81 research outputs found

    Revisiting the use of remission criteria for rheumatoid arthritis by excluding patient global assessment: An individual meta-analysis of 5792 patients

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    Objectives: To determine the impact of excluding patient global assessment (PGA) from the American College of Rheumatology (ACR)/European League Against Rheumatism (EULAR) Boolean remission criteria, on prediction of radiographic and functional outcome of rheumatoid arthritis (RA). Methods: Meta-analyses using individual patient data from randomised controlled trials testing the efficacy of biological agents on radiographic and functional outcomes at ≄2 years. Remission states were defined by 4 variants of the ACR/EULAR Boolean definition: (i) tender and swollen 28-joint counts (TJC28/SJC28), C reactive protein (CRP, mg/dL) and PGA (0-10=worst) all ≀1 (4V-remission); (ii) the same, except PGA >1 (4V-near-remission); (iii) 3V-remission (i and ii combined; similar to 4V, but without PGA); (iv) non-remission (TJC28 >1 and/or SJC28 >1 and/or CRP >1). The most stringent class achieved at 6 or 12 months was considered. Good radiographic (GRO) and functional outcome (GFO) were defined as no worsening (ie, change in modified total Sharp score (ΔmTSS) ≀0.5 units and ≀0.0 Health Assessment Questionnaire-Disability Index points, respectively, during the second year). The pooled probabilities of GRO and GFO for the different definitions of remission were estimated and compared. Results: Individual patient data (n=5792) from 11 trials were analysed. 4V-remission was achieved by 23% of patients and 4V-near-remission by 19%. The probability of GRO in the 4V-near-remission group was numerically, but non-significantly, lower than that in the 4V-remission (78 vs 81%) and significantly higher than that for non-remission (72%; difference=6%, 95% CI 2% to 10%). Applying 3V-remission could have prevented therapy escalation in 19% of all participants, at the cost of an additional 6.1%, 4.0% and 0.7% of patients having ΔmTSS >0.0, >0.5 and >5 units over 2 years, respectively. The probability of GFO (assessed in 8 trials) in 4V-near-remission (67%, 95% CI 63% to 71%) was significantly lower than in 4V-remission (78%, 74% to 81%) and similar to non-remission (69%, 66% to 72%). Conclusion: 4V-near-remission and 3V-remission have similar validity as the original 4V-remission definition in predicting GRO, despite expected worse prediction of GFO, while potentially reducing the risk of overtreatment. This supports further exploration of 3V-remission as the target for immunosuppressive therapy complemented by patient-oriented targets

    Multi-classifier prediction of knee osteoarthritis progression from incomplete imbalanced longitudinal data

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    Conventional inclusion criteria used in osteoarthritis clinical trials are not very effective in selecting patients who would benefit from a therapy being tested. Typically majority of selected patients show no or limited disease progression during a trial period. As a consequence, the effect of the tested treatment cannot be observed, and the efforts and resources invested in running the trial are not rewarded. This could be avoided, if selection criteria were more predictive of the future disease progression. In this article, we formulated the patient selection problem as a multi-class classification task, with classes based on clinically relevant measures of progression (over a time scale typical for clinical trials). Using data from two long-term knee osteoarthritis studies OAI and CHECK, we tested multiple algorithms and learning process configurations (including multi-classifier approaches, cost-sensitive learning, and feature selection), to identify the best performing machine learning models. We examined the behaviour of the best models, with respect to prediction errors and the impact of used features, to confirm their clinical relevance. We found that the model-based selection outperforms the conventional inclusion criteria, reducing by 20-25% the number of patients who show no progression. This result might lead to more efficient clinical trials.Comment: 22 pages, 12 figures, 10 table

    The impact of patient global assessment in the definition of remission as a predictor of long-term radiographic damage in patients with rheumatoid arthritis: protocol for an individual patient data meta-analysis

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    BACKGROUND: Remission is the target for management of rheumatoid arthritis (RA) and intensification of immunosuppressive therapy is recommended for those that do not achieve this status. Patient global assessment (PGA) is the single patient reported outcome considered in the American College of Rheumatology/European League Against Rheumatism remission criteria, but its use as target has been questioned. The primary aim of this study is to assess whether excluding PGA from the definition of disease remission changes the association of disease remission with long-term radiographic damage and physical function in patients with RA. METHODS: Individual Patient Data Meta-analysis using data from randomized controlled trials of biological and targeted synthetic agents, identified through ClinicalTrials.gov and PubMed. Different remission states will be defined: (i) 4v-remission [tender (TJC28) and swollen 28-joint counts (SJC28) both≀1, C-reactive protein (CRP)≀1 (mg/dl), and PGA≀1 (0-10 scale)], (ii) 4v-near-remission (TJC28≀1, SJC28≀1, CRP≀1, and PGA>1), (iii) non-remission (TJC28>1 or SJC28>1 or CRP>1), all mutually exclusive, and (iv) 3v-remission (TJC28≀1, SJC28≀1, CRP≀1). Likelihood ratios will be used to descriptively compare whether meeting the 3v and 4v-remission criteria in a single visit (at 6 or 12 months) predicts good outcome in the second year (1-2y). Differences in the predictive value of PGA in the definition of remission will be assessed by comparing the three mutually exclusive disease states using logistic regression analysis. Good outcome is defined primarily by radiographic damage (no deterioration in radiographic scores, whatever the instrument used in each trial), and secondarily by functional disability (Health Assessment Questionnaire consistently ≀0.5 and no deterioration), and their combination ("overall good outcome"). Additional analyses will consider longer periods over which to (concurrently) define remission status and outcome (between 1-5y and 1-10y), different cut-offs to define good radiographic outcome (change ≀0.5, ≀3 and ≀5 in radiographic score), sustained remission and the influence of treatment and other clinical factors. DISCUSSION: If 4v-remission and 4v-near-remission are associated with a similar probability of good outcomes, particularly regarding structural damage, the 3v-remission (excluding PGA) could be adopted as the target for immunosuppressive therapy. Patients' perspectives would remain essential, but assessed separately from disease activity, using instruments adequate to guide adjunctive therapies. Systematic review registration: PROSPERO, CRD42017057099

    GaitSmart motion analysis compared to commonly used function outcome measures in the IMI-APPROACH knee osteoarthritis cohort

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    [Abstract] Background: There are multiple measures for assessment of physical function in knee osteoarthritis (OA), but each has its strengths and limitations. The GaitSmartÂź system, which uses inertial measurement units (IMUs), might be a user-friendly and objective method to assess function. This study evaluates the validity and responsiveness of GaitSmartÂź motion analysis as a function measurement in knee OA and compares this to Knee Injury and Osteoarthritis Outcome Score (KOOS), Short Form 36 Health Survey (SF-36), 30s chair stand test, and 40m self-paced walk test. Methods: The 2-year Innovative Medicines Initiative-Applied Public-Private Research enabling OsteoArthritis Clinical Headway (IMI-APPROACH) knee OA cohort was conducted between January 2018 and April 2021. For this study, available baseline and 6 months follow-up data (n = 262) was used. Principal component analysis was used to investigate whether above mentioned function instruments could represent one or more function domains. Subsequently, linear regression was used to explore the association between GaitSmartÂź parameters and those function domains. In addition, standardized response means, effect sizes and t-tests were calculated to evaluate the ability of GaitSmartÂź to differentiate between good and poor general health (based on SF-36). Lastly, the responsiveness of GaitSmartÂź to detect changes in function was determined. Results: KOOS, SF-36, 30s chair test and 40m self-paced walk test were first combined into one function domain (total function). Thereafter, two function domains were substracted related to either performance based (objective function) or self-reported (subjective function) function. Linear regression resulted in the highest R2 for the total function domain: 0.314 (R2 for objective and subjective function were 0.252 and 0.142, respectively.). Furthermore, GaitSmartÂź was able to distinguish a difference in general health status, and is responsive to changes in the different aspects of objective function (Standardized response mean (SRMs) up to 0.74). Conclusion: GaitSmartÂź analysis can reflect performance based and self-reported function and may be of value in the evaluation of function in knee OA. Future studies are warranted to validate whether GaitSmartÂź can be used as clinical outcome measure in OA research and clinical practice

    Baseline clinical characteristics of predicted structural and pain progressors in the IMI-APPROACH knee OA cohort

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    [Abstract] Objectives: To describe the relations between baseline clinical characteristics of the Applied Public-Private Research enabling OsteoArthritis Clinical Headway (IMI-APPROACH) participants and their predicted probabilities for knee osteoarthritis (OA) structural (S) progression and/or pain (P) progression. Methods: Baseline clinical characteristics of the IMI-APPROACH participants were used for this study. Radiographs were evaluated according to Kellgren and Lawrence (K&L grade) and Knee Image Digital Analysis. Knee Injury and Osteoarthritis Outcome Score (KOOS) and Numeric Rating Scale (NRS) were used to evaluate pain. Predicted progression scores for each individual were determined using machine learning models. Pearson correlation coefficients were used to evaluate correlations between scores for predicted progression and baseline characteristics. T-tests and χ2 tests were used to evaluate differences between participants with high versus low progression scores. Results: Participants with high S progressions score were found to have statistically significantly less structural damage compared with participants with low S progression scores (minimum Joint Space Width, minJSW 3.56 mm vs 1.63 mm; p<0.001, K&L grade; p=0.028). Participants with high P progression scores had statistically significantly more pain compared with participants with low P progression scores (KOOS pain 51.71 vs 82.11; p<0.001, NRS pain 6.7 vs 2.4; p<0.001). Conclusions: The baseline minJSW of the IMI-APPROACH participants contradicts the idea that the (predicted) course of knee OA follows a pattern of inertia, where patients who have progressed previously are more likely to display further progression. In contrast, for pain progressors the pattern of inertia seems valid, since participants with high P score already have more pain at baseline compared with participants with a low P score

    Relationship Between Motion, Using the GaitSmartTM System, and Radiographic Knee Osteoarthritis: An Explorative Analysis in the IMI-APPROACH Cohort

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    Multicenter study[Abstract] Objectives: To assess underlying domains measured by GaitSmartTMparameters and whether these are additional to established OA markers including patient reported outcome measures (PROMs) and radiographic parameters, and to evaluate if GaitSmart analysis is related to the presence and severity of radiographic knee OA. Methods: GaitSmart analysis was performed during baseline visits of participants of the APPROACH cohort (n = 297). Principal component analyses (PCA) were performed to explore structure in relationships between GaitSmart parameters alone and in addition to radiographic parameters and PROMs. Logistic and linear regression analyses were performed to analyse the relationship of GaitSmart with the presence (Kellgren and Lawrence grade ≄2 in at least one knee) and severity of radiographic OA (ROA). Results: Two hundred and eighty-four successful GaitSmart analyses were performed. The PCA identified five underlying GaitSmart domains. Radiographic parameters and PROMs formed additional domains indicating that GaitSmart largely measures separate concepts. Several GaitSmart domains were related to the presence of ROA as well as the severity of joint damage in addition to demographics and PROMs with an area under the receiver operating characteristic curve of 0.724 and explained variances (adjusted R2) of 0.107, 0.132 and 0.147 for minimum joint space width, osteophyte area and mean subchondral bone density, respectively. Conclusions: GaitSmart analysis provides additional information over established OA outcomes. GaitSmart parameters are also associated with the presence of ROA and extent of radiographic severity over demographics and PROMS. These results indicate that GaitsmartTM may be an additional outcome measure for the evaluation of OA

    Predicted and actual 2-year structural and pain progression in the IMI-APPROACH knee osteoarthritis cohort

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    ClinicalTrials.gov, https://clinicaltrials.gov, NCT03883568[Abstract] Objectives: The IMI-APPROACH knee osteoarthritis study used machine learning (ML) to predict structural and/or pain progression, expressed by a structural (S) and pain (P) predicted-progression score, to select patients from existing cohorts. This study evaluates the actual 2-year progression within the IMI-APPROACH, in relation to the predicted-progression scores. Methods: Actual structural progression was measured using minimum joint space width (minJSW). Actual pain (progression) was evaluated using the Knee injury and Osteoarthritis Outcomes Score (KOOS) pain questionnaire. Progression was presented as actual change (Δ) after 2 years, and as progression over 2 years based on a per patient fitted regression line using 0, 0.5, 1 and 2-year values. Differences in predicted-progression scores between actual progressors and non-progressors were evaluated. Receiver operating characteristic (ROC) curves were constructed and corresponding area under the curve (AUC) reported. Using Youden's index, optimal cut-offs were chosen to enable evaluation of both predicted-progression scores to identify actual progressors. Results: Actual structural progressors were initially assigned higher S predicted-progression scores compared with structural non-progressors. Likewise, actual pain progressors were assigned higher P predicted-progression scores compared with pain non-progressors. The AUC-ROC for the S predicted-progression score to identify actual structural progressors was poor (0.612 and 0.599 for Δ and regression minJSW, respectively). The AUC-ROC for the P predicted-progression score to identify actual pain progressors were good (0.817 and 0.830 for Δ and regression KOOS pain, respectively). Conclusion: The S and P predicted-progression scores as provided by the ML models developed and used for the selection of IMI-APPROACH patients were to some degree able to distinguish between actual progressors and non-progressors

    Neuropathic Pain in the IMI-APPROACH Knee Osteoarthritis Cohort: Prevalence and Phenotyping

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    The study is registered under clinicaltrials.gov nr: NCT03883568.[Abstract] Objectives: Osteoarthritis (OA) patients with a neuropathic pain (NP) component may represent a specific phenotype. This study compares joint damage, pain and functional disability between knee OA patients with a likely NP component, and those without a likely NP component. Methods: Baseline data from the Innovative Medicines Initiative Applied Public-Private Research enabling OsteoArthritis Clinical Headway knee OA cohort study were used. Patients with a painDETECT score ≄19 (with likely NP component, n=24) were matched on a 1:2 ratio to patients with a painDETECT score ≀12 (without likely NP component), and similar knee and general pain (Knee Injury and Osteoarthritis Outcome Score pain and Short Form 36 pain). Pain, physical function and radiographic joint damage of multiple joints were determined and compared between OA patients with and without a likely NP component. Results: OA patients with painDETECT scores ≄19 had statistically significant less radiographic joint damage (p≀0.04 for Knee Images Digital Analysis parameters and Kellgren and Lawrence grade), but an impaired physical function (p<0.003 for all tests) compared with patients with a painDETECT score ≀12. In addition, more severe pain was found in joints other than the index knee (p≀0.001 for hips and hands), while joint damage throughout the body was not different. Conclusions: OA patients with a likely NP component, as determined with the painDETECT questionnaire, may represent a specific OA phenotype, where local and overall joint damage is not the main cause of pain and disability. Patients with this NP component will likely not benefit from general pain medication and/or disease-modifying OA drug (DMOAD) therapy. Reserved inclusion of these patients in DMOAD trials is advised in the quest for successful OA treatments

    EULAR points to consider for the management of difficult-to-treat rheumatoid arthritis

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    Objective To develop evidence-based European Alliance of Associations for Rheumatology (EULAR) points to consider (PtCs) for the management of difficult-to-treat rheumatoid arthritis (D2T RA). Methods An EULAR Task Force was established comprising 34 individuals: 26 rheumatologists, patient partners and rheumatology experienced health professionals. Two systematic literature reviews addressed clinical questions around diagnostic challenges, and pharmacological and non-pharmacological therapeutic strategies in D2T RA. PtCs were formulated based on the identified evidence and expert opinion. Strength of recommendations (SoR, scale A–D: A typically consistent level 1 studies and D level 5 evidence or inconsistent studies) and level of agreement (LoA, scale 0–10: 0 completely disagree and 10 completely agree) of the PtCs were determined by the Task Force members. Results Two overarching principles and 11 PtCs were defined concerning diagnostic confirmation of RA, evaluation of inflammatory disease activity, pharmacological and non-pharmacological interventions, treatment adherence, functional disability, pain, fatigue, goal setting and self-efficacy and the impact of comorbidities. The SoR varied from level C to level D. The mean LoA with the overarching principles and PtCs was generally high (8.4–9.6). Conclusions These PtCs for D2T RA can serve as a clinical roadmap to support healthcare professionals and patients to deliver holistic management and more personalised pharmacological and non-pharmacological therapeutic strategies. High-quality evidence was scarce. A research agenda was created to guide future research
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