ClinicalTrials.gov
public full text
Public Domain
Predictability Studies on the Efficacy of TNF-α Inhibitors in Chinese RA From "Real World"
Rheumatoid arthritis (RA) is a chronic and disabling disease. tumor necrosis factor-a(TNF-a) inhibitors have demonstrated an outstanding performance in relieving joint inflammation and retarding bone erosion involved in RA. However, there is still about one-thirds of RA patients had a poor response to TNF α inhibitors. The Investigators hope to discover prediction protein with a domestic genetic background and finally establish prediction system with Chinese characteristics.
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Identification of Genomic Biomarkers for Rheumatoid Arthritis With Late Onset#842200
- Predictors of Response to Tofacitinib Treatment in Rheumatoid Arthritis Patients#1031893
- Abatacept versus tocilizumab for the treatment of rheumatoid arthritis in TNF inhibitor inadequate responders: study protocol of the SUNSTAR randomised controlled open-label superiority trial#1425761
- Safety of TofAcitinib in Routine Care Patients With Rheumatoid Arthritis (STAR-RA)- Cardiovascular Endpoints#1229593
- Study of Tapering and Discontinuing Biological DMARDs in Rheumatoid Arthritis Patients#1369446
Record · ID 1421220
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive