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The emerging disciplines of lipidomics and metabolomics show great potential for the discovery of diagnostic biomarkers, but appropriate pre-analytical sample-handling procedures are critical because several analytes are prone to ex vivo distortions during sample collection. To test how the intermediate storage temperature and storage period of plasma samples from K3EDTA whole-blood collection tubes affect analyte concentrations, we assessed samples from non-fasting healthy volunteers (n = 9) for a broad spectrum of metabolites, including lipids and lipid mediators, using a well-established LC-MS-based platform. We used a fold change-based approach as a relative measure of analyte stability to evaluate 489 analytes, employing a combination of targeted LC-MS/MS and LC-HRMS screening. The concentrations of many analytes were found to be reliable, often justifying less strict sample handling; however, certain analytes were unstable, supporting the need for meticulous processing. We make four data-driven recommendations for sample-handling protocols with varying degrees of stringency, based on the maximum number of analytes and the feasibility of routine clinical implementation. These protocols also enable the simple evaluation of biomarker candidates based on their analyte-specific vulnerability to ex vivo distortions. In summary, pre-analytical sample handling has a major effect on the suitability of certain metabolites as biomarkers, including several lipids and lipid mediators. Our sample-handling recommendations will increase the reliability and quality of samples when such metabolites are necessary for routine clinical diagnosis.
Small molecule biomarker discovery: Proposed workflow for LC-MS-based clinical research projects
(2023)
Mass spectrometry focusing on small endogenous molecules has become an integral part of biomarker discovery in the pursuit of an in-depth understanding of the pathophysiology of various diseases, ultimately enabling the application of personalized medicine. While LC-MS methods allow researchers to gather vast amounts of data from hundreds or thousands of samples, the successful execution of a study as part of clinical research also requires knowledge transfer with clinicians, involvement of data scientists, and interactions with various stakeholders.
The initial planning phase of a clinical research project involves specifying the scope and design, and engaging relevant experts from different fields. Enrolling subjects and designing trials rely largely on the overall objective of the study and epidemiological considerations, while proper pre-analytical sample handling has immediate implications on the quality of analytical data. Subsequent LC-MS measurements may be conducted in a targeted, semi-targeted, or non-targeted manner, resulting in datasets of varying size and accuracy. Data processing further enhances the quality of data and is a prerequisite for in-silico analysis. Nowadays, the evaluation of such complex datasets relies on a mix of classical statistics and machine learning applications, in combination with other tools, such as pathway analysis and gene set enrichment. Finally, results must be validated before biomarkers can be used as prognostic or diagnostic decision-making tools. Throughout the study, quality control measures should be employed to enhance the reliability of data and increase confidence in the results.
The aim of this graphical review is to provide an overview of the steps to be taken when conducting an LC-MS-based clinical research project to search for small molecule biomarkers.
Objective: To conduct subset analyses of SPIRIT-P2 (Standard Protocol Items: Recommendations for Interventional Trials, NCT02349295) to investigate the efficacy and safety of ixekizumab versus placebo in three subgroups of patients with active psoriatic arthritis (PsA) according to the concomitant conventional synthetic disease-modifying antirheumatic drug (cDMARD) received: any background cDMARDs (including methotrexate), background methotrexate only
Methods: Patients were randomised to receive placebo, ixekizumab 80 mg every 4 weeks (IXEQ4W) or every 2 weeks (IXEQ2W). Efficacy and safety were assessed when patients were subdivided according to cDMARD use at baseline. Efficacy was evaluated versus placebo at week 24 by the American College of Rheumatology criteria (ACR20/50), achievement of minimal disease activity (MDA) state, DiseaseActivityIndex for PsA (DAPSA), 28-joint DiseaseActivityScore using C reactive protein (DAS28-CRP), HealthAssessmentQuestionnaire-Disability Index and the 36-item Short-Form health survey physical functioning domain.
Results: Regardless of background cDMARD status, ACR20, ACR50 and MDA response rates were significantly higher than placebo with IXEQ4W or IXEQ2W treatment. Similarly, significant improvements were observed relative to placebo for DAS28-CRP and DAPSA across subgroups. Physical function also significantly improved relative to placebo with IXEQ4W treatment regardless of background cDMARD status and with IXEQ2W alone. Percentages of reported treatment emergent adverse events (AEs), serious AEs (including serious infections) and discontinuations due to AEs in each subgroup were comparable to the overall SPIRIT-P2 population.
Conclusion: Ixekizumab was efficacious in patients with active PsA and previous tumour necrosis factor inhibitor (TNFi)inadequate response or TNFi intolerance treated with ixekizumab alone or when added to cDMARDswith subgroup safety profiles that were consistent with that observed in the overall SPIRIT-P2 population.
Objectives: To compare efficacy and safety of ixekizumab (IXE) to adalimumab (ADA) in biological disease-modifying antirheumatic drug-naïve patients with both active psoriatic arthritis (PsA) and skin disease and inadequate response to conventional synthetic disease-modifying antirheumatic drug (csDMARDs).
Methods: Patients with active PsA were randomised (1:1) to approved dosing of IXE or ADA in an open-label, head-to-head, blinded assessor clinical trial. The primary objective was to evaluate whether IXE was superior to ADA at week 24 for simultaneous achievement of a ≥50% improvement from baseline in the American College of Rheumatology criteria (ACR50) and a 100% improvement from baseline in the Psoriasis Area and Severity Index (PASI100). Major secondary objectives, also at week 24, were to evaluate whether IXE was: (1) non-inferior to ADA for achievement of ACR50 and (2) superior to ADA for PASI100 response. Additional PsA, skin, treat-to-target and quality-of-life outcome measures were assessed at week 24.
Results: The primary efficacy endpoint was met (IXE: 36%, ADA: 28%; p=0.036). IXE was non-inferior for ACR50 response (IXE: 51%, ADA: 47%; treatment difference: 3.9%) and superior for PASI100 response (IXE: 60%, ADA: 47%; p=0.001). IXE had greater response versus ADA in additional PsA, skin, nail, treat-to-target and quality-of-life outcomes. Serious adverse events were reported in 8.5% (ADA) and 3.5% (IXE) of patients.
Conclusions: IXE was superior to ADA in achievement of simultaneous improvement of joint and skin disease (ACR50 and PASI100) in patients with PsA and inadequate response to csDMARDs. Safety and tolerability for both biologicals were aligned with established safety profiles.
Implementing an automated monitoring process in a digital, longitudinal observational cohort study
(2021)
Background: Clinical data collection requires correct and complete data sets in order to perform correct statistical analysis and draw valid conclusions. While in randomized clinical trials much effort concentrates on data monitoring, this is rarely the case in observational studies- due to high numbers of cases and often-restricted resources. We have developed a valid and cost-effective monitoring tool, which can substantially contribute to an increased data quality in observational research.
Methods: An automated digital monitoring system for cohort studies developed by the German Rheumatism Research Centre (DRFZ) was tested within the disease register RABBIT-SpA, a longitudinal observational study including patients with axial spondyloarthritis and psoriatic arthritis. Physicians and patients complete electronic case report forms (eCRF) twice a year for up to 10 years. Automatic plausibility checks were implemented to verify all data after entry into the eCRF. To identify conflicts that cannot be found by this approach, all possible conflicts were compiled into a catalog. This “conflict catalog” was used to create queries, which are displayed as part of the eCRF. The proportion of queried eCRFs and responses were analyzed by descriptive methods. For the analysis of responses, the type of conflict was assigned to either a single conflict only (affecting individual items) or a conflict that required the entire eCRF to be queried.
Results: Data from 1883 patients was analyzed. A total of n = 3145 eCRFs submitted between baseline (T0) and T3 (12 months) had conflicts (40–64%). Fifty-six to 100% of the queries regarding eCRFs that were completely missing were answered. A mean of 1.4 to 2.4 single conflicts occurred per eCRF, of which 59–69% were answered. The most common missing values were CRP, ESR, Schober’s test, data on systemic glucocorticoid therapy, and presence of enthesitis.
Conclusion: Providing high data quality in large observational cohort studies is a major challenge, which requires careful monitoring. An automated monitoring process was successfully implemented and well accepted by the study centers. Two thirds of the queries were answered with new data. While conventional manual monitoring is resource-intensive and may itself create new sources of errors, automated processes are a convenient way to augment data quality.
Psoriasis (PsO) is one of the common chronic inflammatory skin diseases. Approximately 3% of the European Caucasian population is affected. Psoriatic arthritis (PsA) is a chronic immune-mediated disease associated with PsO characterized by distinct musculoskeletal inflammation. Due to its heterogeneous clinical manifestations (e.g., oligo- or polyarthritis, enthesitis, dactylitis, and axial inflammation), early diagnosis of PsA is often difficult and delayed. Approximately 30% of PsO patients will develop PsA. The responsible triggers for the transition from PsO only to PsA are currently unclear, and the impacts of different factors (e.g., genetic, environmental) on disease development are currently discussed. There is a high medical need, recently unmet, to specifically detect those patients with an increased risk for the development of clinically evident PsA early to initiate sufficient treatment to inhibit disease progression and avoid structural damage and loss of function or even intercept disease development. Increased neoangiogenesis and enthesial inflammation are hypothesized to be early pathological findings in PsO patients with PsA development. Different disease states describe the transition from PsO to PsA. Two of those phases are of value for early detection of PsA at-risk patients to prevent later development of PsA as changes in biomarker profiles are detectable: the subclinical phase (soluble and imaging biomarkers detectable, no clinical symptoms) and the prodromal phase (imaging biomarkers detectable, unspecific musculoskeletal symptoms such as arthralgia and fatigue). To target the unmet need for early detection of this at-risk population and to identify the subgroup of patients who will transition from PsO to PsA, imaging plays an important role in characterizing patients precisely. Imaging techniques such as ultrasound (US), magnetic resonance imaging (MRI), and computerized tomography (CT) are advanced techniques to detect sensitively inflammatory changes or changes in bone structure. With the use of these techniques, anatomic structures involved in inflammatory processes can be identified. These techniques are complemented by fluorescence optical imaging as a sensitive method for detection of changes in vascularization, especially in longitudinal measures. Moreover, high-resolution peripheral quantitative CT (HR-pQCT) and dynamic contrast-enhanced MRI (DCE-MRI) may give the advantage to identify PsA-related early characteristics in PsO patients reflecting transition phases of the disease.
Assessment of individual therapeutic responses provides valuable information concerning treatment benefits in individual patients. We evaluated individual therapeutic responses as determined by the Disease Activity Score-28 joints critical difference for improvement (DAS28-dcrit) in rheumatoid arthritis (RA) patients treated with intravenous tocilizumab or comparator anti-tumor necrosis factor (TNF) agents. The previously published DAS28-dcrit value [DAS28 decrease (improvement) ≥ 1.8] was retrospectively applied to data from two studies of tocilizumab in RA, the 52-week ACT-iON observational study and the 24-week ADACTA randomized study. Data were compared within (not between) studies. DAS28 was calculated with erythrocyte sedimentation rate as the inflammatory marker. Stability of DAS28-dcrit responses and European League Against Rheumatism (EULAR) good responses was determined by evaluating repeated responses at subsequent timepoints. A logistic regression model was used to calculate p values for differences in response rates between active agents. Patient-reported outcomes (PROs; pain, global health, function, and fatigue) in DAS28-dcrit responder versus non-responder groups were compared with an ANCOVA model. DAS28-dcrit individual response rates were 78.2% in tocilizumab-treated patients and 58.2% in anti-TNF-treated patients at week 52 in the ACT-ion study (p = 0.0001) and 90.1% versus 59.1% at week 24 in the ADACTA study (p < 0.0001). DAS28-dcrit responses showed greater stability over time (up to 52 weeks) than EULAR good responses. For both active treatments, DAS28-dcrit responses were associated with statistically significant improvements in mean PRO values compared with non-responders. The DAS28-dcrit response criterion provides robust assessments of individual responses to RA therapy and may be useful for discriminating between active agents in clinical studies and guiding treat-to-target decisions in daily practice.
Qualitätsstandards (QS) sind messbare Konstrukte, die helfen sollen, Versorgungslücken quantitativ zu erfassen, um langfristig die Versorgungsqualität zu verbessern. Die Assessment of SpondyloArthritis International Society (ASAS) hat kürzlich erstmals internationale QS für das Management von Patient*innen mit axialer Spondyloarthritis (axSpA) konsentiert und veröffentlicht. Die Deutsche Gesellschaft für Rheumatologie (DGRh) hat daraufhin beschlossen, diese Standards durch eine Gruppe von Expert*innen aus unterschiedlichen Versorgungsbereichen zu übersetzen, zu prüfen und ggf. zu übernehmen. Vor diesem Hintergrund wurden erstmals nationale QS für das Management von Patient*innen mit axSpA für Deutschland entwickelt. Hierbei wurde v. a. auf Machbarkeit und Praxisrelevanz geachtet. Letztlich wurden 9 QS definiert, mit denen die Qualität der Versorgung in Deutschland gemessen und verbessert werden kann bzw. soll.
Background: Secukinumab [an interleukin (IL)‐17A inhibitor] has demonstrated significantly higher efficacy vs. etanercept (a tumour necrosis factor inhibitor) and ustekinumab (an IL‐12/23 inhibitor) in patients with moderate‐to‐severe plaque psoriasis.
Objectives: To report 52‐week results from a prespecified analysis of patients with active psoriatic arthritis (PsA) having concomitant moderate‐to‐severe plaque psoriasis from the head‐to‐head EXCEED monotherapy study comparing secukinumab with adalimumab.
Methods: Patients were randomized to receive secukinumab 300 mg via subcutaneous injection at baseline, week 1–4, and then every 4 weeks until week 48 or adalimumab 40 mg via subcutaneous injection every 2 weeks from baseline until week 50. Assessments in patients with concomitant moderate‐to‐severe psoriasis, defined as having affected body surface area > 10% or Psoriasis Area and Severity Index (PASI) ≥ 10 at baseline, included musculoskeletal, skin and quality‐of‐life outcomes. Missing data were handled using multiple imputation.
Results: Of the 853 patients [secukinumab (N = 426), adalimumab (N = 427)], 211 (24·7%) had concomitant moderate‐to‐severe psoriasis [secukinumab (N = 110, 25·8%), adalimumab (N = 101, 23·7%)]. Up to week 50, 5·5% of patients discontinued secukinumab vs.17·8% in the adalimumab group. The proportion of patients who achieved American College of Rheumatology (ACR) 20 response was 76·4% with secukinumab vs. 68·3% with adalimumab (P = 0·175), PASI 100 response was 39·1% vs. 23·8% (P = 0·013), and simultaneous improvement in ACR 50 and PASI 100 response at week 52 was 28·2% vs. 17·7%, respectively (P = 0·06). Secukinumab demonstrated consistently higher responses vs. adalimumab across skin endpoints.
Conclusions: This prespecified analysis in PsA patients with concomitant moderate‐to‐severe plaque psoriasis in the EXCEED study provides further evidence that IL‐17 inhibitors offer a comprehensive biological treatment to manage the concomitant features of psoriasis and PsA.