RTCure: list of downloadable deliverables.
| title and desprition
| type |
last update |
Comparison of serologic features of at-risk individuals and recent onset arthritis patients
Compare at-risk individuals with recent-onset/early arthritis patients
RTCure partners have already established well characterized cohorts of recent onset/early arthritis patients such as the TACERA, the Leiden Early Arthritis and the Scottish Early RA (SERA) cohorts, which provide an excellent possibility to compare the clinical, serologic and cellular features of patients who have recently moved into the inflammatory phase of the disease with those of imminent risk of developing the disease. Additional biobanks of recent onset/early arthritis patients from other RTCure partners (MUW, KI) provide valuable information of the serologic features of recent onset/early arthritis patients.
Programme: H2020-EU.3.1.7. - Topic(s): IMI2-2016-09-02
download deliverable
|
Documents, reports |
2020-04-14 |
Optimal participant population(s) for clinical studies of tolerogenic interventions
Definition of the optimal participant population(s) for clinical studies of tolerogenic interventions (UKER and UQ).
The target population is critical for testing tolerogenic therapies and will be a topic for ongoing debate among WP6 members, with input from WPs 1 and 2 in particular.
Programme: H2020-EU.3.1.7. - Topic(s): IMI2-2016-09-02
download deliverable
|
Documents, reports |
2020-04-14 |
Algorithm for predicting the development of arthritis
Establishment of an algorithm for predicting the development of arthritis.
The aim of this part is to develop a risk prediction model for development of RA, which is based on the parameters collected in the at-risk cohorts of the RTCure partners. Many of these cohorts contain longitudinal follow-ups, which allow to evaluate which of the at-risk individuals developed RA and which one remained in the at-risk stage. A particular focus will be drawn on parameters which predict progression to RA in several different cohorts. In addition, additive risk prediction by using several different parameters such as combination of clinical, laboratory and imaging parameters will be addressed.
Programme: H2020-EU.3.1.7. - Topic(s): IMI2-2016-09-02
download deliverable
|
Documents, reports |
2020-04-14 |
Key risk predictors for the transition from the at-risk status to clinical arthritis
Establishment of key risk predictors for the transition from the at-risk status to clinical arthritis (UA or RA).
Core data sets extracted from existing cohorts in the first part of WP2 will be evaluated for their role in predicting the risk to progress from the at-risk state to the clinical state of arthritis (either undifferentiated arthritis or rheumatoid arthritis).
Programme: H2020-EU.3.1.7. - Topic(s): IMI2-2016-09-02
download deliverable
|
Documents, reports |
2020-04-14 |
ARIAA Midterm recruitment report
Clinical trial ARIAA Midterm recruitment report (UKER, BMS)
Programme: H2020-EU.3.1.7. - Topic(s): IMI2-2016-09-02
download deliverable
|
Documents, reports |
2020-04-14 |
Status on ongoing clinical trials in RTCure
Status on ongoing clinical trials in RTCure. Including:
First study subject approvals package (ASCARA, ICosRA, APPIPRA),
All approval package (ICosRA and APIPPRA),
Midterm recruitment report (ICosRA, APIPPRA)
Programme: H2020-EU.3.1.7. - Topic(s): IMI2-2016-09-02
download deliverable
|
Documents, reports |
2020-04-14 |
Arrange thematic workshops in collaboration with the other WPs
Arrange thematic workshops in collaboration with the other WPs. Approximately one every year.
Programme: H2020-EU.3.1.7. - Topic(s): IMI2-2016-09-02
download deliverable
|
Other |
2020-04-14 |
Report on the core data set for characterisation of individuals at-risk for developing RA
Report on the core data set for characterisation of individuals at-risk for developing rheumatoid arthritis.
In this part of WP2 the existing cohorts of individuals at-risk for development of RA from the RTCure partners will be analyzed and compared for their type of data acquisition in order to define an essential core data set for describing the “at-risk†state. This approach will comprise clinical parameters (such for instance the documentation of inflammatory arthralgia), laboratory parameters (such as ultrasensitive C-reactive protein and autoantibody titers against various autoantigens and peptides thereof, citrullinated proteins and other relevant antigenic protein modifications), and other relevant biomarkers (such as autoantibody profiles, protein biomarkers, RNA expression profiles, epigenetic profiles) as well as imaging parameters (such as subclinical synovitis, osteitis or tenosynovitis). Core parameters will be identified, which allow a comprehensive but also feasible description of the nature of the at-risk state in these individuals. In addition, novel more experimental parameters, in particular approaches coming from the immune-phenotyping of T and B cell populations done in WP3 and WP4 will be added to this parameter set, if shown to be relevant for a better characterization of the at-risk state. Importantly, the agreed key parameters will allow for harmonization of patient criteria that can be applied across clinical sites so as to ensure data comparability.
Programme: H2020-EU.3.1.7. - Topic(s): IMI2-2016-09-02
download deliverable
|
Documents, reports |
2020-04-14 |
Build a multidisciplinary task force
Build a multidisciplinary task force with expertise on biology, statistics, database management, including clinicians and ethicists.
Programme: H2020-EU.3.1.7. - Topic(s): IMI2-2016-09-02
download deliverable
|
Websites, patent fillings, videos etc. |
2020-04-14 |
Set up internal and external website with a RTCure logo
Set up external website with a RTCure logo and an internal communication platform where partners can store and share data and information and communicate about publications.
Programme: H2020-EU.3.1.7. - Topic(s): IMI2-2016-09-02
download deliverable
|
Websites, patent fillings, videos etc. |
2020-04-14 |
Screening and analysis of biological and clinical datasets
Screening and analysis of biological and clinical datasets generated within the project. Responsible partners LUMC and Pfizer.
Programme: H2020-EU.3.1.7. - Topic(s): IMI2-2016-09-02
download deliverable
|
Documents, reports |
2020-04-14 |
