ATIM-09. SUCCESSFUL EXPERIENCE WITH CLINICAL TRIALS FOR HIGH GRADE GLIOMA IN A COMMUNITY SETTING
Bibliographic record
Abstract
The majority of cancer patients in America are treated in community hospitals and prefer to be treated within a familiar setting, yet most clinical trials are conducted at university medical centers. This report demonstrates that clinical trials for brain tumors can be successfully carried out at a comprehensive community cancer center. Our multidisciplinary neuro-oncology program was established in 2010. All high grade glioma patients are discussed at treatment conferences and considered for clinical trials. Patients have access to studies in partnership with NCI cooperative groups, industry sponsored and investigator initiated trials. To facilitate further research, biospecimens from clinical trial participants are acquired within our tissue bank. Nationally, 20% of adults with cancer qualify for a clinical trial, yet only 3–5% consent. Over the last 4 years, we evaluated 58 patients for 8 different high grade glioma treatment trials, with 50% consenting (29/58). Of 19 patients who received at least one dose of study agent, 79% (15/19) completed treatment. Nationally, 30% of patients drop out of a clinical trial, whereas our voluntary withdrawal rate was only 3%. We had a 100% success rate in harvesting specimens for an autologous vaccine trial (DCVax®-L). Upcoming trials include an anti-angiogenic adenoviral vector (GLOBE), a purified retroviral replicating vector (TOCA5), and radiosurgery combined with tumor treatment field (TTF) therapy (METIS). Our experience demonstrates that clinical trials can successfully be carried out in a comprehensive community cancer center. Acquisition of complex neuro-oncology trials, high patient enrollment and retention, effective study management and reporting of quality data indicate our strong overall trial performance. Therefore, research centers in community hospitals can contribute their patient population to the success of multicenter clinical trials. Our patients are retained and enroll locally with minimal financial and travel burden, maintaining personalized care from their existing medical team.
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 | 0.025 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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".