Bibliographic record
Abstract
Objectives: 1) To evaluate the quality of randomized clinical trials (RCTs) in rare diseases using Juvenile Idiopathic Arthritis (JIA) as an example, 2) to evaluate the time to treatment response in patients with rheumatic diseases, 3) to evaluate the power of the Randomized Placebo-Phase Design (RPPD) under various response time distributions, and 4) to examine the use of Value of Information (VOI) methodology in the optimal design of clinical trials for rare disease using hemophilia prophylaxis with factor VIII as an example.\n\nMethods. The methods include a systematic review, a secondary analysis of data from an RCT and from a patient registry, a computer simulation study, and an evaluation of hypothetical RCT scenarios with VOI methodology. \n\nResults. The quality of RCTs in JIA based on selected quality indicators was poor with some positive changes over time. In the data sets used for the assessment of hazard distributions, the response times followed mostly generalized gamma or lognormal distributions. The impact of time-to-event distribution on the power of RCTs was assessed in computer simulations. Based on the simulation results, the highest sample sizes were observed for response times following the exponential distribution. In most scenarios, the parallel groups RCT design had higher power than the RPPD. The conclusion of the VOI analyses indicated that at threshold values lower than 400,000 the current evidence supported the use of on-demand therapy. Threshold values higher than 1,000,000 supported the use of tailored or alternate day prophylaxis. At threshold values between 400,000 - 1,000,000 the optimal decision varied from on-demand to prophylaxis therapies.\n \nConclusions. New, more powerful and acceptable designs should be developed for rare diseases. When time-to-event outcomes are used, investigators should use various sources of information to evaluate response time distributions before the new trial is designed, and consider this information in sample size calculation and analysis. VOI methodology should be used in the planning stage of studies to determine the relevant costs and benefits of future research, and to determine the optimal trial parameters that maximize the cost-benefit trade-off.
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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 | 0.424 | 0.645 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.009 | 0.006 |
| Bibliometrics | 0.006 | 0.003 |
| Science and technology studies | 0.001 | 0.006 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.008 | 0.005 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".