Complex machine-learning algorithms and multivariable logistic regression on par in the prediction of insufficient clinical response to methotrexate in rheumatoid arthritis

The goals of this study were to examine whether machine-learning algorithms outper-form multivariable logistic regression in the prediction of insufficient response to methotrexate (MTX); secondly, to examine which features are essential for correct prediction; and finally, to in-vestigate whether the best performing model specifically identifies insufficient responders to MTX (combination) therapy. The prediction of insufficient response (3-month Disease Activity Score 28-Erythrocyte-sedimentation rate (DAS28-ESR) > 3.2) was assessed using logistic regression, least absolute shrinkage and selection operator (LASSO), random forest, and extreme gradient boosting (XGBoost). The baseline features of 355 rheumatoid arthritis (RA) patients from the “treatment in the Rotterdam Early Arthritis CoHort” (tREACH) and the U-Act-Early trial were combined for analyses. The model performances were compared using area under the curve (AUC) of receiver operating characteristic (ROC) curves, 95% confidence intervals (95% CI), and sensitivity and specificity. Fi-nally, the best performing model following feature selection was tested on 101 RA patients starting tocilizumab (TCZ)-monotherapy. Logistic regression (AUC = 0.77 95% CI: 0.68–0.86) performed as well as LASSO (AUC = 0.76, 95% CI: 0.67–0.85), random forest (AUC = 0.71, 95% CI: 0.61 = 0.81), and XGBoost (AUC = 0.70, 95% CI: 0.61–0.81), yet logistic regression reached the highest sensitivity (81%). The most important features were baseline DAS28 (components). For all algorithms, models with six features performed similarly to those with 16. When applied to the TCZ-monotherapy group, logistic regression’s sensitivity significantly dropped from 83% to 69% (p = 0.03). In the current dataset, logistic regression performed equally well compared to machine-learning algorithms in the prediction of insufficient response to MTX. Models could be reduced to six features, which are more conducive for clinical implementation. Interestingly, the prediction model was specific to MTX (combination) therapy response

Translation of clinical problems in osteoarthritis into pathophysiological research goals

Osteoarthritis (OA) accounts for more disability among the elderly than any other disease and is associated with an increased mortality rate. The prevalence in Europe will rise in the future since this continent has a strongly ageing population and an obesity epidemic; obesity and age both being major risk factors for OA. No adequate therapeutic options, besides joint replacement, are available, although they are greatly needed and should be acquired by adequate research investments. However, the perspective on OA from a researcher's point of view is not always aligned with the perspective of a patient with OA. Researchers base their views on OA mainly on abnormalities in structure and function while patients consider OA as a collection of symptoms. In this viewpoint paper, we discuss the possibility of translating the most important clinical problems into pathophysiological research goals to facilitate the translation from bench to bedside and vice versa. This viewpoint is the outcome of a dialogue within the 'European League Against Rheumatism study group on OA' and People with Arthritis/Rheumatism across Europe (PARE) representatives

Novel Genetic Variants for Cartilage Thickness and Hip Osteoarthritis

Osteoarthritis is one of the most frequent and disabling diseases of the elderly. Only few genetic variants have been identified for osteoarthritis, which is partly due to large phenotype heterogeneity. To reduce heterogeneity, we here examined cartilage thickness, one of the structural components of joint health. We conducted a genome-wide association study of minimal joint space width (mJSW), a proxy for cartilage thickness, in a discovery set of 13,013 participants from five different cohorts and replication in 8,227 individuals from seven independent cohorts. We identified five genome-wide significant (GWS, P≤5·0×10−8) SNPs annotated to four distinct loci. In addition, we found two additional loci that were significantly replicated, but results of combined meta-analysis fell just below the genome wide significance threshold. The four novel associated genetic loci were located in/near TGFA (rs2862851), PIK3R1 (rs10471753), SLBP/FGFR3 (rs2236995), and TREH/DDX6 (rs49654

The ability of systemic biochemical markers to reflect presence, incidence, and progression of early-stage radiographic knee and hip osteoarthritis: Data from CHECK

Objective: To relate systemic biochemical markers of joint metabolism to presence, incidence, and progression of early-stage radiographic knee and/or hip osteoarthritis (OA). Method: The cartilage markers uCTX-II, sCOMP, sPIIANP, and sCS846, bone markers uCTX-I, uNTX-I, sPINP, and sOC, and synovial markers sHA and sPIIINP were assessed by enzyme-linked immunosorbent assay or radioactive immunoassay in baseline samples of CHECK (Cohort Hip and Cohort Knee), a cohort study of early-stage symptomatic knee and/or hip OA. Knee and hip radiographs were obtained at baseline and 5-year follow-up. Presence of OA at baseline was defined as Kellgren and Lawrence (K&L)=1 (maximum observed). Incidence of OA was defined as K&L=0 at baseline and K&L≥1 at 5-year follow-up. Progression of OA was defined as K&L=1 at baseline and K&L≥2 at 5-year follow-up. Results: Data were available for 801 subjects at baseline and for 723 subjects at both baseline and 5-year follow-up. Multiple cartilage and synovial markers showed positive associations with presence and progression of knee and hip OA and with incidence of hip OA, except for negative associations of uCTX-II and sCOMP with incidence of knee OA. uCTX-II and sCOMP showed multiple interactions with other biomarkers in their associations with knee and hip OA. Bone markers were positively associated with presence of radiographic knee OA, but negatively associated with progression of radiographic hip OA. Conclusion: Especially metabolism in cartilage and synovial matrix appear to be of relevance in knee and hip OA. The role of bone metabolism appears to differ between knee and hip OA

Increased interleukin (IL)-7Rα expression in salivary glands of patients with primary Sjögren's syndrome is restricted to T cells and correlates with IL-7 expression, lymphocyte numbers and activity

Objective: To identify interleukin (IL)-7Rα expression in the labial salivary gland (LSG) of patients with primary Sjögren's syndrome (pSS) and non-Sjögren's syndrome sicca (nSS-sicca) and to study its correlation with glandular infl ammation and IL-7 expression. Methods: The presence of infi ltrating immune cells and IL-7Rα cells in infl amed LSG of patients with pSS (n=12) and nSS-sicca controls (n=7) was studied by immunohistochemistry and fl uorescence activated cell sorting analysis upon tissue digestion (n=15 and n=13, respectively). Additionally, the correlations of IL-7Rαcells with hallmark disease parameters of pSS, major infi ltrating infl ammatory cells and IL-7 were assessed. Results: In the LSG of patients with pSS increased numbers of IL-7Rα cells were found as compared with nSS-sicca patients. IL7Rα cells strongly correlated with the lymphocytic focus score, IL-7 expression, the decrease in percentage of IgA plasma cells and numbers of CD3 T cells, CD20 B cells, and CD1a and CD208 myeloid dendritic cells. Analysis of isolated cells from the LSG demonstrated strongly increased percentages of IL-7Rα CD3 T cells in pSS as compared with nSS, showing abundant IL-7Rα expression on both CD4 and CD8 T cells. Other CD45 leucocytes and CD45- tissue cells scarcely expressed IL-7Rα. Percentages of IL-7RαT cells also signifi cantly correlated with glandular infl ammation. Conclusions: This study shows the presence of increased IL-7Rα T cells in the LSG of patients with pSS and their association with the severity of sialadenitis, disease parameters and IL-7 expression. Considering the immunostimulatory ability of IL-7Rα T cells and IL-7, this suggests that IL-7(R)-dependent T cell-driven immune activation plays an important role in infl ammation in pSS