Towards Personalized Treatment in Haemophilia: The Role of Genetic Factors in Iron and Heme Control to Identify Patients at Risk for Haemophilic Arthropathy.

The treatment landscape for haemophilia is changing rapidly, creating opportunities for personalized treatment. As major morbidity is still caused by haemophilic arthropathy, understanding the factors affecting joint damage and joint damage progression might lead to more individualized treatment regimens. We investigated the association of HFE mutations or HMOX1 polymorphisms affecting iron/heme handling with radiographic joint damage in 252 haemophilia patients (severe and moderate). Although iron levels and transferrin saturation were significantly increased in the 95 patients with an HFE mutation, neither carrying this mutation nor the HMOX1 polymorphism was associated with radiographic joint damage, and the same was true after adjustment for well-known factors associated with arthropathy. In conclusion, this study does not support the hypothesis that HFE mutations or HMOX1 polymorphisms can be used to predict the development of haemophilic arthropathy.

Myostatin and CXCL11 promote nervous tissue macrophages to maintain osteoarthritis pain.

Pain is the most debilitating symptom of knee osteoarthritis (OA) that can even persist after total knee replacement. The severity and duration of pain do not correlate well with joint tissue alterations, suggesting other mechanisms may drive pain persistence in OA. Previous work identified that macrophages accumulate in the dorsal root ganglia (DRG) containing the somas of sensory neurons innervating the injured knee joint in a mouse OA model and acquire a M1-like phenotype to maintain pain. Here we aimed to unravel the mechanisms that govern DRG macrophage accumulation and programming. The accumulation of F4/80+iNOS+ (M1-like) DRG macrophages was detectable at day 3 after mono-iodoacetate (MIA)-induced OA in the mouse. Depletion of macrophages prior to induction of OA resolved pain-like behaviors by day 7 without affecting the initial development of pain-like behaviors. Analysis of DRG transcript identified CXCL11 and myostatin. CXCL11 and myostatin were increased at 3 weeks post OA induction, with CXCL11 expression partially localized in satellite glial cells and myostatin in sensory neurons. Blocking CXCL11 or myostatin prevented the persistence of OA pain, without affecting the initiation of pain. CXCL11 neutralization reduced the number of total and F4/80+iNOS+ DRG macrophages, whilst myostatin inhibition diminished the programming of F4/80+iNOS+ DRG macrophages. Intrathecal injection of recombinant CXCL11 did not induce pain-associated behaviors. In contrast, intrathecal myostatin increased the number of F4/80+iNOS+ DRG macrophages concurrent with the development of mechanical hypersensitivity that was prevented by macrophages depletion or CXCL11 blockade. Finally, myostatin inhibition during established OA, resolved pain and F4/80+iNOS+ macrophage accumulation in the DRG. In conclusion, DRG macrophages maintain OA pain, but are not required for the induction of OA pain. Myostatin is a key ligand in neuro-immune communication that drives the persistence of pain in OA through nervous tissue macrophages and represent a novel therapeutic target for the treatment of OA pain.

Subclinical synovial proliferation in patients with severe haemophilia A: The value of ultrasound screening and biochemical markers.

AIM: Subclinical bleeding and inflammation play a role in progression of haemophilic arthropathy. Synovial proliferation is predictive of joint bleeding and its early detection may guide treatment changes and prevent arthropathy progression. This study evaluated the prevalence of active and inactive subclinical synovial proliferation and investigated potential biochemical blood/urine markers to identify patients with active subclinical synovial proliferation. METHODS: This cross-sectional study included patients with severe haemophilia A born 1970-2006 who were evaluated during routine clinic visits. Patients with (a history of) inhibitors or recent joint bleeding were excluded. Elbows, knees and ankles were examined for subclinical synovial proliferation by ultrasound and physical examination. Active synovial proliferation was distinguished from inactive synovial proliferation using predefined criteria. Blood/urine biochemical markers (serum osteopontin, sVCAM-1, Coll2-1, COMP, CS846, TIMP, and urinary CTX-II) were compared individually and as combined indexes between patients with and without active synovial proliferation. RESULTS: This cohort consisted of 79 patients with a median age of 31 years (range 16.5-50.8 years) with 62/79 (78%) of the patients using continuous prophylaxis. The annualized joint bleeding rate over the last 5 years was .6 (.2-1.1). Active (17/79, 22%) and inactive subclinical synovial proliferation (17/79, 22%) were both prevalent in this cohort. Biochemical markers were not correlated with active subclinical synovial proliferation. CONCLUSION: Subclinical synovial proliferation, both active and inactive, was prevalent in patients with severe haemophilia A with access to prophylaxis and would be overlooked without routinely performed ultrasounds. Biochemical markers were unable to identify patients with active subclinical synovial proliferation.

Development and validation of a machine learning-supported strategy of patient selection for osteoarthritis clinical trials: the IMI-APPROACH study.

Objectives: To efficiently assess the disease-modifying potential of new osteoarthritis treatments, clinical trials need progression-enriched patient populations. To assess whether the application of machine learning results in patient selection enrichment, we developed a machine learning recruitment strategy targeting progressive patients and validated it in the IMI-APPROACH knee osteoarthritis prospective study. Design: We designed a two-stage recruitment process supported by machine learning models trained to rank candidates by the likelihood of progression. First stage models used data from pre-existing cohorts to select patients for a screening visit. The second stage model used screening data to inform the final inclusion. The effectiveness of this process was evaluated using the actual 24-month progression. Results: From 3500 candidate patients, 433 with knee osteoarthritis were screened, 297 were enrolled, and 247 completed the 2-year follow-up visit. We observed progression related to pain (P, 30%), structure (S, 13%), and combined pain and structure (P â€‹+ â€‹S, 5%), and a proportion of non-progressors (N, 52%) ∼15% lower vs an unenriched population. Our model predicted these outcomes with AUC of 0.86 [95% CI, 0.81-0.90] for pain-related progression and AUC of 0.61 [95% CI, 0.52-0.70] for structure-related progression. Progressors were ranked higher than non-progressors for P â€‹+ â€‹S (median rank 65 vs 143, AUC = 0.75), P (median rank 77 vs 143, AUC = 0.71), and S patients (median rank 107 vs 143, AUC = 0.57). Conclusions: The machine learning-supported recruitment resulted in enriched selection of progressive patients. Further research is needed to improve structural progression prediction and assess this strategy in an interventional trial.

CCR9/CXCR5 Co-Expressing CD4 T Cells Are Increased in Primary Sjögren's Syndrome and Are Enriched in PD-1/ICOS-Expressing Effector T Cells.

Primary Sjögren's syndrome (pSS) is an autoimmune disease characterised by B cell hyperactivity. CXCR5+ follicular helper T cells (Tfh), CXCR5-PD-1hi peripheral helper T cells (Tph) and CCR9+ Tfh-like cells have been implicated in driving B cell hyperactivity in pSS; however, their potential overlap has not been evaluated. Our aim was to study the overlap between the two CXCR5- cell subsets and to study their PD-1/ICOS expression compared to "true" CXCR5/PD-1/ICOS-expressing Tfh cells. CXCR5- Tph and CCR9+ Tfh-like cell populations from peripheral blood mononuclear cells of pSS patients and healthy controls (HC) were compared using flow cytometry. PD-1/ICOS expression from these cell subsets was compared to each other and to CXCR5+ Tfh cells, taking into account their differentiation status. CXCR5- Tph cells and CCR9+ Tfh-like cells, both in pSS patients and HC, showed limited overlap. PD-1/ICOS expression was higher in memory cells expressing CXCR5 or CCR9. However, the highest expression was found in CXCR5/CCR9 co-expressing T cells, which are enriched in the circulation of pSS patients. CXCR5- Tph and CCR9+ Tfh-like cells are two distinct cell populations that both are enriched in pSS patients and can drive B cell hyperactivity in pSS. The known upregulated expression of CCL25 and CXCL13, ligands of CCR9 and CXCR5, at pSS inflammatory sites suggests concerted action to facilitate the migration of CXCR5+CCR9+ T cells, which are characterised by the highest frequencies of PD-1/ICOS-positive cells. Hence, these co-expressing effector T cells may significantly contribute to the ongoing immune responses in pSS.

Identifying multivariate disease trajectories and potential phenotypes of early knee osteoarthritis in the CHECK cohort.

OBJECTIVE: To gain better understanding of osteoarthritis (OA) heterogeneity and its predictors for distinguishing OA phenotypes. This could provide the opportunity to tailor prevention and treatment strategies and thus improve care. DESIGN: Ten year follow-up data from CHECK (1002 early-OA subjects with first general practitioner visit for complaints ≤6 months before inclusion) was used. Data were collected on WOMAC (pain, function, stiffness), quantitative radiographic tibiofemoral (TF) OA characteristics, and semi-quantitative radiographic patellofemoral (PF) OA characteristics. Using functional data analysis, distinctive sets of trajectories were identified for WOMAC, TF and PF characteristics, based on model fit and clinical interpretation. The probabilities of knee membership to each trajectory were used in hierarchical cluster analyses to derive knee OA phenotypes. The number and composition of potential phenotypes was selected again based on model fit (silhouette score) and clinical interpretation. RESULTS: Five trajectories representing different constant levels or changing WOMAC scores were identified. For TF and PF OA, eight and six trajectories respectively were identified based on (changes in) joint space narrowing, osteophytes and sclerosis. Combining the probabilities of knees belonging to these different trajectories resulted in six clusters ('phenotypes') of knees with different degrees of functional (WOMAC) and radiographic (PF) parameters; TF parameters were found not to significantly contribute to clustering. Including baseline characteristics as well resulted in eight clusters of knees, dominated by sex, menopausal status and WOMAC scores, with only limited contribution of PF features. CONCLUSIONS: Several stable and progressive trajectories of OA symptoms and radiographic features were identified, resulting in phenotypes with relatively independent symptomatic and radiographic features. Sex and menopausal status may be especially important when phenotyping knee OA patients, while radiographic features contributed less. Possible phenotypes were identified that, after validation, could aid personalized treatments and patients selection.

Machine-learning predicted and actual 2-year structural progression in the IMI-APPROACH cohort.

In the Innovative Medicine's Initiative Applied Public-Private Research enabling OsteoArthritis Clinical Headway (IMI-APPROACH) knee osteoarthritis (OA) study, machine learning models were trained to predict the probability of structural progression (s-score), predefined as >0.3 mm/year joint space width (JSW) decrease and used as inclusion criterion. The current objective was to evaluate predicted and observed structural progression over 2 years according to different radiographic and magnetic resonance imaging (MRI)-based structural parameters. Radiographs and MRI scans were acquired at baseline and 2-year follow-up. Radiographic (JSW, subchondral bone density, osteophytes), MRI quantitative (cartilage thickness), and MRI semiquantitative [SQ; cartilage damage, bone marrow lesions (BMLs), osteophytes] measurements were obtained. The number of progressors was calculated based on a change exceeding the smallest detectable change (SDC) for quantitative measures or a full SQ-score increase in any feature. Prediction of structural progression based on baseline s-scores and Kellgren-Lawrence (KL) grades was analyzed using logistic regression. Among 237 participants, around 1 in 6 participants was a structural progressor based on the predefined JSW-threshold. The highest progression rate was seen for radiographic bone density (39%), MRI cartilage thickness (38%), and radiographic osteophyte size (35%). Baseline s-scores could only predict JSW progression parameters (most P>0.05), while KL grades could predict progression of most MRI-based and radiographic parameters (P<0.05). In conclusion, between 1/6 and 1/3 of participants showed structural progression during 2-year follow-up. KL scores were observed to outperform the machine-learning-based s-scores as progression predictor. The large amount of data collected, and the wide range of disease stage, can be used for further development of more sensitive and successful (whole joint) prediction models. Trial Registration: Clinicaltrials.gov number NCT03883568.

Structural changes after ankle joint distraction in haemophilic arthropathy: an explorative study investigating biochemical markers and 3D joint space width.

INTRODUCTION: Ankle joint distraction (AJD) is a promising treatment for patients with severe haemophilic ankle arthropathy (HAA). However, some patients showed no clinical improvement after AJD and these differences may be related to structural differences. AIM: Primarily to quantify the structural changes after AJD in patients with HAA by the use of 3D joint space width (JSW) measurements and biochemical markers and secondarily to correlate these findings with clinical pain/function. METHODS: Patients with haemophilia A/B who underwent AJD were included for this study. Bone contours on MRI (performed before and 12 and 36 months after AJD) were drawn manually and percentage change in JSW was calculated. Blood/urine (before and 6, 12, 24 and 36 months after AJD) was collected for biomarker measurement (COMP, CS846, C10C, CALC2, PRO-C2, CTX-II) and combined indexes of markers were calculated. Mixed effects models were used for analyses on group level. Structural changes were compared with clinical parameters. RESULTS: Eight patients were evaluated. On group level, percentage changes in JSW showed a slight decrease after 12 months followed by a non-statistically significant increase in JSW after 36 months compared to baseline. Biochemical marker collagen/cartilage formation also showed an initial decrease, followed by a trend towards net formation 12, 24 and 36 months after AJD. On individual patient level, no clear correlations between structural changes and clinical parameters were observed. CONCLUSION: Cartilage restoration activity on group level in patients with HAA after AJD was in concordance with clinical improvements. Correlating structural modifications with clinical parameters in the individual patient remains difficult.

Quantitative CT of the knee in the IMI-APPROACH osteoarthritis cohort: Association of bone mineral density with radiographic disease severity, meniscal coverage and meniscal extrusion.

OBJECTIVE: Osteoarthritis (OA) is a highly prevalent chronic condition. The subchondral bone plays an important role in onset and progression of OA making it a potential treatment target for disease-modifying therapeutic approaches. However, little is known about changes of periarticular bone mineral density (BMD) in OA and its relation to meniscal coverage and meniscal extrusion at the knee. Thus, the aim of this study was to describe periarticular BMD in the Applied Public-Private Research enabling OsteoArthritis Clinical Headway (APPROACH) cohort at the knee and to analyze the association with structural disease severity, meniscal coverage and meniscal extrusion. DESIGN: Quantitative CT (QCT), MRI and radiographic examinations were acquired in 275 patients with knee osteoarthritis (OA). QCT was used to assess BMD at the femur and tibia, at the cortical bone plate (Cort) and at the epiphysis at three locations: subchondral (Sub), mid-epiphysis (Mid) and adjacent to the physis (Juxta). BMD was evaluated for the medial and lateral compartment separately and for subregions covered and not covered by the meniscus. Radiographs were used to determine the femorotibial angle and were evaluated according to the Kellgren and Lawrence (KL) system. Meniscal extrusion was assessed from 0 to 3. RESULTS: Mean BMD differed significantly between each anatomic location at both the femur and tibia (p < 0.001) in patients with KL0. Tibial regions assumed to be covered with meniscus in patients with KL0 showed lower BMD at Sub (p < 0.001), equivalent BMD at Mid (p = 0.07) and higher BMD at Juxta (p < 0.001) subregions compared to regions not covered with meniscus. Knees with KL2-4 showed lower Sub (p = 0.03), Mid (p = 0.01) and Juxta (p < 0.05) BMD at the medial femur compared to KL0/1. Meniscal extrusion grade 2 and 3 was associated with greater BMD at the tibial Cort (p < 0.001, p = 0.007). Varus malalignment is associated with significant greater BMD at the medial femur and at the medial tibia at all anatomic locations. CONCLUSION: BMD within the epiphyses of the tibia and femur decreases with increasing distance from the articular surface. Knees with structural OA (KL2-4) exhibit greater cortical BMD values at the tibia and lower BMD at the femur at the subchondral level and levels beneath compared to KL0/1. BMD at the tibial cortical bone plate is greater in patients with meniscal extrusion grade 2/3.

Exploring the differences between radiographic joint space width and MRI cartilage thickness changes using data from the IMI-APPROACH cohort.

OBJECTIVE: Longitudinal weight-bearing radiographic joint space width (JSW) and non-weight-bearing MRI-based cartilage thickness changes often show weak correlations. The current objective was to investigate these correlations, and to explore the influence of different factors that could contribute to longitudinal differences between the two methods. METHODS: The current study included 178 participants with medial osteoarthritis (OA) out of the 297 knee OA participants enrolled in the IMI-APPROACH cohort. Changes over 2 years in medial JSW (ΔJSWmed), minimum JSW (ΔJSWmin), and medial femorotibial cartilage thickness (ΔMFTC) were assessed using linear regression, using measurements from radiographs and MRI acquired at baseline, 6 months, and 1 and 2 years. Pearson R correlations were calculated. The influence of cartilage quality (T2 mapping), meniscal extrusion (MOAKS scoring), potential pain-induced unloading (difference in knee-specific pain scores), and increased loading (BMI) on the correlations was analyzed by dividing participants in groups based on each factor separately, and comparing correlations (slope and strength) between groups using linear regression models. RESULT: Correlations between ΔMFTC and ΔJSWmed and ΔJSWmin were statistically significant (p < 0.004) but weak (R < 0.35). Correlations were significantly different between groups based on cartilage quality and on meniscal extrusion: only patients with the lowest T2 values and with meniscal extrusion showed significant moderate correlations. Pain-induced unloading or BMI-induced loading did not influence correlations. CONCLUSIONS: While the amount of loading does not seem to make a difference, weight-bearing radiographic JSW changes are a better reflection of non-weight-bearing MRI cartilage thickness changes in knees with higher quality cartilage and with meniscal extrusion.

Structural tissue damage and 24-month progression of semi-quantitative MRI biomarkers of knee osteoarthritis in the IMI-APPROACH cohort.

BACKGROUND: The IMI-APPROACH cohort is an exploratory, 5-centre, 2-year prospective follow-up study of knee osteoarthritis (OA). Aim was to describe baseline multi-tissue semiquantitative MRI evaluation of index knees and to describe change for different MRI features based on number of subregion-approaches and change in maximum grades over a 24-month period. METHODS: MRIs were acquired using 1.5 T or 3 T MRI systems and assessed using the semi-quantitative MRI OA Knee Scoring (MOAKS) system. MRIs were read at baseline and 24-months for cartilage damage, bone marrow lesions (BML), osteophytes, meniscal damage and extrusion, and Hoffa- and effusion-synovitis. In descriptive fashion, the frequencies of MRI features at baseline and change in these imaging biomarkers over time are presented for the entire sample in a subregional and maximum score approach for most features. Differences between knees without and with structural radiographic (R) OA are analyzed in addition. RESULTS: Two hundred eighty-nine participants had readable baseline MRI examinations. Mean age was 66.6 ± 7.1 years and participants had a mean BMI of 28.1 ± 5.3 kg/m2. The majority (55.3%) of included knees had radiographic OA. Any change in total cartilage MOAKS score was observed in 53.1% considering full-grade changes only, and in 73.9% including full-grade and within-grade changes. Any medial cartilage progression was seen in 23.9% and any lateral progression on 22.1%. While for the medial and lateral compartments numbers of subregions with improvement and worsening of BMLs were very similar, for the PFJ more improvement was observed compared to worsening (15.5% vs. 9.0%). Including within grade changes, the number of knees showing BML worsening increased from 42.2% to 55.6%. While for some features 24-months change was rare, frequency of change was much more common in knees with vs. without ROA (e.g. worsening of total MOAKS score cartilage in 68.4% of ROA knees vs. 36.7% of no-ROA knees, and 60.7% vs. 21.8% for an increase in maximum BML score per knee). CONCLUSIONS: A wide range of MRI-detected structural pathologies was present in the IMI-APPROACH cohort. Baseline prevalence and change of features was substantially more common in the ROA subgroup compared to the knees without ROA. TRIAL REGISTRATION: Clinicaltrials.gov identification: NCT03883568.

TOFA-PREDICT study protocol: a stratification trial to determine key immunological factors predicting tofacitinib efficacy and drug-free remission in psoriatic arthritis (PsA).

INTRODUCTION: Psoriatic arthritis (PsA) is a chronic, inflammatory, musculoskeletal disease that affects up to 30% of patients with psoriasis. Current challenges in clinical care and research include personalised treatment, understanding the divergence of therapy response and unravelling the multifactorial pathophysiology of this complex disease. Moreover, there is an urgent clinical need to predict, assess and understand the cellular and molecular pathways underlying the response to disease-modifying antirheumatic drugs (DMARDs). The TOFA-PREDICT clinical trial addresses this need. Our primary objective is to determine key immunological factors predicting tofacitinib efficacy and drug-free remission in PsA. METHODS AND ANALYSIS: In this investigator-initiated, phase III, multicentre, open-label, four-arm randomised controlled trial, we plan to integrate clinical, molecular and imaging parameters of 160 patients with PsA. DMARD-naïve patients are randomised to methotrexate or tofacitinib. Additionally, patients who are non-responsive to conventional synthetic (cs)DMARDs continue their current csDMARD and are randomised to etanercept or tofacitinib. This results in four arms each with 40 patients. Patients are followed for 1 year. Treatment response is defined as minimal disease activity at week 16. Clinical data, biosamples and images are collected at baseline, 4 weeks and 16 weeks; at treatment failure (treatment switch) and 52 weeks. For the first 80 patients, we will use a systems medicine approach to assess multiomics biomarkers and develop a prediction model for treatment response. Subsequently, data from the second 80 patients will be used for validation. ETHICS AND DISSEMINATION: The study was approved by the Medical Research Ethics Committee in Utrecht, Netherlands, is registered in the European Clinical Trials Database and is carried out in accordance with the Declaration of Helsinki. The study's progress is monitored by Julius Clinical, a science-driven contract research organisation. TRIAL REGISTRATION NUMBER: EudraCT: 2017-003900-28.

Ankle joint distraction is a promising alternative treatment for patients with severe haemophilic ankle arthropathy.

INTRODUCTION: Haemophilic ankle arthropathy (HAA) causes major morbidity. When conservative treatment fails, major surgical interventions are indicated. An alternative treatment to maintain joint mobility and postpone these interventions is desired. AIM: To gather prospective data on clinical/structural changes after ankle joint distraction (AJD) in HAA. METHODS: This study includes patients with severe HAA insufficiently responding to conservative treatment. AJD was performed during 8-10 weeks by use of an external frame. Questionnaires, physical examination and radiology were used to evaluate pain, function and structural changes before and 6, 12, 24 and 36 months after distraction. Mixed effect models were used for analysis. RESULTS: This study includes eight cases (21-53 years). The fixed effects estimates of the visual analogue score (0-10) improved from 7.5 at baseline to 3.4 (p = .023) 3 years after distraction. The Haemophilia Activities List (HAL, 0-100) for basic/complex lower extremities functions improved from respectively 29.6 and 31.5 to 54.3 (p = .015) and 50.7 (p = .031). Joint mobility was maintained. Magnetic resonance imaging (MRI) showed thickened cartilage and reduced bone marrow oedema and subchondral cysts. Pin tract infections (n = 6) were effectively treated and no adverse bleeding events occurred. At 3-year follow-up, in none of the patients the originally indicated arthrodesis was performed. CONCLUSION: This first prospective study showed that AJD in HAA results in decreased pain, improved function and decreased arthropathy-related MRI findings in the majority of patients for prolonged time. Although the study population is small and follow-up is relatively short, AJD may be promising to postpone invalidating interventions and might be a breakthrough treatment.

CCL5 Release by CCR9+ CD8 T Cells: A Potential Contributor to Immunopathology of Primary Sjögren's Syndrome.

Introduction: Increased CCL5 expression and CD8 T cells have been shown to be pivotal regulators of immunopathology in primary Sjögren's syndrome (pSS) and pSS-like disease. Increased CCL5 expression by CCR9+ CD4 T cells has previously been implicated as a contributor to immunopathology in pSS. The role of CD8 T cells and in particular CCR9+ CD8 T cells and their potential to secrete CCL5 has not previously been studied in pSS. In this study we investigated both CCR9 and CCL5 expression by CD8 T cells in pSS patients compared to healthy controls (HC). Methods: CCR9 expression on CD8 T cells from peripheral blood was compared between patients with pSS and HC by flow cytometry. Intracellular CCL5 expression by naive, memory and effector CCR9- and CCR9+ CD8 T cells was assessed. In addition, the capacity and pace of CCL5 release upon T cell activation was determined for all subsets and compared with CD4 T cells. Results: The frequency of circulating CCR9+ CD8 T cells in pSS patients is increased compared to HC. Antigen-experienced CD8 T cells, especially CCR9+ effector CD8 T cells, express the highest CCL5 levels, and release the highest levels of CCL5 upon activation. Memory and effector CD8 T cells of pSS patients express significantly less CCL5 and subsequently release less CCL5 upon stimulation compared to HC. CCR9+ CD8 T cells rapidly release CCL5 and significantly more than CCR9+ CD4 T cells. Conclusion: CCR9+ CD8 T cells express more CCL5 than CCR9- CD8 T cells. CCL5 is rapidly released upon activation, resulting in reduced intracellular expression. Reduced CCL5 expression by an elevated number of antigen-experienced CCR9-expressing CD8 T cells in pSS patients points towards increased release in vivo. This suggests that CCL5 release by CCR9+ CD8 T cells contributes to immunopathology in pSS.

Prediction Aided Tapering In rheumatoid arthritis patients treated with biOlogicals (PATIO): protocol for a randomized controlled trial.

BACKGROUND: Biological disease-modifying anti-rheumatic drugs (bDMARDs) are effective in the treatment of rheumatoid arthritis (RA) but are expensive and increase the risk of infection. Therefore, in patients with a stable low level of disease activity or remission, tapering bDMARDs should be considered. Although tapering does not seem to affect long-term disease control, (short-lived) flares are frequent during the tapering process. We have previously developed and externally validated a dynamic flare prediction model for use as a decision aid during stepwise tapering of bDMARDs to reduce the risk of a flare during this process. METHODS: In this investigator-initiated, multicenter, open-label, randomized (1:1) controlled trial, we will assess the effect of incorporating flare risk predictions into a bDMARD tapering strategy. One hundred sixty RA patients treated with a bDMARD with stable low disease activity will be recruited. In the control group, the bDMARD will be tapered according to "disease activity guided dose optimization" (DGDO). In the intervention group, the bDMARD will be tapered according to a strategy that combines DGDO with the dynamic flare prediction model, where the next bDMARD tapering step is not taken in case of a high risk of flare. Patients will be randomized 1:1 to the control or intervention group. The primary outcome is the number of flares per patient (DAS28-CRP increase > 1.2, or DAS28-CRP increase > 0.6 with a current DAS28-CRP ≥ 2.9) during the 18-month follow-up period. Secondary outcomes include the number of patients with a major flare (flare duration ≥ 12 weeks), bDMARD dose reduction, adverse events, disease activity (DAS28-CRP) and patient-reported outcomes such as quality of life and functional disability. Health Care Utilization and Work Productivity will also be assessed. DISCUSSION: This will be the first clinical trial to evaluate the benefit of applying a dynamic flare prediction model as a decision aid during bDMARD tapering. Reducing the risk of flaring during tapering may enhance the safety and (cost)effectiveness of bDMARD treatment. Furthermore, this study pioneers the field of implementing predictive algorithms in clinical practice. TRIAL REGISTRATION: Dutch Trial Register number NL9798, registered 18 October 2021, https://www.trialregister.nl/trial/9798 . The study has received ethical review board approval (number NL74537.041.20).

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

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. TRIAL REGISTRATION: ClinicalTrials.gov, https://clinicaltrials.gov, NCT03883568.

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

BACKGROUND: There are multiple measures for assessment of physical function in knee osteoarthritis (OA), but each has its strengths and limitations. The GaitSmart® 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 GaitSmart® 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 GaitSmart® parameters and those function domains. In addition, standardized response means, effect sizes and t-tests were calculated to evaluate the ability of GaitSmart® to differentiate between good and poor general health (based on SF-36). Lastly, the responsiveness of GaitSmart® 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, GaitSmart® 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: GaitSmart® 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 GaitSmart® can be used as clinical outcome measure in OA research and clinical practice.

Using real-world data to dynamically predict flares during tapering of biological DMARDs in rheumatoid arthritis: development, validation, and potential impact of prediction-aided decisions.

BACKGROUND: Biological disease-modifying antirheumatic drugs (bDMARDs) are effective in the treatment of rheumatoid arthritis. However, as bDMARDs may also lead to adverse events and are expensive, tapering them is of great clinical interest. Tapering according to disease activity-guided dose optimization (DGDO) does not seem to affect long term remission rates, but flares are frequent during this process. Our objective was to develop a model for the prediction of flares during bDMARD tapering using data from routine care and to evaluate its potential clinical impact. METHODS: We used a joint latent class model to repeatedly predict the probability of a flare occurring within the next 3 months. The model was developed using longitudinal data on disease activity (DAS28) and other routine care data from two clinics. Predictive accuracy was assessed in cross-validation and external validation was performed with data from the DRESS (Dose REduction Strategy of Subcutaneous tumor necrosis factor inhibitors) trial. Additionally, we simulated the reduction in number of flares and bDMARD dose when implementing the model as a decision aid during bDMARD tapering in the DRESS trial. RESULTS: Data from 279 bDMARD courses were used for model development. The final model included two latent DAS28-trajectories, bDMARD type and dose, disease duration, and seropositivity. The area under the curve of the final model was 0.76 (0.69-0.83) in cross-validation and 0.68 (0.62-0.73) in external validation. In simulation of prediction-aided decisions, the mean number of flares over 18 months decreased from 1.21 (0.99-1.43) to 0.75 (0.54-0.96). The reduction in he bDMARD dose was mostly maintained, increasing from 54 to 64% of full dose. CONCLUSIONS: We developed a dynamic flare prediction model, exclusively based on data typically available in routine care. Our results show that using this model to aid decisions during bDMARD tapering may significantly reduce the number of flares while maintaining most of the bDMARD dose reduction. TRIAL REGISTRATION: The clinical impact of the prediction model is currently under investigation in the PATIO randomized controlled trial (Dutch Trial Register number NL9798).

Classification of rheumatoid arthritis into active or inactive with a modified Disease Activity score, for future use as a treat-to-target tool, with a HandScan score replacing joint counts.

OBJECTIVES: To establish the value of a modified Disease Activity score with Optical Spectral Transmission score (DAS-OST) without joint counts but with a HandScan score, versus that of DAS28, to classify rheumatoid arthritis (RA) as active versus inactive, with as reference standard the rheumatologist's clinical classification. METHODS: RA patients with at least one HandScan and DAS28 measurement performed at the same visit were included. Data was extracted from medical records, as was the clinical interpretation as active or inactive RA by the rheumatologist. Logistic regression analyses were performed to calculate areas under the receiver operating characteristics (AU-ROC) curves. The clinical interpretation was used as reference standard in all analyses, and disease activity measures were used as predictor variables. The performance of predictor variables (AU-ROCs) was compared. RESULTS: The data of 1505 RA patients were used for analyses. The highest AU-ROC of 0.88 (95%CI 0.85-0.90) was shown for DAS28; AU-ROC of DAS-OST was 0.78 (95%CI 0.75-0.81), difference 0.10, p<0.01. CONCLUSIONS: Compared to DAS28, DAS-OST classified RA statistically significantly less well as active versus inactive, when using the clinical classification as reference standard. However, a DAS-modification without joint scores might have a place in strategies limiting routine outpatients' visits to the rheumatologist.

Efficacy of Tocilizumab Monotherapy Versus Tocilizumab and Methotrexate Combination Therapy in the Prevention of Radiographic Progression in Rheumatoid Arthritis: An Analysis Using Individual Patient Data From Multiple Clinical Trials.

OBJECTIVE: To compare the effects of preventing radiographic progression (in its 3 components) of tocilizumab (TCZ) monotherapy with those of TCZ and methotrexate (MTX) in combination therapy (TCZ + MTX), and to evaluate possible effect modifiers in this model. METHODS: Randomized trials that compared TCZ monotherapy to TCZ + MTX combination therapy for differences in radiographic progression were analyzed on an individual patient data level using mixed-effects models, and data were collected from 820 subjects with either early rheumatoid arthritis (RA) or established RA. Outcomes were classified as the absence of radiographic progression after 2 years (i.e., preventing radiographic progression) as measured by total Sharp/van der Heijde score (SHS), erosion score, and joint space narrowing (JSN) score. Effect modification by baseline joint damage, disease duration, and Disease Activity Score in 28 joints (DAS28) was studied. RESULTS: Overall, TCZ + MTX combination therapy was more effective in preventing radiographic progression compared to TCZ monotherapy, which was measured by total SHS score. However, in patients with early RA who had more joint damage compared to those with less joint damage at baseline (relative risk [RR] 1.02 versus RR 0.91, respectively) or in patients with a lower DAS28 score compared to those with a higher DAS28 score (RR 1.04 versus RR 0.92, respectively) at baseline, this advantage disappeared. In patients with established RA, the advantage of TCZ + MTX versus TCZ alone in the prevention of radiographic progression disappeared with a longer disease duration at baseline (RR 1.04 versus 0.83). Results of erosion scores as an outcome were in line with these findings, though findings for JSN scores were less clear. CONCLUSION: Combination therapy with TCZ + MTX is more effective in preventing radiographic progression compared to TCZ monotherapy, but the effectiveness of TCZ monotherapy may approximate the effectiveness of TCZ + MTX in patients with early RA who have more joint damage and/or a lower DAS28 at baseline and in patients with established RA who have longer disease duration.