When Perfect Is the Enemy of Good: Results of a RAND Appropriateness Panel on Treat to Target in Asymptomatic Inflammatory Bowel Disease
Bibliographic record
Abstract
BACKGROUND: A treat-to-target strategy for inflammatory bowel disease (IBD) recommends iterative treatment adjustments to achieve clinical and endoscopic remission. In asymptomatic patients with ongoing endoscopic activity, the risk/benefit balance of this approach is unclear, particularly with prior exposure to advanced therapies. METHODS: Using the RAND/University of California Los Angeles Appropriateness Method, 9 IBD specialists rated appropriateness of changing therapy in 126 scenarios of asymptomatic patients with ulcerative colitis and Crohn's disease and active endoscopic disease. Disease extent and behavior, prior treatment, prior complications, and recent disease progression were considered, as were factors that might influence decision-making, including age and pregnancy. Ratings were collected through anonymous survey, discussed at an in-person meeting, and finalized in a second anonymous survey. RESULTS: Panelists rated change in therapy as appropriate (i.e., expected benefit sufficiently outweighs potential harms from continuing therapy) in 96/126 scenarios, generally in patients with progressive, complicated, and/or extensive disease, while changing therapy was rated uncertain in 27 scenarios of mild and/or stable disease. Changing therapy was rated inappropriate in ulcerative colitis patients with mild and stable disease previously exposed to ≥3 therapies or with improved endoscopic activity, and in Crohn's disease patients with only scattered aphthous ulcers. The validated threshold for disagreement was not crossed for any scenario. Patient age older than 65 years and a plan for pregnancy in the next year might influence decision-making in some settings. DISCUSSION: Appropriateness ratings can help guide clinical decision-making about changing therapy to achieve endoscopic remission in asymptomatic patients with IBD until data from ongoing randomized studies are available.
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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 | 0.022 | 0.059 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".