Clinical Trial Risk in Non-Hodgkin’s Lymphoma: Endpoint and Target Selection
Bibliographic record
Abstract
PURPOSE: To quantify the clinical trial risk of new drug development in Non-Hodgkin's lymphoma (NHL). Risk estimates for this disease have not been reported before. METHODS: We undertook a retrospective review of clinical trials in (NHL) in four subtypes to compare the success rate with the industry average. Our inclusion criteria required that a drug must initiate its phase I trial in one of the four NHL subtypes between 1998 and June 2008 in the US. In addition, clinical trials of new drug candidates that pertain to four subtypes of NHL were retrieved from clinicaltrial.gov. Drug candidates that did not meet these criteria were excluded from the study. RESULTS: The overall success rate (8-11%) was significantly lower than the industry standard (17%). Overall survival (OS) as a secondary outcome appeared more predictive than primary endpoints that were surrogate, of overall success. Further, targeted therapies appear more successful in these lymphoma sub-types than broad acting drugs. CONCLUSION: Clinical trial risk in NHL, with an 89% failure rate reported here, may be reduced by basing decisions on OS secondary endpoints and biologic drugs.
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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 | 0.244 | 0.453 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".