ArticleTrials2020
Efficacy, safety and cost-effectiveness of a web-based platform delivering the results of a biomarker-based predictive model of biotherapy response for rheumatoid arthritis patients: a protocol for a randomized multicenter single-blind active controlled clinical trial (PREDIRA).
Article in Trials, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04147026 (PRediction mEdical DevIce for Rheumatoid Arthritis), which is not on this map. Cited by 5 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
PRediction mEdical DevIce for Rheumatoid Arthritis: Scale-up of Unique Predictive Online Platform Highly Improving the Quality of Life of Rheumatoid Arthritis' Patient by Personalised and Efficient Biotherapies Prescription
Who cites it
5 citing papers in PubMed, 6 citations in OpenAlex.
- Article
- Tailored therapeutic decision of rheumatoid arthritis using proteomic strategies: how to start and when to stop?Clinical proteomics · 2023Review
- ATRPred: A machine learning based tool for clinical decision making of anti-TNF treatment in rheumatoid arthritis patients.PLoS computational biology · 2022Article
- Big data analyses and individual health profiling in the arena of rheumatic and musculoskeletal diseases (RMDs).Therapeutic advances in musculoskeletal disease · 2022Review
- Predicting clinical response to costimulation blockade in autoimmunity.Immunotherapy advances · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors at 6 institutions in 2 countries.
Funding
Abstract
backgroundRheumatoid arthritis (RA) is one of the leading chronic inflammatory rheumatism. First-line therapy with synthetic disease-modifying antirheumatic drugs (sDMARD) is insufficiently effective in 40% of cases and these patients are treated with biotherapies. The increased use of these drugs each year is becoming a public health issue with considerable economic burden. This cost is 20 times higher than that of sDMARD. However, among patients treated with biotherapies, clinical practice shows that about one third will not respond to the selected drug. In nonresponse cases, practitioners currently have no choice but to perform an empirical switching between different treatments, because no tool capable of predicting the response or nonresponse to these molecules is currently available.
methodsThe study is a prospective, phase III, controlled, multicenter, and randomized, single-blind (patient) clinical trial, including RA patients with a previous failure to anti-TNF therapies. The main objective is the analysis of the clinical and pharmacoeconomic impact after 6 months of treatment. Intervention arm: prescription of biotherapy (rituximab, adalimumab, abatacept) using SinnoTest® software, a prediction software based on proteomic biomarkers. Control arm: prescription of biotherapy based on current practice, without the SinnoTest® software (any biotherapy). In addition, a substudy will be carried out within this trial to generate a biobank and further analyze the proteomic profile of the patients and their modification throughout the study. DISCUSSION: This clinical trial study will be the first validation study of a biotherapy response prediction software, bringing personalized medicine into the management of RA. We expect that the findings from this study will bring several benefits for the patient and the Health Care System.
trial registrationClincalTrials.gov NCT04147026 . Registered on 31 October, 2019.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.