Advancing Clinical Trial Design for Non-Muscle Invasive Bladder Cancer
Bibliographic record
Abstract
BACKGROUND: Despite recent drug development for non-muscle invasive bladder cancer (NMIBC), few therapies have been approved by the US Food and Drug Administration (FDA), and there remains an unmet clinical need. Bacillus Calmette-Guerin (BCG) supply issues underscore the importance of developing safe and effective drugs for NMIBC. OBJECTIVE: On November 18-19, 2021, the FDA held a public virtual workshop to discuss NMIBC research needs and potential trial designs for future development of effective therapies. METHODS: Representatives from various disciplines including urologists, oncologists, pathologists, statisticians, basic and translational scientists, and the patient advocacy community participated. The workshop format included invited lectures, panel discussions, and opportunity for audience discussion and comment. RESULTS: In a pre-workshop survey, 92% of urologists surveyed considered the development of alternatives to BCG as a high drug development priority for BCG-naïve high-risk patients. Key topics discussed included definitions of disease states; trial design for BCG-naïve NMIBC, BCG-unresponsive carcinoma in situ, and BCG-unresponsive papillary carcinoma; strengths and limitations of single-arm trial designs; assessing patient-reported outcomes; and considerations for assessing avoidance of cystectomy as an efficacy measure. CONCLUSIONS: The workshop discussed several important opportunities for trial design refinement in NMIBC. FDA encourages sponsors to meet with the appropriate review division to discuss trial design proposals for NMIBC early in drug development.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".