Long-term use of dasatinib in patients with metastatic castration-resistant prostate cancer after receiving the combination of dasatinib and docetaxel
Bibliographic record
Abstract
John C Araujo,1 Geralyn C Trudel,2 Prashni Paliwal3 1Department of Genitourinary Medical Oncology, Division of Cancer Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, USA; 2Bristol-Myers Squibb, Montreal, Quebec, Canada; 3Bristol-Myers Squibb, Wallingford, CT, USA Abstract: Dasatinib is a potent oral tyrosine kinase inhibitor which targets several kinases, including the SRC family kinases. SRC family kinases have been implicated in androgen therapy resistance that often develops in metastatic castration-resistant prostate cancer (mCRPC), which drives the need for non-androgen targeting therapies. This article describes the preclinical rationale for the use of combination dasatinib and docetaxel therapy in mCRPC, and highlights the results of a phase I–II trial in which 46 patients with mCRPC, treated with a regimen of dasatinib and docetaxel, demonstrated improvements in bone scans, high rates of soft tissue responses, and modulation of markers of bone turnover. This brief report discusses in detail follow-up data on two patients who remain alive after >2.5 years on dasatinib single-agent therapy after discontinuing docetaxel treatment. Keywords: case study, dasatinib, docetaxel, prostate cancer, targeted therapy
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 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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 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".