid arthritis– in 45, osteoarthritis – in 68, psoriatic arthritis – in 26 people. A total of 2279 joints were included in the analysis. A classification tree algorithm for differential diagnosis of arthropathies was constructed. Key indicators for identifying subgroups in the algorithm were the intensity of radiopharmaceutical uptake in the wrist, knee and hip joints. The significance level of differences between the resulting groups at all points of the algorithm branching, taking into account the Bonferroni adjustment, was p=0.001 or less. In the training sample, 51.5% of the observations were correctly classified. According to results of the cross-validation, the expected rate of correct classifications in the actual application of the algorithm is 38.0%.Conclusions. An algorithm for differential diagnosis of the most common inflammatory diseases of the joints has been developed. It allows the use of quantitative osteoscintigraphy data in the diagnosis of arthritis.