The burden of adverse drug reactions reported by patients in the Dutch ADR monitor: a proof of concept.

BACKGROUND: We aimed to describe the burden of adverse drug reactions (ADRs) reported by patients participating in the Dutch ADR Monitor using a multifactorial burden measurement instrument. METHODS: The Dutch ADR Monitor is a cohort event monitoring system that collects information on ADR experiences, including burden. This study includes the initial data (November 2022 until May 2023). Patients were asked if experienced ADRs impacted 7 domains of burden: appearance, medical treatment, daily life, fatigue, physical consequences, mental consequences and the course of ADRs. Burden was scored from 0 to 10 on impacted domains. The distributions of these burden scores were demonstrated in Likert plots. The burden between persistent and recurrent ADRs was compared. RESULTS: 92 patients reported 199 ADRs. Impact on the domains fatigue and daily life were experienced most frequently, except for skin and subcutaneous tissue ADRs, where impact on appearance and mental consequences were experienced most frequently. Fatigue was considered the most burdensome domain. No difference in burden was found between persistent (median = 7, IQR = 4) and recurrent ADRs (median = 6, IQR = 4, p = 0.59). CONCLUSIONS: This is the first study investigating burden of ADRs on 7 domains in patients with chronic diseases. Impact on the domain fatigue was considered most burdensome.

Patients with skin and subcutaneous ADRs experienced impact on appearance and mental consequences most often, but found impact on fatigue most burdensome.For most reported ADRs, patients scored the highest burden on the domain fatigue and thus found impact on this domain to be the most burdensome.Patients with skin and subcutaneous ADRs experienced impact on appearance and mental consequences most often, but found impact on fatigue most burdensome.

Quantification of Longitudinal Patient-Reported Burden of Adverse Drug Reactions Attributed to the Use of TNF-α Inhibitors in inflammatory rheumatic diseases: an observational prospective cohort study.

BACKGROUND: There is a lack of knowledge on patient perspectives on adverse drug reactions (ADRs) attributed to the use of biologics. The aim of this study is to quantify the burden over time of ADRs attributed to TNF-α inhibitors in patients with inflammatory rheumatic diseases (IRDs) and investigate whether the burden over time differs between different types of ADRs. RESEARCH DESIGN AND METHODS: Data were used from the Dutch Biologic Monitor (DBM), an observational prospective cohort study for patient-reported ADRs attributed to biologics. Patients with an IRD using a TNF-α inhibitor reporting an ADR, lasting for three consecutive questionnaires, were included. Questionnaires were sent every two months and burden was scored on a 5-point Likert-type scale. Burden scores were analyzed using linear mixed models. RESULTS: Data from 166 unique patients reporting 274 ADRs were included. The burden score decreased every month by 0.29 points (95% CI -0.34 - -0.24) on average on a 5-point Likert-type scale. The burden score for infections and infestations decreased significantly faster than the burden score for injection site reactions. CONCLUSIONS: Patient-reported burden of ADRs attributed to the use of a TNF-α inhibitor in patients with IRDs decreased significantly over time, especially for infections and infestations.

Methotrexate Polyglutamates Exposure - Response Modeling in a Large Cohort of Rheumatoid Arthritis Patients Starting Methotrexate.

Methotrexate polyglutamates (MTX-PG) concentrations in red blood cells (RBCs) have been suggested as a biomarker of response in patients with rheumatoid arthritis (RA) receiving low-dose MTX therapy. We investigated the association and interpatient variability between RBC-MTX-PG3-5 -exposure and response in patients with RA starting MTX. Data of three prospective cohorts were available. The relationship between exposure and Disease Activity Score in 28 joints (DAS28) was analyzed using a population pharmacokinetic-pharmacodynamic model. Relevant covariates were tested using full covariate modeling and backward elimination. From 395 patients, 3,401 MTX-PG concentrations and 1,337 DAS28 measurements were available between 0 and 300 days after MTX treatment onset. The developed model adequately described the time course of MTX-PG3-5 and DAS28. The median MTX-PG3-5 level at month 1 was 30.9 nmol/L (interquartile range (IQR): 23.6-43.7; n = 41) and at month 3: 69.3 nmol/L (IQR: 17.9-41.2; n = 351). Clearance of MTX-PG3-5 from RBCs was 28% lower (95% confidence interval (CI): 23.6-32.8%) in a woman and 10% lower (95% CI: 7.7-12.4%) in a 65-year-old compared with a 35-year-old patient. MTX-PG3-5 concentrations associated with DAS28: half-maximal effective concentration (EC50 ) was 9.14 nmol/L (95% CI: 4.2 nmol/L-14.1 nmol/L). EF at 80% (EC80 ) above 47 nmol/L was regarded as the optimal response. Independent of the MTX-PG 3-5 - response association, co-administration of disease-modifying antirheumatic drugs and corticosteroids improved response (additive effect on maximum effect (Emax )), whereas smoking, high body mass index and low albumin decreased Emax . In patients with RA starting MTX, RBC-MTX-PG3-5 was associated with clinical response. A dose increase is suggested when MTX-PG3-5 at month 1 is below 9.15 nmol/L, continued with the same dose when the concentration is above 47 nmol/L, and consider other treatment options above 78 nmol/L from 3 months onwards.

Sex differences in adverse drug reactions from Adalimumab and etanercept in patients with inflammatory rheumatic diseases.

BACKGROUND: We examine sex differences in relation to the nature, frequency, and burden of patient-reported adverse drug reactions (ADRs) in patients with inflammatory rheumatic diseases. RESEARCH DESIGN AND METHODS: Rheumatoid arthritis, psoriatic arthritis, or axial spondyloarthritis patients using etanercept or adalimumab from the Dutch Biologic Monitor were sent bimonthly questionnaires concerning experienced ADRs. Sex differences in the proportion and nature of reported ADRs were assessed. Additionally, 5-point Likert-type scales reported for the burden of ADRs, were compared between sexes. RESULTS: In total 748 consecutive patients were included (59% female). From the women 55% reported ≥1 ADR, which was significantly higher than 38% of the men that reported ≥1 ADR (p < 0.001). A total of 882 ADRs were reported comprising 264 distinct ADRs. The nature of the reported ADRs differed significantly between both sexes (p = 0.02). Women in particular reported more injection site reactions than men. The burden of ADRs was similar between sexes. CONCLUSIONS: Sex differences in the frequency and nature of ADRs, but not in ADR burden, exist during treatment with adalimumab and etanercept in patients with inflammatory rheumatic diseases. This should be taken into consideration when investigating and reporting results on ADRs and when counseling patients in daily clinical practice.

Disease-specific ADRs of TNF-α inhibitors as reported by patients with inflammatory rheumatic diseases: a registry-based prospective multicenter cohort study.

BACKGROUND: The extent to which adverse drug reactions (ADRs) of biologics differ per immune-mediated inflammatory disease (IMID), and the relevance of tailoring ADR information per IMID is not fully investigated. We aimed to compare patient-reported ADRs attributed to adalimumab and etanercept between different inflammatory rheumatic diseases (IRDs). RESEARCH DESIGN AND METHODS: ADR reports from IRD patients were extracted from the Dutch Biologic Monitor. ADR frequencies were compared using Fischer-Freeman-Halton exact test and the influence of covariates was assessed using binomial logistic regression.A total, of 729 participants were included, of which 354 participants reported 887 unique ADRs. ADR frequencies were not significantly different between the IRDs. Rheumatoid arthritis and ankylosing spondylitis including axial spondyloarthritis patients had an increased risk of ADRs related to 'Respiratory, thoracic and mediastinal disorders' and as compared to psoriatic arthritis patients. Etanercept use, combination therapy with methotrexate and/or corticosteroids, and age also influenced the risk of reporting specific ADRs. CONCLUSIONS: There were no differences in frequencies and nature of patient-reported ADRs attributed to adalimumab and etanercept between different IRDs. However, more research is needed to align patients' and health-care professionals' perspectives to improve knowledge on disease-specific ADRs.

Analysis and visualization of the course and burden over time of adverse drug reactions (ADRs) attributed to TNFα-inhibitors in patients with inflammatory rheumatic diseases (IRDs).

BACKGROUND: We aimed to investigate course and burden over time of ADRs attributed to TNFα-inhibitors in IRD-patients, and whether Sankey diagrams and polar plots can visualize this. RESEARCH DESIGN AND METHODS: Data on ADRs experienced during the Dutch Biologic Monitor (January 2017 till December 2022) were used in this study. We selected IRD-patients using a TNFα-inhibitor, reporting skin reactions/infections/injection site reactions and completing ≥3 questionnaires (i.e. the initial report and ≥2 follow-ups). Course was scored as worsening/improving/remaining stable/resolving and as (non-)recurrent. Patients scored burden from 1 (no burden) to 5 (very high burden). Sankey diagrams and polar plots visualized this. RESULTS: 202 patients were included, reporting 353 ADRs. Most skin reactions were stable (25.0%). Most infections resolved (50.8%). Injection site reactions were mostly recurrent (72.3%). Skin reactions and infections tended to decrease in burden . Infections had highest burden at start, which mostly decreased over time. Injection site reactions had a low and stable burden. CONCLUSIONS: Skin reactions attributed to TNFα-inhibitors by IRD-patients are stable with a slightly decreasing burden over time. Infections have highest burden at start but resolved mostly. Injection site reactions have a low and stable burden. Sankey diagrams and polar plots are suitable to visualize this.

Development of a multivariate prediction model to identify individual case safety reports which require clinical review.

BACKGROUND: The number of Individual Case Safety Reports (ICSRs) in pharmacovigilance databases are rapidly increasing world-wide. The majority of ICSRs at the Netherlands Pharmacovigilance Centre Lareb is reviewed manually to identify potential signal triggering reports (PSTR) or ICSRs which need further clinical assessment for other reasons. OBJECTIVES: To develop a prediction model to identify ICSRs that require clinical review, including PSTRs. Secondly, to identify the most important features of these reports. METHODS: All ICSRs (n = 30 424) received by Lareb between October 1, 2017 and February 26, 2021 were included. ICSRs originating from marketing authorisation holders and ICSRs reported on vaccines were excluded. The outcome was defined as PSTR (yes/no), where PSTR 'yes' was defined as an ICSR discussed at a signal detection meeting. Nineteen features were included, concerning structured information on: patients, adverse drug reactions (ADR) or drugs. Data were divided into a training (70%) and test set (30%) using a stratified split to maintain the PSTR/no PSTR ratio. Logistic regression, elastic net logistic regression and eXtreme Gradient Boosting models were trained and tuned on a training set. Random down-sampling of negative controls was applied on the training set to adjust for the imbalanced dataset. Final models were evaluated on the test set. Model performances were assessed using the area under the curve (AUC) with 95% confidence interval of a receiver operating characteristic (ROC), and specificity and precision were assessed at a threshold for perfect sensitivity (100%, to not miss any PSTRs). Feature importance plots were inspected and a selection of features was used to re-train and test model performances with fewer features. RESULTS: 1439 (4.7%) of reports were PSTR. All three models performed equally with a highest AUC of 0.75 (0.73-0.77). Despite moderate model performances, specificity (5%) and precision (5%) were low. Most important features were: 'absence of ADR in the Summary of product characteristics', 'ADR reported as serious', 'ADR labelled as an important medical event', 'ADR reported by physician' and 'positive rechallenge'. Model performances were similar when using only nine of the most important features. CONCLUSIONS: We developed a prediction model with moderate performances to identify PSTRs with nine commonly available features. Optimisation of the model using more ICSR information (e.g., free text fields) to increase model precision is required before implementation.

Epigenome wide association study of response to methotrexate in early rheumatoid arthritis patients.

AIM: To identify differentially methylated positions (DMPs) and regions (DMRs) that predict response to Methotrexate (MTX) in early rheumatoid arthritis (RA) patients. MATERIALS AND METHODS: DNA from baseline peripheral blood mononuclear cells was extracted from 72 RA patients. DNA methylation, quantified using the Infinium MethylationEPIC, was assessed in relation to response to MTX (combination) therapy over the first 3 months. RESULTS: Baseline DMPs associated with response were identified; including hits previously described in RA. Additionally, 1309 DMR regions were observed. However, none of these findings were genome-wide significant. Likewise, no specific pathways were related to response, nor could we replicate associations with previously identified DMPs. CONCLUSION: No baseline genome-wide significant differences were identified as biomarker for MTX (combination) therapy response; hence meta-analyses are required.

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 outperform 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 investigate 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. Finally, 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.

Global DNA (hydroxy)methylation is stable over time under several storage conditions and temperatures.

BACKGROUND: Epigenetic markers are often quantified and related to disease in stored samples. While, effects of storage on stability of these markers have not been thoroughly examined. In this longitudinal study, we investigated the influence of storage time, material, temperature, and freeze-thaw cycles on stability of global DNA (hydroxy)methylation. METHODS: EDTA blood was collected from 90 individuals. Blood (n = 30, group 1) and extracted DNA (n = 30, group 2) were stored at 4°C, -20°C and -80°C for 0, 1 (endpoint blood 4°C), 6, 12 or 18 months. Additionally, freeze-thaw cycles of blood and DNA samples (n = 30, group 3) were performed over three days. Global DNA methylation and hydroxymethylation (mean ± SD) were quantified using liquid chromatography-electrospray ionization-tandem mass spectrometry (LC-ESI-MS/MS) with between-run precision of 2.8% (methylation) and 6.3% (hydroxymethylation). Effects on stability were assessed using linear mixed models. RESULTS: global DNA methylation was stable over 18 months in blood at -20°C and -80°C and DNA at 4°C and -80°C. However, at 18 months DNA methylation from DNA stored at -20°C relatively decreased -6.1% compared to baseline. Global DNA hydroxymethylation was more stable in DNA samples compared to blood, independent of temperature (p = 0.0131). Stability of global DNA methylation and hydroxymethylation was not affected up to three freeze - thaw cycles. CONCLUSION: Global DNA methylation and hydroxymethylation stored as blood and DNA can be used for epigenetic studies. The relevance of  small differences occuring during storage depend on the expected effect size and research question.

Identification of Metabolic Biomarkers in Relation to Methotrexate Response in Early Rheumatoid Arthritis.

This study aimed to identify baseline metabolic biomarkers for response to methotrexate (MTX) therapy in rheumatoid arthritis (RA) using an untargeted method. In total, 82 baseline plasma samples (41 insufficient responders and 41 sufficient responders to MTX) were selected from the Treatment in the Rotterdam Early Arthritis Cohort (tREACH, trial number: ISRCTN26791028) based on patients' EULAR response at 3 months. Metabolites were assessed using high-performance liquid chromatography-quadrupole time of flight mass spectrometry. Differences in metabolite concentrations between insufficient and sufficient responders were assessed using partial least square regression discriminant analysis (PLS-DA) and Welch's t-test. The predictive performance of the most significant findings was assessed in a receiver operating characteristic plot with area under the curve (AUC), sensitivity and specificity. Finally, overrepresentation analysis was performed to assess if the best discriminating metabolites were enriched in specific metabolic events. Baseline concentrations of homocystine, taurine, adenosine triphosphate, guanosine diphosphate and uric acid were significantly lower in plasma of insufficient responders versus sufficient responders, while glycolytic intermediates 1,3-/2,3-diphosphoglyceric acid, glycerol-3-phosphate and phosphoenolpyruvate were significantly higher in insufficient responders. Homocystine, glycerol-3-phosphate and 1,3-/2,3-diphosphoglyceric acid were independent predictors and together showed a high AUC of 0.81 (95% CI: 0.72-0.91) for the prediction of insufficient response, with corresponding sensitivity of 0.78 and specificity of 0.76. The Warburg effect, glycolysis and amino acid metabolism were identified as underlying metabolic events playing a role in clinical response to MTX in early RA. New metabolites and potential underlying metabolic events correlating with MTX response in early RA were identified, which warrant validation in external cohorts.

Validation of a Prognostic Multivariable Prediction Model for Insufficient Clinical Response to Methotrexate in Early Rheumatoid Arthritis and Its Clinical Application in Evidencio.

INTRODUCTION: Methotrexate (MTX) constitutes the first-line therapy in rheumatoid arthritis (RA), yet approximately 30% of the patients do not benefit from MTX. Recently, we reported a prognostic multivariable prediction model for insufficient clinical response to MTX at 3 months of treatment in the treatment in the Rotterdam Early Arthritis Cohort (tREACH), including baseline predictors: Disease activity score 28 (DAS28), Health Assessment Questionnaire (HAQ), erythrocyte folate, single-nucleotide polymorphisms (SNPs; ABCB1, ABCC3), smoking, and BMI. The purpose of the current study was (1) to externally validate the model and (2) to enhance the model's clinical applicability. METHODS: Erythrocyte folate and SNPs were assessed in 91 early disease-modifying antirheumatic drug (DMARD)-naïve RA patients starting MTX in the external validation cohort (U-Act-Early). Insufficient response (DAS28 > 3.2) was determined after 3 months and non-response after 6 months of therapy. The previously developed prediction model was considered successfully validated in the U-Act-Early (validation cohort) if the area under the curve (AUC) of the receiver operating characteristic (ROC) was not significantly lower than in the tREACH (derivation cohort). RESULTS: The AUCs in U-Act-Early at three and 6 months were 0.75 (95% CI 0.64-0.85) and 0.71 (95% CI 0.60-0.82) respectively, similar to the tREACH. Baseline DAS28 > 5.1 and HAQ > 0.6 were the strongest predictors. The model was simplified by excluding the SNPs, while still classifying 73% correctly. Furthermore, interaction terms between BMI and HAQ and BMI and erythrocyte folate significantly improved the model increasing correct classification to 75%. Results were successfully implemented in Evidencio online platform assisting clinicians in shared decision-making to intensify treatment when appropriate. CONCLUSIONS: We successfully externally validated our recently reported prediction model for MTX non-response and enhanced its clinical application thus enabling its evaluation in a clinical trial. TRIAL REGISTRATION: The U-Act-Early is registered at ClinicalTrials.gov. number: NCT01034137. tREACH is registered retrospectively at ISRCTN registry, number: ISRCTN26791028 at 23 August 2007.

Higher baseline global leukocyte DNA methylation is associated with MTX non-response in early RA patients.

BACKGROUND: Low-dose methotrexate (MTX) is the first-line therapy in early rheumatoid arthritis (eRA). Up to 40% of eRA patients do not benefit from MTX therapy. MTX has been shown to inhibit one-carbon metabolism, which is involved in the donation of methyl groups. In this study, we investigate baseline global DNA methylation and changes in DNA methylation during treatment in relation to clinical non-response after 3 months of MTX treatment. METHODS: Two hundred ninety-four blood samples were collected from the Treatment in the Rotterdam Early Arthritis Cohort (tREACH, ISRCTN26791028), a multicenter, stratified single-blind clinical trial of eRA patients. Global DNA (hydroxy)methylation was quantified using liquid chromatography-electrospray ionization-tandem mass spectrometry (LC-ESI-MS/MS) and validated with a global DNA LINE-1 methylation technique. MTX response was determined as ΔDAS28. Additionally, patients were stratified into two response groups according to the European League Against Rheumatism (EULAR) response criteria. Associations between global DNA methylation and response were examined using univariate regression models adjusted for baseline DAS28, baseline erythrocyte folate levels, and body mass index (BMI). RESULTS: Higher baseline global DNA methylation was associated with less decrease of DAS28 (ß = 0.15, p = 0.013) and with MTX non-response (OR = 0.010, 95% CI = 0.001-0.188). This result was validated in LINE-1 elements (ß = 0.22, p = 0.026). Changes in global DNA (hydroxy)methylation were not associated with MTX response over 3 months. CONCLUSIONS: These results show that higher baseline global DNA methylation in treatment naïve eRA patients is associated with decreased clinical response after 3 months of treatment of eRA patients and can be further evaluated as a predictor for MTX therapy non-response. TRIAL REGISTRATION: ISRCTN, ISRCTN26791028 , registered 23 August 2007-retrospectively registered.