Osteoarthritis and cartilage open最新文献

{"title":"Development and validation of a generalisable survival model to predict osteoarthritis progression","authors":"H.H.T. Li ,&nbsp;L.C. Chan ,&nbsp;P.K. Chan ,&nbsp;C. Wen","doi":"10.1016/j.ocarto.2025.100688","DOIUrl":"10.1016/j.ocarto.2025.100688","url":null,"abstract":"<div><h3>Objective</h3><div>To develop and validate a transfer-learning survival model to predict progression end-stage knee osteoarthritis (esKOA) or receive knee replacement (KR).</div></div><div><h3>Method</h3><div>A DeepSurv model was trained on the Osteoarthritis Initiative (OAI) dataset with baseline clinical variables, including age, sex, BMI, comorbidities, smoking status, prior knee injury and surgery, pain medication use, use of walking aids, and activity level (9560 knees). A generalisable model was then developed by fine-tuning the OAI-derived model with data from the Multicenter Osteoarthritis Study (MOST) Centre 1 (3002 knees). This model was validated on an independent dataset from MOST Centre 2 (2972 knees). Model performance was evaluated using the concordance index from 1000 bootstrap resamples. SHapley Additive exPlanations (SHAP) were employed to assess changes in feature importance after fine-tuning.</div></div><div><h3>Results</h3><div>The OAI-derived model performed well within OAI (C-index ​= ​0.75) but fairly on MOST Centre 1 (C-index ​= ​0.61, <em>p</em> ​&lt; ​0.0001), indicating domain shift or cross-cohort variation. Similarly, a model trained only on MOST Centre 1 data performed moderately within MOST (C-index ​= ​0.63) but did not generalise to OAI (C-index ​= ​0.60, <em>p</em> ​&lt; ​0.0001). After transfer learning, the generalised model maintained performance on OAI (C-index ​= ​0.69) and improved on MOST Centre 1 (C-index ​= ​0.64, <em>p</em> ​&lt; ​0.0001) and MOST Centre 2 (C-index ​= ​0.67, <em>p</em> ​&lt; ​0.0001). SHAP analysis revealed that heart attack history, diabetes, smoking, and BMI became more influential predictors in the fine-tuned model.</div></div><div><h3>Conclusion</h3><div>Transfer learning enabled the development of a generalised model for knee OA prognosis that performs consistently across cohorts. By adapting to population-specific risk patterns, this approach enhances model generalisability and reduces bias from ethnic or demographic overrepresentation in training datasets.</div></div>","PeriodicalId":74377,"journal":{"name":"Osteoarthritis and cartilage open","volume":"7 4","pages":"Article 100688"},"PeriodicalIF":2.8,"publicationDate":"2025-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145220169","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Cross-sectional associations of radiographic multiple joint osteoarthritis and symptoms, laboratory values and the gut microbiota: A multimodal study in humans and pet dogs","authors":"Amanda E. Nelson ,&nbsp;Liubov Arbeeva ,&nbsp;Kelly Johnson ,&nbsp;Serena Savage-Guin ,&nbsp;Tessa Walker ,&nbsp;Masataka Enomoto ,&nbsp;Christina Stevens ,&nbsp;Milja Koskinen ,&nbsp;Tracey Cole ,&nbsp;Savannah Aker ,&nbsp;Connor Thonen-Fleck ,&nbsp;M. Andrea Azcarate-Peril ,&nbsp;Richard F. Loeser ,&nbsp;Jordan B. Renner ,&nbsp;Yvonne M. Golightly ,&nbsp;B. Duncan X. Lascelles","doi":"10.1016/j.ocarto.2025.100682","DOIUrl":"10.1016/j.ocarto.2025.100682","url":null,"abstract":"<div><h3>Objective</h3><div>To describe the frequency of multiple joint osteoarthritis (MJOA) and symptoms, and associations with fecal microbial diversity and composition, in cohorts of humans and dogs.</div></div><div><h3>Design</h3><div>Human participants enrolled in the community-based Johnston County Health Study (JoCoHS), and an independent cohort of pet dogs, were included. Questionnaires, functional assessments, standardized multiple joint radiographs, and pain assessments, blood and fecal samples were obtained. Microbiome analysis was done by 16S rRNA amplicon sequencing. MJOA was defined as ≥3 unique joint sites involved; symptom burden was based on self-reported/proxy measures of pain. Descriptive statistics and Spearman correlations with Benjamini-Hochberg correction were used to determine relationships among lab tests, pain, and microbiome diversity measures.</div></div><div><h3>Results</h3><div>Human participants (n ​= ​100, 63 ​% women, mean age 56 years, mean body mass index 34 ​kg/m²) and 115 pet dogs (40 ​% spayed females, 57 ​% neutered males, mean age 8 years, mean weight 27 ​kg) were included; 20 ​% had radiographic MJOA (rMJOA). Microbial α-diversity did not differ between participants with or without rMJOA. However, lower levels of the <em>Christensenellaceae R-7 group</em> and <em>Lachnoclostridium</em> in humans, and the butyrate-producing bacterium, <em>Faecalibacterium</em> in dogs, were moderately correlated with greater pain severity, as were higher levels of <em>Escherichia-Shigella</em> in dogs. <em>Faecalibacterium</em> was more abundant in humans without rMJOA.</div></div><div><h3>Conclusions</h3><div>These two cohorts demonstrated remarkably similar frequencies of rMJOA (∼20 ​%), supporting the use of dogs to model naturally occurring MJOA. Taxa potentially related to rMJOA and pain were identified in this preliminary analysis, providing new insights into links between dysbiosis and MJOA.</div></div>","PeriodicalId":74377,"journal":{"name":"Osteoarthritis and cartilage open","volume":"7 4","pages":"Article 100682"},"PeriodicalIF":2.8,"publicationDate":"2025-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145158746","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Artificial intelligence in osteoarthritis research: summary of the 2025 OARSI pre-congress workshop","authors":"Matthew S. Harkey ,&nbsp;Kerry E. Costello ,&nbsp;Bella Mehta ,&nbsp;Chunyi Wen ,&nbsp;Anne-Marie Malfait ,&nbsp;Henning Madry ,&nbsp;Brooke Patterson","doi":"10.1016/j.ocarto.2025.100687","DOIUrl":"10.1016/j.ocarto.2025.100687","url":null,"abstract":"<div><h3>Objective</h3><div>Artificial intelligence (AI) is transforming musculoskeletal research, offering new approaches to diagnosis, prognosis, and patient management in osteoarthritis (OA). However, implementation and ethical challenges persist. This manuscript summarizes insights from the OARSI 2025 Pre-Congress Workshop on Artificial Intelligence in Osteoarthritis Research, highlighting opportunities and challenges in applying AI across biomechanics, imaging, and clinical research domains.</div></div><div><h3>Design</h3><div>The workshop, organized by the OARSI Early Career Investigator Committee and co-chaired by Drs. Matthew Harkey and Brooke Patterson, convened experts to discuss the use of AI in real-world biomechanics data collection, radiomics for imaging-based biomarkers, and large language models (LLMs) for clinical and research applications. Emphasis was placed on the need for interdisciplinary collaboration and ethical oversight.</div></div><div><h3>Results</h3><div>In biomechanics, AI-driven markerless motion capture and wearable sensors enable scalable, ecologically valid data collection, though issues such as class imbalance, data privacy, and model interpretability remain. In imaging, radiomics and deep learning models show promise for early OA detection and progression prediction but face challenges in domain adaptation and external validation. In clinical research, LLMs can streamline documentation and thematic analysis but must address concerns around bias, data security, and transparency. Across domains, transparency, reproducibility, and ethical use of AI were emphasized as critical for maintaining scientific rigor.</div></div><div><h3>Conclusions</h3><div>Cross-disciplinary collaboration and AI literacy are essential to responsibly advance AI integration in OA research. The workshop's collective insights call for ethical, patient-centered approaches that leverage AI's strengths while preserving research integrity and trust.</div></div>","PeriodicalId":74377,"journal":{"name":"Osteoarthritis and cartilage open","volume":"7 4","pages":"Article 100687"},"PeriodicalIF":2.8,"publicationDate":"2025-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145158066","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Low-level laser therapy in osteoarthritic pain: A narrative review with an approach to integrated clinical use","authors":"S.N. Hennessy ,&nbsp;G.D. Corcoran","doi":"10.1016/j.ocarto.2025.100685","DOIUrl":"10.1016/j.ocarto.2025.100685","url":null,"abstract":"<div><h3>Objective</h3><div>The authors examine how Low-level laser therapy (LLLT) can be used in osteoarthritis (OA) management. LLLT has not, as yet, been widely integrated into OA management, either as a stand-alone modality or in conjunction with standard treatments.</div></div><div><h3>Methods</h3><div>A narrative review of meta-analyses and trials using LLLT in OA treatment was undertaken to establish how it may be used optimally in OA management. Pubmed, Google Scholar and Cochrane databases were interrogated to identify analyses and trials.</div></div><div><h3>Results</h3><div>Meta-analysis and trial results are variable, but improvements of up to 14.23 ​mm are noted in VAS scores following use in knee osteoarthritis (Standardised Mean Difference (SMD) 95 ​% CI: 7.31:21.14), 13.7 ​mm in spinal disease (SMD 95 ​% CI: 9.72; 17.42) and 19.86 ​mm (SMD 95 ​% CI: 10.04:29.68) in cervical disease. Positive effects on function were documented, as was a reduction in use of analgesic medication. Integration of LLLT into OA management programmes produced additional improvements. The side-effect profile is excellent. Issues of trial size, comparability, dosing, and assessment of response, mean that further studies are required.</div></div><div><h3>Conclusions</h3><div>We conclude that LLLT is useful in the management of OA pain, with benefits for stiffness and function. Use as an integral part of an OA management and rehabilitation plan appears to give additional benefits. LLLT has an excellent side effect profile and may reduce need for analgesic medication, making it a potentially valuable adjunct in OA pain management, especially at a time when adverse effects of pharmacological treatment are of increasing concern.</div></div>","PeriodicalId":74377,"journal":{"name":"Osteoarthritis and cartilage open","volume":"7 4","pages":"Article 100685"},"PeriodicalIF":2.8,"publicationDate":"2025-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145158710","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Organ-on-chip technologies: Novel tools with the potential to revolutionize osteoarthritis research and clinical development","authors":"Carlo Alberto Paggi","doi":"10.1016/j.ocarto.2025.100686","DOIUrl":"10.1016/j.ocarto.2025.100686","url":null,"abstract":"<div><h3>Objective</h3><div>To critically evaluate the evolution of in vitro models for osteoarthritis (OA) research, with a specific focus on organ-on-chip (OOC) technologies, and to discuss their potential to overcome the limitations of traditional 2D, 3D, and explant models in disease modelling, drug discovery, and preclinical toxicology.</div></div><div><h3>Methods</h3><div>This review synthesizes findings from recent literature regarding historical and current in vitro platforms used in OA research. It categorizes models based on biological complexity and physiological relevance, with particular emphasis on biomechanical and biochemical stimulation in OOC systems. Key examples from the literature are discussed to illustrate the utility and scalability of emerging platforms.</div></div><div><h3>Results</h3><div>Traditional 2D cultures, while widely used, lack the spatial and environmental complexity necessary to replicate native joint physiology. 3D cultures and explant models provide improved architecture and cellular context, but face challenges related to standardization, longevity, and reproducibility. OOC systems offer a dynamic and tunable microenvironment that supports real-time monitoring and integration of mechanical cues such as shear stress and compression. These platforms have been successfully employed to investigate immune cell migration, drug permeability across barriers, and cytokine-induced matrix degradation. Furthermore, their application in preclinical modelling for efficacy and safety studies highlights the potential for more predictive, human-relevant data compared to conventional methods.</div></div><div><h3>Conclusion</h3><div>OOCs technology represents a transformative advance in OA modelling, offering increased physiological relevance and experimental precision. With continued refinement and validation, OOC platforms could significantly improve the translational success of disease-modifying OA therapies.</div></div>","PeriodicalId":74377,"journal":{"name":"Osteoarthritis and cartilage open","volume":"7 4","pages":"Article 100686"},"PeriodicalIF":2.8,"publicationDate":"2025-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145158709","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The relationship between circulating and tissue biomarkers and OA-related pain: A systematic literature review","authors":"Sylvain Mathieu ,&nbsp;Liisa Kuhi ,&nbsp;Marie Binvignat ,&nbsp;Philip G. Conaghan ,&nbsp;Niels Eijkelkamp ,&nbsp;Yves Henrotin ,&nbsp;Eva Kosek ,&nbsp;Ali Mobasheri ,&nbsp;Hans-George Schaible ,&nbsp;Kalle Kisand ,&nbsp;Jérémie Sellam","doi":"10.1016/j.ocarto.2025.100684","DOIUrl":"10.1016/j.ocarto.2025.100684","url":null,"abstract":"<div><h3>Objective</h3><div>This study aimed to provide an overview of the relationship between osteoarthritis (OA) pain and various fluid biomarkers by conducting a systematic literature review (SLR), to help the development of OA-related pain endotyping.</div></div><div><h3>Method</h3><div>An SLR was conducted, using the PubMed, Embase, Scopus, Web of Science and the Cochrane Library databases, up to December 2024. Pain measures (VAS, WOMAC, HOOS/KOOS, AUSCAN, PainDETECT and Pain Pressure Threshold) were analysed for their association with circulating biomarkers in blood, urine, synovial and cerebrospinal fluids or tissue and genetic biomarkers. Biomarkers were categorised as “associated” depending on statistical significance and further subcategorised as “consistently associated”, “uncertainly associated” or “not associated” based on the quality of evidence determined by the number of studies, sample size and the strength of correlation.</div></div><div><h3>Results</h3><div>The five databases yielded 30,088 citations, of which 263 relevant papers were selected. Total cholesterol in the blood was the only biomarker consistently associated with pain. Among blood biomarkers, CRP, hsCRP and IL-17 showed suggestive but inconsistent associations with OA-related pain. In synovial fluid, IL-17, C2C and VEGF were consistently associated with increasing pain intensity, based on multiple concordant studies. In cerebrospinal fluid, CX3CL1 and Flt-1 were consistently associated with pain, displaying a negative correlation.</div></div><div><h3>Conclusion</h3><div>This SLR identified no relevant biomarkers in different body fluids that were associated with OA-related pain. Further investigation of CRP and IL-17 is required to achieve greater consistency across studies.</div></div><div><h3>PROSPERO</h3><div>CRD42024550244.</div></div>","PeriodicalId":74377,"journal":{"name":"Osteoarthritis and cartilage open","volume":"7 4","pages":"Article 100684"},"PeriodicalIF":2.8,"publicationDate":"2025-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145109130","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Development of an iPSC-based screening platform identifying enhancers of chondrogenesis","authors":"Aisling O'Brien ,&nbsp;Maojia Xu ,&nbsp;Enda O'Connell ,&nbsp;Aline M. Morrison ,&nbsp;Georgina Shaw ,&nbsp;James R. Dutton ,&nbsp;Mary Murphy ,&nbsp;Frank Barry","doi":"10.1016/j.ocarto.2025.100680","DOIUrl":"10.1016/j.ocarto.2025.100680","url":null,"abstract":"<div><h3>Objective</h3><div>There is currently no long-term treatment for the repair of damaged cartilage and osteoarthritis (OA). Induced pluripotent stem cells (iPSCs) are an ideal cell source for screening platforms due to their ability to self-renew and differentiate to cell types that would otherwise require invasive surgeries to obtain, such as chondrocytes and mesenchymal stromal cells (MSCs). Here, we developed an iPSC-based screening platform and tested previously described pro-chondrogenic small molecule compounds, to determine their potential to identify hits.</div></div><div><h3>Design</h3><div>iPSC derived chondroprogenitors (iCPs) and neural crest cell (NCC) derived MSCs (iNCC-MSCs) were generated, and their chondrogenic potential was confirmed. The iPSC derived cells and a primary bone marrow derived MSC (BM-MSC) line were cultured as pellets and treated with different concentrations of small molecule compounds, in the presence of chondrogenic inducing growth factors, over 14 days at 2 ​% O₂. Glycosaminoglycan (GAG) synthesis was quantified by a 1,9- dimethylmethylene blue (DMMB) assay.</div></div><div><h3>Results</h3><div>After 14 days of chondrogenesis, forskolin, baicalin and sesamin enhanced GAG synthesis in the iCPs, and forskolin enhanced GAG synthesis in the iNCC-MSCs, while no small molecule compounds enhanced GAG synthesis in the BM-MSCs.</div></div><div><h3>Conclusion</h3><div>Our findings further demonstrate how the small molecules pro-chondrogenic effects are dependent on the screening platform conditions, including the cell type, molecule concentration, 3D culture, hypoxia, and the inclusion of additional growth factors. The iPSC-based screening platform developed has the potential to identify disease modifying OA drugs (DMOADs) in novel compound screening libraries.</div></div>","PeriodicalId":74377,"journal":{"name":"Osteoarthritis and cartilage open","volume":"7 4","pages":"Article 100680"},"PeriodicalIF":2.8,"publicationDate":"2025-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145158067","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Defining and measuring varus thrust in knee osteoarthritis: A scoping review of current evidence and challenges","authors":"Vincenzo E. Di Bacco ,&nbsp;Zaryan Masood ,&nbsp;Joshua A.J. Keogh ,&nbsp;Matthew C. Ruder ,&nbsp;Fatima Gafoor ,&nbsp;Jenny Wu ,&nbsp;Yalda Azari ,&nbsp;Eseoghene Orogun ,&nbsp;Dylan Kobsar","doi":"10.1016/j.ocarto.2025.100683","DOIUrl":"10.1016/j.ocarto.2025.100683","url":null,"abstract":"<div><h3>Objective</h3><div>This scoping review investigated the definitions, assessment methods, and current applications of varus thrust (VT) in knee osteoarthritis (OA).</div></div><div><h3>Methods</h3><div>Five databases (MEDLINE, EMBASE, CINAHL, SPORTDiscus, and Web of Science Core Collection) were searched in this scoping review for studies assessing VT during walking in adults with knee OA using the terms “varus” and “lateral” in proximity to thrust. Data were extracted and categorized by study characteristics (OA sample, publication year, design, and aim) and VT assessment protocol (method and definition).</div></div><div><h3>Results</h3><div>A total of 63 studies were included, examining 12,569 individuals with knee OA using visual (<em>n</em> ​= ​24), optical motion capture (<em>n</em> ​= ​27), or inertial/wearable sensor (<em>n</em> ​= ​19) methods. Designs included prospective, experimental, cross-sectional, and case series. VT was most often assessed to examine disease severity, progression, surgical outcomes, and symptom associations. Visual VT was commonly defined as dynamic worsening or abrupt onset of varus alignment during weight acceptance. Optical motion capture commonly measured VT as frontal plane knee excursion from foot contact to mid-stance, while inertial methods typically used peak lateral tibial acceleration or angular velocity.</div></div><div><h3>Conclusion</h3><div>Despite growing research interest in VT, inconsistent definitions and measurement protocols limit comparability across studies and hinder broader adoption. Greater standardization and validation are needed to clarify its potential clinical utility in knee OA.</div></div>","PeriodicalId":74377,"journal":{"name":"Osteoarthritis and cartilage open","volume":"7 4","pages":"Article 100683"},"PeriodicalIF":2.8,"publicationDate":"2025-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145105128","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Walking is the form of physical activity people with osteoarthritis in the hip or knee choose and maintain after two years","authors":"R. Bendrik ,&nbsp;M. Peterson ,&nbsp;K. Bröms ,&nbsp;M. Emtner ,&nbsp;A. Hed Ekman ,&nbsp;L.V. Kallings ,&nbsp;B. Sundström","doi":"10.1016/j.ocarto.2025.100681","DOIUrl":"10.1016/j.ocarto.2025.100681","url":null,"abstract":"<div><h3>Objective</h3><div>To evaluate which form and type of physical activity individuals with hip or knee osteoarthritis choose and maintain one and two years after an individualised intervention for physical activity and further to evaluate whether there were differences in the most chosen physical activity with regard to patient characteristics.</div></div><div><h3>Method</h3><div>Patients with hip or knee osteoarthritis from a previous randomised controlled trial, where they received individualised patient-centred counselling about physical activity and registered self-selected sessions of physical activity in a 7-day diary, were included. Sessions lasting more than 10 ​min and rated at least light effort were categorized, and differences were evaluated.</div></div><div><h3>Results</h3><div>Of the 94 patients included, 72.3 ​% were female, 72.0 ​% had knee osteoarthritis and mean age was 62.0 (SD 8.2) years. Women and men who preferred walking, walked on average ​&gt; ​4 times/week and 3–4 times/week, respectively. Everyday activities and cycling were performed 2–3 times/week by both women and men. The proportions of individuals maintaining the same activity after one and two years were 50 ​% for walking and 2 ​% for strength training. Men more often choose different activities and after two years they performed everyday activities and cycling to the same extent as walking. Individuals who chose walking were significantly older, of female gender and had lower muscle strength in the affected leg.</div></div><div><h3>Conclusion</h3><div>Walking is the form of physical activity patients with osteoarthritis most often choose, perform and maintain. Knowledge about preferred activities among patients is crucial for maintaining physical activity in the long term.</div></div>","PeriodicalId":74377,"journal":{"name":"Osteoarthritis and cartilage open","volume":"7 4","pages":"Article 100681"},"PeriodicalIF":2.8,"publicationDate":"2025-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145105129","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Biochemical biomarkers of knee osteoarthritis progression: Results from the FNIH biomarkers consortium progress OA study","authors":"Jamie E. Collins ,&nbsp;Douglas Robinson ,&nbsp;Nigel Arden ,&nbsp;Anne Christine Bay-Jensen ,&nbsp;Leticia A. Deveza ,&nbsp;Morten Karsdal ,&nbsp;Christoph Ladel ,&nbsp;Thomas A. Perry ,&nbsp;Christopher J. Swearingen ,&nbsp;David J. Hunter ,&nbsp;Virginia B. Kraus","doi":"10.1016/j.ocarto.2025.100677","DOIUrl":"10.1016/j.ocarto.2025.100677","url":null,"abstract":"<div><h3>Objective</h3><div>The Foundation for National Institutes of Health (FNIH) OA Biomarkers Consortium aims to identify and qualify biomarkers to support drug development in knee osteoarthritis (OA). The PROGRESS OA study aims to externally validate prognostic biomarkers identified in the earlier Phase I study.</div></div><div><h3>Design</h3><div>PROGRESS OA included data from the control arms of several completed randomized controlled trials (RCTs) for knee OA. The primary outcome was medial or lateral joint space width loss (JSWL) ≥0.7 ​mm. Secondary outcomes included medial or lateral JSWL combined with symptomatic progression. Nine biochemical biomarkers identified in Phase I were included here. Logistic regression with elastic net selection examined associations between baseline biomarkers and outcomes over 12–36 months, separately for subgroups with available serum, urine, and both serum and urine biomarkers.</div></div><div><h3>Results</h3><div>In total, the study included 827 participants across three RCTs, 159 (19 ​%) with JSWL≥0.7 ​mm. In 681 participants with both serum and urine biospecimens, the combination of serum hyaluronan (HA), urinary C2C-HUSA, body mass index (BMI), and Kellgren-Lawrence grade (KLG) yielded AUC 0.627 (95 ​% CI: 0.573, 0.681) for predicting JSWL≥0.7 ​mm, compared to AUC 0.612 (95 ​% CI: 0.557, 0.667) for BMI and KLG alone. Serum (HA) and urinary C2C-HUSA were consistently selected as predictors of disease progression in elastic net models across the subgroups.</div></div><div><h3>Conclusions</h3><div>Biomarker associations were consistent with Phase I findings, but predictive performance remained modest. Future work in the FNIH OA Biomarkers consortium project will focus on evaluating short term changes in biomarkers to assess their potential for monitoring treatment efficacy.</div></div>","PeriodicalId":74377,"journal":{"name":"Osteoarthritis and cartilage open","volume":"7 4","pages":"Article 100677"},"PeriodicalIF":2.8,"publicationDate":"2025-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145105130","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}