OBJECTIVE:Network meta-analyses (NMAs) frequently inform recommendations for osteoarthritis (OA), but methodological flaws may introduce bias and yield misleading results. This methodological study aimed to evaluate the risk of bias in a restricted sample of systematic reviews incorporating NMAs of health care interventions for knee and hip OA. METHOD:We searched PubMed to identify NMAs published in 22 leading general/internal medical and specialty journals ('Rheumatology/Orthopedics', 'Rehabilitation/Sports Sciences') that evaluated pharmacological or non-pharmacological interventions for knee or hip OA pain or physical function. Risk of bias was assessed independently by two reviewers using the ROBIS tool in combination with the Risk of Bias in Network Meta-Analysis (RoB NMA) tool. RESULTS:A total of 21 NMAs were included. Of these, 11 (52%) evaluated pharmacological interventions, 7 (33%) non-pharmacological interventions, and 3 (14%) a combination. Most NMAs (13; 62%) were rated high risk of bias, four (19%) raised some concerns, and four (19%) were low risk. Risk of bias was most frequently related to intervention grouping and assessment of transitivity, including limited consideration of effect modifiers and statistical consistency. Assessments took a median of 45 minutes (range: 20-110 minutes), with 67-71% inter-rater agreement and slight to fair agreement statistics. CONCLUSION:Knee and hip OA NMAs published in leading journals frequently exhibit limitations in intervention grouping and assessment of transitivity, potentially affecting their validity. Future OA NMAs should implement transparent node-making and assess transitivity a priori by examining key clinical and methodological study characteristics to determine whether valid statistical synthesis is feasible.
Objectives To gain insight in Stepped Care (SC) adherence prior to orthopedic consultation in patients 55 years of age or older with a symptomatic knee, in treatment choices following orthopedic consultation and in factors associated with arthroplasty as preferred treatment. Methods Prospectively collected Computer-Assisted History Taking data from three hospitals was used to allocate included patients (n=7874, average age 66.8 years (SD: ±8.2), 54% female) into a full SC (three steps: non anti-inflammatory analgesics, anti-inflammatory drugs, exercises), a partial SC (missing 1 or 2 steps) or a no SC group (no steps applied). Regression analyses were used to evaluate how clinical features, SC adherence and radiographic severity were associated with arthroplasty as a treatment choice following orthopedic consultation. Results Prior to orthopedic consultation, full SC adherence was 12%, partial SC 66.3% and no SC 21.7%. For the majority of patients (71.6%), treatment following orthopedic consultation consisted of non-operative OA management options. Increasing age, higher BMI, longer symptom duration, greater pain during activity, reduced walking ability, and full adherence to SC were all associated with higher odds of arthroplasty, with a highest Odds Ratio of 4.4 (95% Confidence Interval: 3.7-5.3) for symptom duration. Conclusions Despite clinical guidelines outlining a SC approach to manage knee OA, only a small proportion of patients of 55 years of age or older with knee complaints have utilized all non-surgical treatment options before being referred for orthopedic consultation in the Netherlands. Most patients consulting an orthopedic surgeon receive conservative treatment modalities, also included in the Dutch clinical guideline on knee symptoms for GPs.
OBJECTIVE:To evaluate care delivery models for knee osteoarthritis (OA) versus usual care in primary health care settings and explore effects by delivery arrangement subcategory. METHOD:Systematic review and meta-analysis of randomized controlled trials (RCTs). We searched PubMed, Embase, CENTRAL and trial registries from 1 January 2010 to 28 June 2026. Delivery differences were mapped using the Cochrane Effective Practice and Organisation of Care (EPOC) Delivery Arrangements taxonomy. Outcomes were pain, function and health-related quality of life (HRQoL). Risk of bias and certainty were assessed using RoB 2 and GRADE respectively. RESULTS:Fifteen RCTs (n=2,944) were included. Compared with usual care, care delivery models improved pain (SMD -0.40, 95% CI -0.63 to -0.16) and function (SMD -0.26, 95% CI -0.39 to -0.14), with little to no difference in HRQoL (SMD 0.00, -0.10 to 0.09). Back-translated effects did not reach prespecified minimal clinically important differences (MCIDs) for pain (0.68 vs 2 NRS points) or function (4.2 vs 12 WOMAC Function points). Certainty was moderate for pain and function, and high for HRQoL. Exploratory subgroups incorporating information and communication technology (ICT) suggested benefit, but each included only two or three trials. CONCLUSION:Care delivery models produced small improvements in pain and function, but these did not reach prespecified MCIDs. There was little to no difference in HRQoL. Only 15 trials were included, and findings from subgroups of two or three trials should be interpreted cautiously. ICT-supported delivery, particularly when combined with care coordination, warrants evaluation in larger pragmatic trials with longer follow-up.
OBJECTIVE:To quantify general population prevalence, and differences by sex and BMI, in ultrasound (US) features of knee osteoarthritis (KOA), patient-reported knee symptoms (Ksx), radiographic KOA (rKOA), and symptomatic KOA (sxKOA). METHODS:Participants from the Johnston County Health Study (2019-2024; n=902) provided demographic, clinical, and imaging data. Ksx was defined as self-reported pain, aching or stiffness on most days of any one month in the past 12 months. rKOA was defined as Kellgren-Lawrence grade ≥2 (or total knee replacement (TKR)), severe rKOA as grades 3-4 (or TKR), and sxKOA as rKOA and Ksx in the same knee. Standardized US scoring was performed as previously reported. Weighted prevalence estimates and 95% confidence intervals (CI) for Ksx, rKOA, sxKOA, severe rKOA, and US features were calculated overall and by sex and BMI category. RESULTS:Among 902 participants (67% female; 66% non-Hispanic white, mean age 55 years, and BMI 33 kg/m²), the weighted prevalence of Ksx, rKOA, sxKOA, and severe rKOA were 61%, 36%, 27%, and 21%, respectively, all higher (based on non-overlapping CIs) than baseline estimates from the Johnston County Osteoarthritis Project and other cohorts. Ksx, rKOA, sxKOA, and severe rKOA were higher among females and those with obesity. Compared to females with obesity, those with severe obesity had higher prevalence of all radiographic outcomes at moderate and severe grades with non-overlapping CI. US effusion and synovitis were more prevalent in males, whereas medial and lateral cartilage damage were more common in females. With increasing obesity, osteophytes and medial cartilage damage were more prevalent, while gryescale effusion was actually less frequent. CONCLUSION:KOA prevalence continues to increase in the population. Sex and BMI differences in KOA prevalence and US features were most pronounced among females with severe obesity. Distinguishing between sexes and by obesity levels may improve understanding of KOA mechanisms and guide tailored prevention and treatment strategies.
OBJECTIVES:This study aimed to develop KOA-Diff, a multimodal diffusion model predicting future knee radiographs for accurate, visually interpretable forecasting of knee osteoarthritis (KOA) progression. METHODS:KOA-Diff utilizes a latent diffusion backbone and a multimodal fusion network to integrate baseline X-rays, MRIs, and clinical characteristics. A feature-targeting attention mechanism guides image generation toward critical anatomical structures. The model was trained and internally validated on the Osteoarthritis Initiative (OAI) dataset and externally validated on a private cohort (PUTH-KOA, n=80). We evaluated the synthesized future radiographs using joint space width error (JSWE, error relative to the actual width) and binary Kellgren-Lawrence (KL) grade accuracy (early [KL ≤2] vs. advanced [KL ≥3]). Additionally, blinded experts graded structural features. Finally, clinical utility was tested by using model outputs to assist clinicians in identifying high-risk patients exhibiting a longitudinal KL grade increase ≥2 levels over 8 years. RESULTS:In the OAI dataset, KOA-Diff achieved a JSWE of 0.71%-1.21% and binary KL-grade accuracy of 84.0%-91.8% over 96 months. External validation demonstrated promising performance with 90.0% binary KL-grade accuracy and 2.06% JSWE. In the blinded evaluation, experts rated the accuracy of synthesized features on a 5-point scale. For the OAI cohort, the model scored 4.162 (joint space narrowing), 3.895 (osteophyte formation), and 3.943 (subchondral bone sclerosis). PUTH-KOA scores were consistently high (4.050, 3.925, 3.775, respectively). With model assistance, clinicians' accuracy in identifying high-risk patients improved from 58.3% to 77.5%. CONCLUSIONS:KOA-Diff synthesizes future radiographs reflecting accurate structural progression, providing an interpretable tool for KOA prediction.
OBJECTIVE:Osteoarthritis (OA) is characterized by progressive cartilage loss and is a major cause of chronic pain and disability. The infrapatellar fat pad (IFP) is an adipose tissue that contacts the synovium and is implicated in knee OA pain. However, the molecular mechanisms linking the IFP to pain remain poorly understood. In this study, we explored a potential IFP-derived mediator of knee OA pain. DESIGN:Knee OA was induced in male and female Sprague Dawley rats by the intra-articular monoiodoacetic acid injection, and saline was injected as a control. Pain-related behaviors of MIA model rats were assessed using the Pressure Application Measurement (n = 7) and von Frey tests (n = 6-7). RNA sequencing was performed on IFP tissue from MIA model and control rats (n = 4). Expression levels of apelin and its receptor APJ were examined using quantitative polymerase chain reaction, and APJ distribution was examined with immunofluorescence. The involvement of apelin and nerve growth factor (NGF) in knee pain was investigated by intra-articular injection of [Pyr1]-apelin-13, the APJ antagonist ML221 and an anti-NGF antibody. RESULTS:Apelin signaling was identified as the most significant pathway relating to differentially expressed genes in the IFP from rats with knee OA. Apelin expression was upregulated in the IFP, and the intra-articular injection of [Pyr1]-apelin-13 caused knee pain (estimated mean difference of -294.8 g and 95% CI of -487.3 to -102.3 g in the PAM test on day 1). APJ expression was markedly increased in synoviocytes of knee OA. The APJ antagonist ML221 alleviated knee OA pain (estimated mean difference of 239.9 g and 95% CI of 125.3-354.6 g in the PAM test on day 1), in association with reduced NGF expression in the synovium. [Pyr1]-apelin-13-induced knee pain was suppressed by anti-NGF antibody (estimated mean difference of 234.9 g and 95% CI of 124.9-344.9 g in the PAM test on day 1). CONCLUSIONS:Our findings indicate that apelin causes knee OA pain by regulating NGF expression in the synovium of MIA model rats. Targeting apelin signaling may therefore provide a novel analgesic therapy for knee OA pain.
OBJECTIVE:Osteoarthritis is the most common degenerative joint disease worldwide, characterized by degeneration of articular cartilage caused by chondrocyte dysfunction and invasion of vessels from subchondral bone. However, the molecular mechanisms governing the dyshomeostasis of cartilage and subchondral bone during osteoarthritis remain unclear. Emerging evidence indicates that myocyte enhancer factor 2D (MEF2D) promotes chondrocyte hypertrophy and vascularization, whereas its role in osteoarthritis has not yet been reported. METHODS:To explore the role of MEF2D, we generated and identified MEF2D conditional knockout mice and established osteoarthritis models via DMM or ACLT surgery. Samples were evaluated using micro-CT, histological, and immunofluorescence analyses, whereas molecular mechanisms were elucidated by RNA-Seq, CUT&Tag, ChIP, and dual-luciferase reporter assays. RESULTS:MEF2D was aberrantly overexpressed in murine osteoarthritis cartilage, whereas osteoarthritis progression was delayed in MEF2D knockout mice (p = 0.0359, OARSI grade, -1.048 [95% CI: -2.034, -0.06209]). Functionally, MEF2D bound to the promoter of lactate dehydrogenase A (LDHA) to activate its transcription, and induced the expression of inflammatory cytokines via LDHA/IκB-ζ signaling, which subsequently promoted the expression of catabolic genes. Moreover, MEF2D increased VEGF secretion by chondrocytes through upregulating brain-derived neurotrophic factor (BDNF) (p < 0.0001, MD = 9.486 [95% CI: 7.185, 9.622]). Additionally, BDNF secreted by chondrocytes binds to its receptor TrkB to form a BDNF/TrkB autocrine loop that positively regulates MEF2D expression (p = 0.0002, MD = 0.9250 [95% CI: 0.5709, 1.279]). Injection of a TrkB antagonist into the articular cavities of osteoarthritis model mice provided preliminary evidence of delayed cartilage degeneration, subchondral osteosclerosis, and osteophyte formation. CONCLUSION:Our study revealed a critical transcriptional regulatory role of MEF2D in osteoarthritis, and further suggested that targeting MEF2D may represent a potential therapeutic strategy.
OBJECTIVES:To disentangle the molecular heterogeneity of knee osteoarthritis (OA) through the classification and characterization of transcriptomic clusters in multiple joint tissues, and to uncover distinct biological pathways that will facilitate improved patient stratification. METHODS:We analyzed RNA sequencing data from 330 knee OA patients across low- and high-grade OA knee cartilage, synovium and infrapatellar fat pad tissues. We used unsupervised machine learning to identify distinct transcriptomic clusters and subsequently performed cluster-specific differential expression and pathway enrichment analyses. We applied multi-omics factor analysis in low-grade cartilage to construct a gene expression-based classifier for subtype prediction, which we validated in an independent knee OA RNA sequencing dataset. RESULTS:We identified robust clusters across all four joint tissues. In low-grade cartilage, we identified two patient groups separated by differences in inflammation and transcriptional regulation. A gene classifier distinguished these groups with a cross-validated accuracy of 94.5% (95% CI 91.1-96.6%). We also reproduced these subtypes in an external cohort in which the same axis similarly separated the subgroups. In high-grade cartilage there were three distinct clusters, characterized by inflammatory, neuroactive receptor-signaling, and housekeeping-transcriptional programs. Both synovium and infrapatellar fat pad showed two distinct subgroups. Despite the histological differences between these two tissues, subgrouping was based on shared biological functions related to immune activation, alongside disease tissue-specific ones. CONCLUSIONS:Our findings identify gene expression-based patient clusters in different primary joint tissues and point to shared and disease tissue-specific molecular programs in OA, thus setting the foundation for transcription signature-based patient stratification.
OBJECTIVE:With the recognition that crosstalk between articular cartilage and subchondral bone may contribute to osteoarthritis (OA), interest in the subchondral osteoblast secretome has grown significantly. Osteoblasts respond to alterations in their microenvironment by expressing a range of signaling and structural cytokines affecting bone remodeling and cartilage breakdown characteristic of OA. This narrative review explores observations made with circulatory imaging of subchondral bone in OA and presents a reconciliation of them in the context of a subchondral hypoxic microenvironment and osteoblast synthetic responses. The pathogenesis of OA is multifactorial and venous stasis, the resulting intraosseous microenvironment, and the consequent osteoblast responses appear to play significant roles. DESIGN:This is a narrative review. A literature search was conducted in PubMed (Medline), Google Scholar, and the Cochrane Library. Search criteria included OA associated with vascularity or perfusion status, osteoblast secretome and cytokines, and hypoxia. RESULTS:Bone is a highly vascular tissue, and its circulatory integrity is a major determinant of the osteoblast microenvironment and secretome. Static imaging studies have shown an altered venous pattern in human OA compared to normal hips with slower elimination of contrast agent consistent with venous stasis. Intraosseous hypertension and hypoxia have also been observed in OA compared to normal subchondral bone. Subchondral osteoblasts respond to an abnormal microenvironment by an altered secretome consistent with bone remodeling and cartilage breakdown typical of OA. Dynamic imaging with contrast-enhanced MRI and 15O-Oxygen and 18F-Fluoride PET have allowed kinetic analyses of bone circulation including temporal and spatial patterns of blood flow in conjunction with cartilage breakdown and subchondral bone remodeling, lending insight into the early pathogenesis of OA. CONCLUSIONS:Subchondral hypertension and hypoxia as consequences of circulatory pathology have emerged as stimuli to pathologic osteoblast cytokine expression.
OBJECTIVE:Osteoarthritis (OA) is characterized by cartilage degeneration, oxidative stress, and chondrocyte senescence. This study investigated whether TL1A promotes OA through ENO1-associated redox, senescence and PI3K-AKT signaling mechanisms. METHOD:Human paired OA cartilage, primary chondrocytes, and mouse age-associated and destabilization of the medial meniscus (DMM)-induced OA models were used. TL1A and ENO1 were manipulated using genetic deletion, intra-articular adenoviral delivery, and siRNA-mediated silencing. Oxidative stress, cellular senescence, cartilage degeneration, ENO1-related regulatory mechanisms, and PI3K-AKT activation were assessed using histology, immunostaining, Western blotting, qPCR, RNA-seq, co-immunoprecipitation, ubiquitination assays, and pharmacological rescue experiments. RESULTS:TL1A-positive chondrocytes were increased in damaged versus paired undamaged human cartilage (n = 8 paired patients) [mean paired difference, +64.24 percentage points; 95% CI, 57.80-70.68]. In DMM mice, Tl1a deletion reduced cartilage damage [OARSI Hodges-Lehmann (HL) difference, -2.50; 95% CI, -4 to 0], whereas intra-articular Tl1a overexpression induced mild OA-like cartilage changes [OARSI HL difference, +0.75; 95% CI, 0-1.50]. TL1A silencing reduced ROS fluorescence in IL-1β-treated human chondrocytes [mean change, -53.50%; 95% CI, -61.59 to -45.41]. TL1A interacted with ENO1 and was associated with altered ENO1 ubiquitination and protein abundance; Eno1 overexpression restored OA severity in DMM-operated Tl1a-/- mice [OARSI HL difference, +3.75; 95% CI, 3-5.50]. PI3K-AKT activation contributed to this phenotype, as 740 Y-P increased OARSI scores in DMM-operated Tl1a-/- mice [HL difference, +1.25; 95% CI, 0-2.50]. CONCLUSION:TL1A contributes to OA progression by promoting ENO1-associated redox imbalance, chondrocyte senescence, and PI3K-AKT signaling, supporting the TL1A-ENO1 axis as a potential therapeutic target.
OBJECTIVE:To investigate associations between infrapatellar fat pad volume (IPFPVol) measured on MRI with knee cartilage thickness and imaging features of knee osteoarthritis. DESIGN:This cross-sectional study used baseline data from the Osteoarthritis Initiative. IPFPVol was quantified using a deep learning algorithm for automatic volumetric IPFP segmentation. Outcomes by subregion included knee cartilage thickness in the lateral tibia (LT), medial tibia (MT), lateral femur (LF), medial femur (MF), and patella, along with Whole-Organ Magnetic Resonance Imaging Score (WORMS) scores for cartilage, bone marrow edema-like lesions (BMELL), and menisci across the same subregions and the trochlea. Linear regression models included an interaction term between IPFPVol and subregion. When interactions were significant, subregion-specific associations were estimated. Models were adjusted for relevant confounders. RESULTS:A total of 4257 participants were included in the final analysis. Significant interactions between IPFPVol and subregion were observed for cartilage thickness and WORMS scores (all p<0.001). Larger IPFPVol was associated with greater cartilage thickness in the patella (β = 0.011 mm per cm³; 95% CI, 0.006-0.016) and LT (β = 0.015 mm per cm³; 95% CI, 0.010-0.019). For WORMS, larger IPFPVol was associated with lower cartilage lesion scores in the patella (β = -0.036 points per cm³; 95% CI, -0.061 to -0.010), LF (β = -0.058 points per cm³; 95% CI, -0.076 to -0.039), and LT (β = -0.079 points per cm³; 95% CI, -0.099 to -0.060), along with lower BMELL scores in the LT (β = -0.027 points per cm³; 95% CI, -0.036 to -0.018) and lower lateral meniscus scores (β = -0.054 points per cm³; 95% CI, -0.070 to -0.037). CONCLUSIONS:Larger IPFPVol was associated with greater patellofemoral cartilage thickness and less severe osteoarthritis features in the patellofemoral and lateral tibiofemoral joint. These findings highlight the subregion-specific relationship between IPFP volume, knee cartilage thickness and imaging features of osteoarthritis.
OBJECTIVE:Sleep is a modifiable lifestyle factor potentially related to osteoarthritis (OA), but previous studies have mainly relied on self-reported sleep duration or quality. Using accelerometer-derived data, we examined associations of multidimensional objective sleep characteristics with incident OA. METHOD:We included 61,904 UK Biobank participants who were free of OA at baseline and had accelerometer data. Six objective sleep metrics across five dimensions were derived: sleep quantity (average sleep duration), sleep quality (sleep efficiency), sleep regularity (sleep regularity index and sleep duration variability), sleep timing (sleep midpoint), and circadian rhythm strength (relative amplitude). Cox models examined associations with incident OA. Restricted cubic splines (RCS) and interaction analyses were conducted. RESULTS:Longer average sleep duration (HR 0.93, 95% CI 0.91-0.95), higher sleep efficiency (HR 0.95, 95% CI 0.92-0.97), and stronger relative amplitude (HR 0.93, 95% CI 0.90-0.95) were associated with lower OA risk, whereas delayed sleep midpoint was associated with higher risk (HR 1.08, 95% CI 1.05-1.11; all FDR < 0.001). RCS analyses indicated significant non-linear associations for these four metrics except sleep efficiency. Stronger circadian rhythmicity may attenuate the OA risk associated with delayed sleep midpoint. Associations were broadly consistent for weight-bearing joint OA (hip and knee), but not non-weight-bearing joint (hand) OA. CONCLUSIONS:Delayed sleep timing and weaker circadian rhythm strength were associated with higher incident OA risk, with particularly higher risk observed when delayed sleep timing was accompanied by weaker circadian rhythmicity, extending previous evidence on sleep duration and quality by highlighting sleep timing and circadian rhythmicity.
