Implementation of Timeline Reforms Speeds Initiation of National Cancer Institute-Sponsored Trials
Bibliographic record
Abstract
BACKGROUND: The National Cancer Institute (NCI) organized the Operational Efficiency Working Group in 2008 to develop recommendations for improving the speed with which NCI-sponsored clinical trials move from the idea stage to a protocol open to patient enrollment. METHODS: Given the many stakeholders involved, the Operational Efficiency Working Group advised a multifaceted approach to mobilize the entire research community to improve their business processes. New staff positions to monitor progress, protocol-tracking Web sites, and strategically planned conference calls were implemented. NCI staff and clinical teams at Cooperative Groups and Cancer Centers strived to achieve new target timelines but, most important, agreed to abide by absolute deadlines. For phase I-II studies and phase III studies, the target timelines are 7 months and 10 months, whereas the absolute deadlines were set at 18 and 24 months, respectively. Trials not activated by the absolute deadline are automatically disapproved. RESULTS: The initial experience is encouraging and indicates a reduction in development times for phase I-II studies from the historical median of 541 days to a median of 442 days, an 18.3% decrease. The experience with phase III studies to date, although more limited (n = 25), demonstrates a 45.7% decrease in median days. CONCLUSIONS: Based upon this progress, the NCI and the investigator community have agreed to reduce the absolute deadlines to 15 and 18 months for phase I-II and III trials, respectively. Emphasis on initiating trials rapidly is likely to help reduce the time it takes for clinical trial results to reach patients in need of new treatments.
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 | 0.008 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".