Therapeutic Advances in Musculoskeletal Disease最新文献

{"title":"Similarities and differences: disentangling the intersection between axial psoriatic arthritis and axial spondyloarthritis.","authors":"Murat Torgutalp, Henriette Käding, Fabian Proft","doi":"10.1177/1759720X251357532","DOIUrl":"10.1177/1759720X251357532","url":null,"abstract":"<p><p>Spondyloarthritis is a group of chronic inflammatory diseases that includes axial spondyloarthritis (axSpA) and psoriatic arthritis (PsA). AxSpA primarily affects the axial skeleton, manifesting with hallmark features such as inflammatory back pain and a strong association with human leukocyte antigen-B27. On the other hand, axial involvement in PsA (axial PsA) poses unique challenges in the diagnosis, classification, and management. These challenges stem from a limited understanding of this condition and an absence of a specific definition for its diagnosis. Although shared genetic and environmental contributors are observed, the presence of differences suggests the possibility that axial PsA may, in fact, represent a distinct clinical entity rather than axSpA. The prevailing classification criteria, such as ClASsification criteria for Psoriatic ARthritis for PsA and the Assessment of SpondyloArthritis International Society criteria for axSpA, are insufficient in capturing the full scope of axial PsA. Moreover, treatment paradigms for axial PsA are primarily extrapolated from axSpA due to the lack of targeted trials in this specific population. Biologic disease-modifying anti-rheumatic drugs, encompassing tumor necrosis factor inhibitors, interleukin (IL)-17 inhibitors, and Janus kinase inhibitors, have demonstrated efficacy in axSpA and PsA. However, IL-23 inhibitors have not shown efficacy in axSpA, and currently, no results from randomized controlled trials in axial PsA are available. While axial PsA exhibits features that overlap with axSpA, emerging evidence underscores its distinct pathophysiology and clinical characteristics, highlighting the need for standardized definitions and tailored therapeutic approaches to optimize outcomes. Ongoing studies evaluating therapeutic efficacy and molecular characterization hold promises to enhance understanding and management of axial PsA, thus paving the way for personalized treatment strategies. This review aims to provide an overview of the similarities and differences between axial PsA and axSpA and seeks to disentangle the intersections between these two diseases.</p>","PeriodicalId":23056,"journal":{"name":"Therapeutic Advances in Musculoskeletal Disease","volume":"17 ","pages":"1759720X251357532"},"PeriodicalIF":4.1,"publicationDate":"2025-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12304513/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144745149","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Deep learning meets chest X-rays: a promising approach for predicting future compression fracture risk.","authors":"Kai-Chieh Chen, Shan-Yueh Chang, Yuan-Ping Chao, Dung-Jang Tsai, Wei-Chou Chang, Yu-Shiou Weng, Chin Lin, Wen-Hui Fang","doi":"10.1177/1759720X251357157","DOIUrl":"10.1177/1759720X251357157","url":null,"abstract":"<p><strong>Background: </strong>Osteoporotic fractures are a significant global health concern, leading to disability and reduced quality of life. Existing diagnostic tools, such as dual-energy X-ray absorptiometry (DXA) and the Fracture Risk Assessment Tool, have limitations, such as dependence on structured datasets and difficulty identifying all high-risk individuals.</p><p><strong>Objectives: </strong>This study aimed to develop and validate an AI-enabled chest X-ray (AI-CXR) model for predicting osteoporotic fracture risk, offering a noninvasive, accessible alternative.</p><p><strong>Design: </strong>This is a retrospective study.</p><p><strong>Methods: </strong>This study analyzed 166,571 CXR from 78,548 patients in Taiwan, with internal validation on 31,977 X-rays and external validation on 36,677 X-rays. The datasets were divided into groups with and without <i>T</i>-scores. Radiological features such as costophrenic angle blunting and degenerative joint disease were extracted and incorporated into the predictive framework. The model's performance was assessed using concordance indices, calibration curves, and stratified risk analyses, and compared to DXA-based <i>T</i>-scores.</p><p><strong>Results: </strong>The AI-CXR model demonstrated superior predictive accuracy compared to DXA, particularly for patients without <i>T</i>-scores (internal validation: concordance index 0.896 vs 0.829; external validation: 0.778 vs 0.818). Among high-risk groups identified by AI-CXR, the 5-year fracture incidence was significantly higher than in low-risk groups (internal: 2.6% vs 0.3%, hazard ratio (HR): 2.01; external: 3.5% vs 0.5%, HR: 2.34). Key radiological features were more prevalent in high-risk groups, including costophrenic angle blunting and degenerative joint disease. Stratified analysis revealed consistent performance across various demographic subgroups, such as gender and age categories.</p><p><strong>Conclusion: </strong>The AI-CXR model provides a cost-effective, noninvasive tool for osteoporotic fracture risk assessment, enabling improved early detection and personalized intervention across diverse clinical settings.</p>","PeriodicalId":23056,"journal":{"name":"Therapeutic Advances in Musculoskeletal Disease","volume":"17 ","pages":"1759720X251357157"},"PeriodicalIF":4.1,"publicationDate":"2025-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12304508/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144745134","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Impact of conflicting information on the use of antirheumatic drugs in pregnancy and breastfeeding: perspectives of healthcare providers from the global PRAISE survey.","authors":"Karen Schreiber, Christine Graversgaard, Ioannis Parodis, Nancy Agmon-Levin, Silvia Aguilera, Aleksandra Antovic, George K Bertsias, Ilaria Bini, Anca Bobirca, Susana Capela, Ricard Cervera, Nathalie Costedoat-Chalumeau, Radboud Dolhain, Oseme Etomi, Julia Flint, Joao Eurico Fonseca, Ruth Fritsch-Stork, Frauke Förger, Ian Giles, Bethan Goulden, Carina Götestam Skorpen, Iva Gunnarsson, Latika Gupta, Hege Svean Koksvik, Louise Linde, Jacob Lykke, Yvette Meissner, Anna Molto, Louise Moore, Marta Mosca, Catherine Nelson-Piercy, Luis Fernando Perez-Garcia, Luigi Raio, Ane Lilleoere Rom, Amihai Rottenstreich, Muna Saleh, Savino Sciascia, Anja Strangfeld, Elisabet Svenungsson, Maria G Tektonidou, Angela Tincani, Anne Troldborg, Jelena Vojinovic, Anne Voss, Marianne Wallenius, Nuria Zuniga-Serrano, Laura Andreoli","doi":"10.1177/1759720X251350087","DOIUrl":"10.1177/1759720X251350087","url":null,"abstract":"<p><strong>Background: </strong>Treating rheumatic musculoskeletal diseases (RMDs) during pregnancy and breastfeeding presents significant complexities, mainly due to inconsistencies between the clinical guidance documents and the reference safety information, including the summary of product characteristics (SmPC) and the patient information leaflets (PIL).</p><p><strong>Objectives: </strong>To assess healthcare professionals' (HCPs) prescribing behaviors, comfort levels, and challenges when advising patients, focusing on discrepancies between clinical guidance documents and SmPC/PIL.</p><p><strong>Design: </strong>Online survey entitled PRAISE (Perception of healthcare providers Regarding Antirheumatics in pregnancy and breastfeeding: advice, Information and patient perSpEctives) and disseminated through HCPs groups and social media.</p><p><strong>Methods: </strong>A cross-sectional survey was conducted among 414 HCPs globally. Respondents were divided into prescribers (<i>n</i> = 336) and non-prescribers (<i>n</i> = 78) based on their self-reported role in prescribing antirheumatic medications to pregnant or breastfeeding patients with RMDs. The survey covered demographics, clinical experience, confidence in prescribing, use of clinical guidelines, and experiences managing conflicting information between guidelines and SmPC/PIL.</p><p><strong>Results: </strong>Prescribers were more likely than non-prescribers to feel comfortable discussing medication safety during pregnancy. Most prescribers found clinical guidance documents useful, with 48% rating them as \"very useful\" and 38% as \"extremely useful.\" In case of conflicting information between clinical guidance documents and SmPC/PIL, 58% of HCPs reported that it caused confusion and tension in patient-doctor relationships, and almost 20% of them are \"likely\" or \"very likely\" to discontinue ongoing treatment. Clear communication and shared decision-making were the most common strategies used to address patient concerns.</p><p><strong>Conclusion: </strong>HCPs often face significant challenges when advising patients with RMDs on the use of medications during pregnancy and breastfeeding. Conflicting information between clinical guidance documents and SmPC/PIL can disrupt patient-doctor relationship and lead to treatment discontinuation, with potential consequences on maternal disease control. Improved alignment between clinical guidance documents and the SmPC/PIL could enhance patient care and prevent confusion among HCPs and patients.</p>","PeriodicalId":23056,"journal":{"name":"Therapeutic Advances in Musculoskeletal Disease","volume":"17 ","pages":"1759720X251350087"},"PeriodicalIF":3.4,"publicationDate":"2025-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12267951/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144660304","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Menopause in systemic sclerosis: the impact on clinical presentation in a multicenter cross-sectional analysis from the National Registry of the Italian Society for Rheumatology (SPRING-SIR).","authors":"Martina Orlandi, Dilia Giuggioli, Clodoveo Ferri, Rossella De Angelis, Valeria Riccieri, Fabio Cacciapaglia, Silvia Laura Bosello, Veronica Codullo, Gianluigi Bajocchi, Lorenzo Dagna, Corrado Campochiaro, Giacomo De Luca, Giovanni Zanframundo, Rosario Foti, Giovanna Cuomo, Alarico Ariani, Edoardo Rosato, Francesco Girelli, Elisabetta Zanatta, Ilaria Cavazzana, Francesca Ingegnoli, Maria De Santis, Giuseppe Murdaca, Giuseppina Abignano, Giorgio Petitti, Alessandra Della Rossa, Maurizio Caminiti, Anna Maria Iuliano, Giovanni Ciano, Lorenzo Beretta, Gianluca Bagnato, Ennio Lubrano, Ilenia De Andres, Alessandro Giollo, Marta Saracco, Cecilia Agnes, Edoardo Cipolletta, Federica Lumetti, Amelia Spinella, Luca Magnani, Elisa Visalli, Carlo Iandoli, Antonietta Gigante, Greta Pellegrino, Erika Pigatto, Maria Grazia Lazzaroni, Franco Franceschini, Elena Generali, Gianna Mennillo, Simone Barsotti, Giuseppa Pagano Mariano, Federica Furini, Licia Vultaggio, Simone Parisi, Clara Lisa Peroni, Gerolamo Bianchi, Enrico Fusaro, Gian Domenico Sebastiani, Marcello Govoni, Salvatore D'Angelo, Franco Cozzi, Andrea Doria, Carlo Salvarani, Florenzo Iannone, Serena Guiducci, Silvia Bellando-Randone, Marco Matucci-Cerinic, Cosimo Bruni","doi":"10.1177/1759720X251354898","DOIUrl":"10.1177/1759720X251354898","url":null,"abstract":"<p><strong>Background: </strong>Hormonal changes in menopause might interact with the presentation of underlying autoimmune diseases, such as systemic sclerosis (SSc).</p><p><strong>Objectives: </strong>Our study aimed to evaluate the association of (1) current menopausal status, (2) early menopause, and (3) disease onset during fertile or post-menopausal age on SSc clinical phenotype in a large SSc cohort from the Italian Systemic sclerosis Progression INvestiGation (SPRING-SIR) registry.</p><p><strong>Design: </strong>Female SSc patients from the SPRING-SIR registry, fulfilling the American College of Rheumatology (ACR)/European Alliance of Associations for Rheumatology (EULAR) 2013 classification criteria, with data on SSc disease onset, menopausal status, and menopausal age, were eligible. SSc onset was categorized as pre-menopausal if SSc onset happened >1 year before menopause or as post-menopausal onset if it occurred >1 year after menopause. An early menopause was defined by a menopausal age <45 years.</p><p><strong>Methods: </strong>Descriptive statistics and regression models were built to test the association between current menopausal status, pre-menopausal disease onset, and early menopause with SSc-related features.</p><p><strong>Results: </strong>At baseline, 1157/1538 (75%) patients were in menopause, 632 (50.4%) had a pre-menopausal SSc onset, and 130 (14.4%) reported an early menopause. Post-menopausal patients had more frequent limited cutaneous SSc, anti-centromere antibody positivity, interstitial lung disease, and gastrointestinal manifestations. Pre-menopausal onset cases showed more frequent diffuse cutaneous involvement and peripheral vasculopathy. Patients with early menopause had more frequent peripheral vasculopathy and interstitial lung disease, being early menopause an independent risk factor for digital ulcers and lower diffusing capacity of the lung for carbon monoxide.</p><p><strong>Conclusion: </strong>Current post-menopausal status and early menopause may impact SSc presentation, being associated with vascular and gastrointestinal manifestations. Menopausal status and age should therefore be thoroughly addressed, aiming at better disease management.</p>","PeriodicalId":23056,"journal":{"name":"Therapeutic Advances in Musculoskeletal Disease","volume":"17 ","pages":"1759720X251354898"},"PeriodicalIF":3.4,"publicationDate":"2025-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12260299/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144643635","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Distinctive clinical patterns and management trends in late-onset psoriatic arthritis: data from Argentina's RECCAPSO registry.","authors":"Gustavo A Medina, Maximiliano Fenucci, Sebastián Magri, Marcelo Abdala, Tamara Arias, Brian Abdala, Leila Abbas, Vinod Chandran, Rodrigo García-Salinas","doi":"10.1177/1759720X251356206","DOIUrl":"10.1177/1759720X251356206","url":null,"abstract":"<p><strong>Background: </strong>Late-onset psoriatic arthritis (LO-PsA) has been underexplored despite its growing prevalence in aging populations. Understanding its distinct clinical presentation and treatment patterns is essential to optimize care in this subgroup.</p><p><strong>Objectives: </strong>To describe the demographic, clinical, and therapeutic features of patients with LO-PsA compared to early onset PsA (EO-PsA) using data from the Argentine RECCAPSO registry.</p><p><strong>Design: </strong>Ambispective, multicenter analysis with a cross-sectional evaluation.</p><p><strong>Methods: </strong>Patients with PsA were categorized into EO-PsA (age of onset ⩽60 years) and LO-PsA (>60 years). Demographics, clinical characteristics, disease activity, and treatment variables were compared between groups using appropriate statistical tests. A multivariate logistic regression model was constructed to identify factors independently associated with LO-PsA.</p><p><strong>Results: </strong>A total of 271 PsA patients were included (EO-PsA: <i>n</i> = 184; LO-PsA: <i>n</i> = 87). LO-PsA patients had higher frequencies of hypertension (50% vs 21.4%, <i>p</i> < 0.001), diabetes (22.1% vs 7.9%, <i>p</i> = 0.007), and oligoarticular presentation (57.4% vs 40.5%, <i>p</i> = 0.03), and were less likely to receive b/tsDMARDs (42.6% vs 58.7%, <i>p</i> = 0.02). In multivariate analysis, hypertension (OR: 4.69, 95% CI: 1.83-12.03) and diabetes (OR: 14.83, 95% CI: 2.36-93.05) were independently associated with LO-PsA.</p><p><strong>Conclusion: </strong>LO-PsA presents a distinct clinical profile characterized by greater comorbidity burden and lower exposure to advanced therapies. These findings highlight the need for tailored management strategies in older adults with PsA.</p>","PeriodicalId":23056,"journal":{"name":"Therapeutic Advances in Musculoskeletal Disease","volume":"17 ","pages":"1759720X251356206"},"PeriodicalIF":3.4,"publicationDate":"2025-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12254671/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144627113","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Current application, possibilities, and challenges of artificial intelligence in the management of rheumatoid arthritis, axial spondyloarthritis, and psoriatic arthritis.","authors":"Emre Bilgin","doi":"10.1177/1759720X251343579","DOIUrl":"10.1177/1759720X251343579","url":null,"abstract":"<p><p>This narrative review outlines the current applications and considerations of artificial intelligence (AI) for diagnosis, management, and prognosis in rheumatoid arthritis (RA), axial spondyloarthritis (axSpA), and psoriatic arthritis (PsA). Advances in AI, mainly in machine learning and deep learning, have significantly influenced medical research and clinical practice over the past decades by offering precisions in data understanding and treatment approaches. AI applications have enhanced risk prediction models, early diagnosis, and better management in RA. Predictive models have guided treatment decisions such as-response to methotrexate and biologics-while wearable devices and electronic health records (EHR) improve disease activity monitoring. In addition, AI applications are reported as promising for the early identification of extra-articular involvements, prediction, detection, and assessment of comorbidities. In axSpA, AI-driven models using imaging techniques such as sacroiliac radiography, magnetic resonance imaging, and computed tomography have increased diagnostic accuracy, especially for early inflammatory changes. Predictive algorithms help stratify and predict disease outcomes, while clinical decision support systems integrate clinical and imaging data for optimized management. For PsA, AI has also allowed for early detection among psoriasis patients using genetic markers, immune profiling, and EHR-based natural language processing systems. Overall, AI models may predict diagnosis, disease severity, treatment response, and comorbidities to improve care in patients with RA, axSpA, and PsA. As a rapidly developing and improving area, AI has the potential to change our current perspective of medical practice by offering better diagnostic evaluation and treatments and improved patient follow-up. Multimodal AI, focusing on collaboration, reliability, transparency, and patient-centered innovation, looks like the future of medical practice. However, data quality, model interpretability, and ethical considerations must be addressed to ensure reliable and equitable applications in clinical practice.</p>","PeriodicalId":23056,"journal":{"name":"Therapeutic Advances in Musculoskeletal Disease","volume":"17 ","pages":"1759720X251343579"},"PeriodicalIF":3.4,"publicationDate":"2025-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12182628/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144476792","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The neutrophil-to-lymphocyte ratio as a surrogate marker for disease activity in systemic lupus erythematosus: a correlation study using the SLE-DAS.","authors":"Mandy Ming Yan Wong, Fung Lam, Chi Chiu Mok","doi":"10.1177/1759720X251347272","DOIUrl":"10.1177/1759720X251347272","url":null,"abstract":"<p><strong>Background: </strong>The neutrophil-to-lymphocyte ratio (NLR) is a potential surrogate marker for disease activity in many rheumatic diseases.</p><p><strong>Objective: </strong>To study the correlation between NLR and disease activity of systemic lupus erythematosus (SLE) using the SLE disease activity score (SLE-DAS).</p><p><strong>Design: </strong>Retrospective, cross-sectional.</p><p><strong>Methods: </strong>Consecutive adult patients who fulfilled the American College of Rheumatology (ACR) or Systemic Lupus International Collaboration Clinic (SLICC) criteria for SLE were recruited between March 2023 and February 2024. SLE activity was assessed by physicians' global assessment (PGA), SLE-DAS, and SLE disease activity index-2000 (SLEDAI-2K). The calculated NLR was correlated with disease activity indices and serological parameters (anti-dsDNA, C3/4) by Spearman's rank correlation. Patients were stratified into SLE-DAS remission, mild, and moderate/severe disease activity, and a comparison of the NLR was performed among these subgroups by one-way ANOVA.</p><p><strong>Results: </strong>A total of 420 SLE patients were studied (93.1% women, age 31.6 ± 13.1 years, SLE duration 15.7 ± 8.1 years). Moderate/severe, mild disease activity and SLE-DAS remission were present in 70 (16.7%), 65 (15.5%), and 285 (67.9%) patients, respectively. SLE-DAS correlated significantly with SLEDAI-2K (rho 0.90; <i>p</i> < 0.001) and PGA (rho 0.60; <i>p</i> < 0.001). The mean NLR of all patients was 3.54 ± 4.0 and NLR correlated significantly with SLE-DAS (rho 0.17; <i>p</i> < 0.001). The NLR was significantly higher in patients with active disease in the SLE-DAS renal domain than those in remission (5.17 ± 7.11 vs 3.22 ± 3.19; <i>p</i> = 0.03). The NLR in patients with moderate/severe SLE-DAS activity (5.25 ± 6.89) was significantly higher than those with mild activity (3.12 ± 2.26; <i>p</i> < 0.01) or remission (3.22 ± 3.19; <i>p</i> < 0.01). ROC analysis showed that an NLR cut-off of 3.11 showed a sensitivity of 55.6% and specificity of 68.7% in detecting moderate/severe SLE-DAS activity (area under the curve 0.67 (0.6-0.7); <i>p</i> < 0.001).</p><p><strong>Conclusion: </strong>The NLR is a convenient marker that correlates significantly with disease activity in SLE.</p>","PeriodicalId":23056,"journal":{"name":"Therapeutic Advances in Musculoskeletal Disease","volume":"17 ","pages":"1759720X251347272"},"PeriodicalIF":3.4,"publicationDate":"2025-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12179458/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144476793","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Development and evaluation of a multivariable prediction model for clinical improvement in an established cohort of Colombian rheumatoid arthritis patients.","authors":"Claudia Ibáñez-Antequera, Gabriel-Santiago Rodríguez-Vargas, Fernando Rodríguez-Florido, Pedro Rodríguez-Linares, Adriana Rojas-Villarraga, Pedro Santos-Moreno","doi":"10.1177/1759720X251342426","DOIUrl":"10.1177/1759720X251342426","url":null,"abstract":"<p><strong>Background: </strong>Rheumatoid arthritis (RA) is a chronic autoimmune disease, and a predicting clinical improvement is essential.</p><p><strong>Objectives: </strong>The aim of the present study was to identify predictor variables of clinical improvement in patients with RA using artificial intelligence (AI) models in a specialized RA center.</p><p><strong>Design: </strong>Retrospective cohort study in adult RA patients was conducted between January and June 2022. Follow-up data related to clinical improvement was taken from 6 to 12 months after the baseline. Predictive models were generated by machine learning (ML), by Python programming language. The Transparent Reporting of a multivariate prediction model for Individual Prognosis or Diagnosis (TRIPOD) guidelines were followed to harmonize this study based on AI.</p><p><strong>Methods: </strong>The response variable was classified as improved and non-improved. Patients were considered improved if they persisted or achieved a Disease Activity Score 28-joints (DAS28) <3.2 at the end of the follow-up period or experienced a decrease ⩾0.6 compared to baseline, regardless of the initial DAS28 value. Explainability techniques in AI were applied to identify the most relevant clinical features.</p><p><strong>Results: </strong>In total, 3161 RA patients were included. The median age was 65 years (interquartile range (IQR) 57-72). 82.7% were female. Disease duration was 8.3 years (IQR 4.9-11.3). The median value of baseline DAS28 was 2.1 (IQR 2.1-2.8). 2668 (84.4%) were classified as improved, and 493 (15.6%) as non-improved. From ML models, the Extra tree model showed higher sensitivity (0.841). Regarding clinical improvement prediction with the Shapley Additive Explanations method, it was observed that low values of baseline DAS28 were positively associated with clinical improvement. The use of biologic disease-modifying antirheumatic drugs and the presence of anti-cyclic citrullinated peptide (CCP) were related to an increase in the probability of non-improved, which may be secondary to the level of severity of the disease.</p><p><strong>Conclusion: </strong>AI models in RA can predict clinical improvement at initial consultations, enabling targeted approaches. Disease severity may be influenced by anti-CCP positivity and the use of biologic therapies when conventional treatments fail.</p>","PeriodicalId":23056,"journal":{"name":"Therapeutic Advances in Musculoskeletal Disease","volume":"17 ","pages":"1759720X251342426"},"PeriodicalIF":3.4,"publicationDate":"2025-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12174781/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144326878","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Uveitis in patients with axial spondyloarthritis or psoriatic arthritis: a post hoc analysis from placebo-controlled phase III studies with secukinumab.","authors":"Jan Brandt-Jürgens, Martin Rudwaleit, Frank Behrens, Christopher Ritchlin, Daniel Peterlik, Erhard Quebe-Fehling, Atul Deodhar","doi":"10.1177/1759720X251340255","DOIUrl":"10.1177/1759720X251340255","url":null,"abstract":"<p><strong>Background: </strong>The incidence rate of uveitis in secukinumab-treated patients with axial spondyloarthritis (axSpA) was previously reported.</p><p><strong>Objective: </strong>To evaluate the incidence rate of uveitis in patients with axSpA and psoriatic arthritis (PsA) treated with secukinumab or placebo during placebo-controlled phase III studies.</p><p><strong>Design: </strong>This was a post hoc analysis from 11 phase III studies.</p><p><strong>Methods: </strong>Pooled data from axSpA (MEASURE 1-5 and PREVENT studies) and PsA (FUTURE 1-5 studies) were analyzed.</p><p><strong>Results: </strong>In the axSpA cohort (<i>N</i> = 1980), the incidence rate for uveitis was 1.29 per 100 patient-years in the secukinumab 150 mg and 1.72 per 100 patient-years in the placebo arm. In the PsA cohort (<i>N</i> = 2453), the incidence rate for uveitis was 0.71 per 100 patient-years in the secukinumab 300 mg arm; no events were reported in the placebo arm.</p><p><strong>Conclusion: </strong>During the placebo-controlled phase, a numerically lower incidence of uveitis was observed in secukinumab-treated axSpA patients. In PsA patients, the incidence was low in secukinumab-treated patients, while uveitis was not reported in the placebo group.</p>","PeriodicalId":23056,"journal":{"name":"Therapeutic Advances in Musculoskeletal Disease","volume":"17 ","pages":"1759720X251340255"},"PeriodicalIF":3.4,"publicationDate":"2025-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12144362/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144249738","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Inflammatory activity levels on patients with anti-TNF therapy: most important factors and a decision tree model based on REGISPONSER and RESPONDIA registries.","authors":"David Castro Corredor, Luis Ángel Calvo Pascual, Eduardo Collantes-Estévez, Clementina López-Medina","doi":"10.1177/1759720X251332224","DOIUrl":"https://doi.org/10.1177/1759720X251332224","url":null,"abstract":"<p><strong>Background: </strong>The effectiveness of anti-tumour necrosis factor (TNF) therapy in spondyloarthritis is traditionally associated with factors such as age, obesity and disease subtypes. However, less-explored aspects, such as mental health, socioeconomic status and work type may also play a crucial role in determining inflammatory activity and therapeutic response.</p><p><strong>Objectives: </strong>To identify the most significant factors explaining inflammatory activity levels in patients treated with anti-TNF therapy and to develop an interpretable machine-learning model with good performance and minimal overfitting.</p><p><strong>Design: </strong>This is an observational, cross-sectional and multicentre study with socio-demographical and clinical data extracted from the Registry of Spondyloarthritis of Spanish Rheumatology (REGISPONSER) and Ibero-American Registry of Spondyloarthropathies (RESPONDIA) registries.</p><p><strong>Methods: </strong>We selected patients receiving anti-TNF therapy and applied five feature selection methods to identify key factors. We evaluated these factors using 182 machine learning models, and, finally, we selected a decision tree model that offered comparable performance with reduced overfitting.</p><p><strong>Results: </strong>Activity levels appear strongly influenced by quality-of-life indicators, particularly the SF-12 physical and mental components and Ankylosing Spondylitis Quality of Life scores. While factors such as age, weight, years of treatment and age at diagnosis have relevance, they are not necessary to obtain a pruned tree with similar cross-validated mean accuracy.</p><p><strong>Conclusion: </strong>Recognizing the central role of physical and mental well-being in managing disease activity can lead to better therapeutic strategies for chronic disease management.</p>","PeriodicalId":23056,"journal":{"name":"Therapeutic Advances in Musculoskeletal Disease","volume":"17 ","pages":"1759720X251332224"},"PeriodicalIF":3.4,"publicationDate":"2025-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12078959/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144080367","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}