Evidence- and data-driven classification of low back pain via artificial intelligence: Protocol of the PREDICT-LBP study.

In patients presenting with low back pain (LBP), once specific causes are excluded (fracture, infection, inflammatory arthritis, cancer, cauda equina and radiculopathy) many clinicians pose a diagnosis of non-specific LBP. Accordingly, current management of non-specific LBP is generic. There is a need for a classification of non-specific LBP that is both data- and evidence-based assessing multi-dimensional pain-related factors in a large sample size. The "PRedictive Evidence Driven Intelligent Classification Tool for Low Back Pain" (PREDICT-LBP) project is a prospective cross-sectional study which will compare 300 women and men with non-specific LBP (aged 18-55 years) with 100 matched referents without a history of LBP. Participants will be recruited from the general public and local medical facilities. Data will be collected on spinal tissue (intervertebral disc composition and morphology, vertebral fat fraction and paraspinal muscle size and composition via magnetic resonance imaging [MRI]), central nervous system adaptation (pain thresholds, temporal summation of pain, brain resting state functional connectivity, structural connectivity and regional volumes via MRI), psychosocial factors (e.g. depression, anxiety) and other musculoskeletal pain symptoms. Dimensionality reduction, cluster validation and fuzzy c-means clustering methods, classification models, and relevant sensitivity analyses, will classify non-specific LBP patients into sub-groups. This project represents a first personalised diagnostic approach to non-specific LBP, with potential for widespread uptake in clinical practice. This project will provide evidence to support clinical trials assessing specific treatments approaches for potential subgroups of patients with non-specific LBP. The classification tool may lead to better patient outcomes and reduction in economic costs.

Secukinumab in axial spondyloarthritis: a narrative review of clinical evidence.

Axial spondyloarthritis (axSpA) is a chronic inflammatory rheumatic disease characterized by inflammation and new bone formation in the axial skeleton. AxSpA is considered a spectrum of disease that includes two subtypes identified by the Assessment in SpondyloArthritis International Society classification criteria, namely, radiographic (r-axSpA usually referred to as ankylosing spondylitis) and non-radiographic axSpA (nr-axSpA). Although the burden of disease appears similar between the two classified subtypes, the degree of inflammation, as assessed by magnetic resonance imaging and C-reactive protein, and the degree of new bone formation are significantly higher in r-axSpA than in nr-axSpA. Nevertheless, axSpA is considered one disease with different courses. International guidelines for the management of axSpA have outlined treatment goals focused on control of signs and symptoms, inflammation, prevention of progressive structural damage, preservation of physical function, normalization of social participation and improvement of quality of life. The pathogenesis of axSpA has not been completely elucidated to date. A strong link between human leukocyte antigen B27 and axSpA, however, has been identified, and the success of anti-tumour necrosis factor and anti-interleukin (IL)-17A therapy has highlighted some of the key pro-inflammatory cytokines involved. The anti-IL-17A monoclonal antibody secukinumab is approved for the treatment of ankylosing spondylitis and nr-axSpA in the European Union and United States. In this narrative review, we discuss data for secukinumab in axSpA from randomized controlled trials, including MEASURE trials in AS and PREVENT in nr-axSpA, and real-world evidence.

[Risk assessment in osteoporosis : Time-tested and new approaches]. / Risikoassessment bei Osteoporose : Bewährtes und Neues.

Fracture risk cannot be determined by bone density alone. It is important to identify and consider risk factors that individually increase the risk of fractures when they occur. Risk calculators have been developed worldwide to determine fracture risk. The risk factors currently listed in the Dachverbands Osteologie (DVO) S3 Guidelines for the "Diagnosis and Therapy of Postmenopausal Osteoporosis and Male Osteoporosis" are diverse and should be prioritized, since not every fracture risk factor present increases the risk of a vertebral or femoral neck fracture to the same extent. Due to the unknown interaction between risk factors, no more than two risk factors in addition to age, gender, and bone density measurement should be considered per patient. For risk assessment, it is important that the two thresholds defined by the German guideline are reached, above which diagnostic workup or specific therapy for fracture risk reduction should be recommended. These thresholds are currently defined as 20% for diagnostics and 30% for therapy, based on the absolute 10-year risk for vertebral and femoral neck fractures. The threshold for diagnostics is reached with the presence of a risk factor mentioned in the guideline. To reach the threshold for therapy, the bone density measurement result is required to reach the age-specific T­score. However, typical fragile fractures of the vertebral bodies or femur increase the fracture risk so substantially that therapy can be recommended even without a bone density result.