Updated consensus statement on biological agents, specifically tumour necrosis factor alpha (TNF alpha) blocking agents and interleukin-1 receptor antagonist (IL-1ra), for the treatment of rheumatic diseases, 2004
Bibliographic record
Abstract
As in previous years, the consensus group to consider the use of biological agents was constituted by rheumatologists from the Universities of Erlangen, Leiden, and Vienna in Europe in cooperation with other Universities in the USA, Canada, and Europe. Pharmaceutical industry support was obtained from a number of companies, but these institutions had no part in the decisions about the specific programme or about the academic participants at this conference. The perspective of this consensus is from the treating physician’s point of view. The 128 rheumatologists and bioscientists who attended the consensus conference were chosen from a worldwide group of physicians and other scientists from 20 countries with expertise in the use of biological agents for the treatment of rheumatic diseases. The number of attendees and participants were limited so that not everyone who might have been interested could be invited. Additional information has come to light in the past year, corroborating the major positive effect these drugs have had in rheumatoid arthritis (RA) and other rheumatic diseases, as well as further documenting adverse events. Therefore an update of the previous consensus statement1 is appropriate. The consensus statement is annotated to document the credibility of the data supporting it as much as possible. This annotation is that of Shekelle et al2 and is described in appendix 3. As the number of possible references has become so large, sometimes reviews were used and, if they contained category A references, will be referred to as category A evidence. All participants reviewed relevant clinical published articles relating to tumour necrosis factor (TNF) and interleukin (IL)-1 blocking agents. They were given a draft consensus statement and were asked to revise the document in small discussion groups; open discussion of the revisions led to a final document, representing this updated consensus statement.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.051 | 0.067 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.009 | 0.004 |
| Research integrity | 0.013 | 0.013 |
| Insufficient payload (model declined to judge) | 0.010 | 0.012 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".