Literature DB >> 32867830

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).

Dalifer Freites-Núñez1, Athan Baillet2, Luis Rodriguez-Rodriguez3, Minh Vu Chuong Nguyen2, Isidoro Gonzalez4, Jose Luis Pablos5, Alejandro Balsa6, Monica Vazquez7, Philippe Gaudin2, Benjamín Fernandez-Gutierrez1.   

Abstract

BACKGROUND: Rheumatoid 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.
METHODS: The 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 REGISTRATION: ClincalTrials.gov NCT04147026 . Registered on 31 October, 2019.

Entities:  

Keywords:  Anti-TNFα agents; Personalized medicine; Prediction models; Rheumatoid arthritis

Mesh:

Substances:

Year:  2020        PMID: 32867830      PMCID: PMC7456748          DOI: 10.1186/s13063-020-04683-7

Source DB:  PubMed          Journal:  Trials        ISSN: 1745-6215            Impact factor:   2.279


  31 in total

1.  Akaike's information criterion in generalized estimating equations.

Authors:  W Pan
Journal:  Biometrics       Date:  2001-03       Impact factor: 2.571

Review 2.  Genetic and genomic predictors of anti-TNF response.

Authors:  Rita Prajapati; Darren Plant; Anne Barton
Journal:  Pharmacogenomics       Date:  2011-11       Impact factor: 2.533

Review 3.  Should patients with recent-onset polyarthritis receive aggressive treatment?

Authors:  Bernard Combe
Journal:  Joint Bone Spine       Date:  2004-11       Impact factor: 4.929

4.  Prediction of treatment response to adalimumab: a double-blind placebo-controlled study of circulating microRNA in patients with early rheumatoid arthritis.

Authors:  S B Krintel; C Dehlendorff; M L Hetland; K Hørslev-Petersen; K K Andersen; P Junker; J Pødenphant; T Ellingsen; P Ahlquist; H M Lindegaard; A Linauskas; A Schlemmer; M Y Dam; I Hansen; H C Horn; A Jørgensen; J Raun; C G Ammitzbøll; M Østergaard; K Stengaard-Pedersen; J S Johansen
Journal:  Pharmacogenomics J       Date:  2015-05-05       Impact factor: 3.550

5.  Prealbumin, platelet factor 4 and S100A12 combination at baseline predicts good response to TNF alpha inhibitors in rheumatoid arthritis.

Authors:  Minh Vu Chuong Nguyen; Athan Baillet; Xavier Romand; Candice Trocmé; Anaïs Courtier; Hubert Marotte; Thierry Thomas; Martin Soubrier; Pierre Miossec; Jacques Tébib; Laurent Grange; Bertrand Toussaint; Thierry Lequerré; Olivier Vittecoq; Philippe Gaudin
Journal:  Joint Bone Spine       Date:  2018-06-06       Impact factor: 4.929

6.  Identification of cartilage oligomeric matrix protein as biomarker predicting abatacept response in rheumatoid arthritis patients with insufficient response to a first anti-TNFα treatment.

Authors:  Minh Vu Chuong Nguyen; Annie Adrait; Athan Baillet; Candice Trocmé; Jacques-Eric Gottenberg; Philippe Gaudin
Journal:  Joint Bone Spine       Date:  2018-09-19       Impact factor: 4.929

7.  Contribution of the bone and cartilage/soft tissue components of the joint damage to the level of disability in rheumatoid arthritis patients: a longitudinal study.

Authors:  Lydia Abasolo; Jose Ivorra-Cortes; Leticia Leon; Juan A Jover; Benjamín Fernández-Gutiérrez; Luis Rodriguez-Rodriguez
Journal:  Clin Rheumatol       Date:  2018-10-16       Impact factor: 2.980

8.  Apolipoprotein A-I and platelet factor 4 are biomarkers for infliximab response in rheumatoid arthritis.

Authors:  C Trocmé; H Marotte; A Baillet; B Pallot-Prades; J Garin; L Grange; P Miossec; J Tebib; F Berger; M J Nissen; R Juvin; F Morel; P Gaudin
Journal:  Ann Rheum Dis       Date:  2008-07-29       Impact factor: 19.103

9.  Long term structural effects of combination therapy in patients with early rheumatoid arthritis: five year follow up of a prospective double blind controlled study.

Authors:  J F Maillefert; B Combe; P Goupille; A Cantagrel; M Dougados
Journal:  Ann Rheum Dis       Date:  2003-08       Impact factor: 19.103

10.  Fetuin-A and thyroxin binding globulin predict rituximab response in rheumatoid arthritis patients with insufficient response to anti-TNFα.

Authors:  Minh Vu Chuong Nguyen; Anaïs Courtier; Annie Adrait; Federica Defendi; Yohann Couté; Athan Baillet; Lisa Guigue; Jacques-Eric Gottenberg; Chantal Dumestre-Pérard; Virginie Brun; Philippe Gaudin
Journal:  Clin Rheumatol       Date:  2020-03-24       Impact factor: 2.980

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  3 in total

1.  Predicting clinical response to costimulation blockade in autoimmunity.

Authors:  Natalie M Edner; Chun Jing Wang; Lina Petersone; Lucy S K Walker
Journal:  Immunother Adv       Date:  2020-11-25

Review 2.  Big data analyses and individual health profiling in the arena of rheumatic and musculoskeletal diseases (RMDs).

Authors:  Diederik De Cock; Elena Myasoedova; Daniel Aletaha; Paul Studenic
Journal:  Ther Adv Musculoskelet Dis       Date:  2022-06-30       Impact factor: 3.625

3.  ATRPred: A machine learning based tool for clinical decision making of anti-TNF treatment in rheumatoid arthritis patients.

Authors:  Bodhayan Prasad; Cathy McGeough; Amanda Eakin; Tan Ahmed; Dawn Small; Philip Gardiner; Adrian Pendleton; Gary Wright; Anthony J Bjourson; David S Gibson; Priyank Shukla
Journal:  PLoS Comput Biol       Date:  2022-07-05       Impact factor: 4.779

  3 in total

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