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

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

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

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

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

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

Correspondence on “Re‐examining remission definitions in rheumatoid arthritis: considering the 28‐Joint Disease Activity Score, C‐reactive protein level and patient global assessment” by Felson et al

International audienc

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

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

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

Reliability and Feasibility of the Self-Administered ISTH-Bleeding Assessment Tool

Introduction  Standardized bleeding assessment tools (BATs), such as the International Society for Thrombosis and Hemostasis (ISTH)-BAT, are screening instruments used during the diagnostic workup of suspected bleeding disorders. A self-administered ISTH-BAT (self-BAT) would enhance screening and save time during an outpatient clinic visit. Aim  This study was aimed to investigate the reliability and feasibility of the self-BAT. Methods  The electronic self-BAT was created from the ISTH-BAT and paper-version of self-BAT and optimized by patients and physicians. Patients with a (suspected) congenital platelet defect (CPD), who had previously undergone physician-administered ISTH-BAT assessment, were invited to complete the self-BAT. Optimal self-BAT cut-off values to detect a bleeding tendency, as defined by the ISTH-BAT, were evaluated by receiver operator characteristic (ROC) curve analysis to reach a sensitivity ≥95%. Reliability was tested by assessing sensitivity, specificity, and intraclass correlation (ICC). Feasibility was evaluated on comprehension and length of self-BAT. Results  Both versions of the BAT were completed by 156 patients. Optimal cut-off values for self-BAT to define a bleeding tendency were found to be identical to those of the ISTH-BAT. Normal/abnormal scores of the ISTH-BAT and self-BAT were agreed in 88.5% (138/156, 95% confidence interval [CI]: 0.83-0.93) of patients. The sensitivity and specificity of the self-BAT to detect a bleeding tendency were 96.9 and 48.1%, respectively. The ICC was 0.73. Self-BAT questions were graded by 96.8% (151/156) as "very easy," "easy," and "satisfactory" and questionnaire length as "exactly right" by 91% (142/156) of patients. Conclusion  In patients with a (suspected) CPD, the self-BAT is sufficiently reliable and feasible to detect a bleeding tendency, which supports its use as a screening tool

Reexamining Remission Definitions in Rheumatoid Arthritis: Considering the 28-joint Disease Activity Score, C-reactive Protein Level, and Patient Global Assessment: Comment on the Article by Felson et Al

International audienc

Reexamining remission definitions in rheumatoid arthritis: Considering the Twenty-Eight–Joint Disease Activity Score, C-reactive protein level, and patient global assessment: Comment on the article by Felson et al

International audienc