Bibliographic record
Abstract
Active specific immunotherapy (ASI) is a promising approach to treating cancer. Numerous studies in the laboratory have demonstrated that various cancer vaccines can stimulate antibody and cell mediated immune responses against tumour-associated antigens [1-9]. Yet few studies have demonstrated convincing clinical responses. Sialyl-Tn (STn) is a carbohydrate associated with the MUC1 mucin on a number of human cancer cells and is associated with more aggressive disease. Consequently, STn is an ideal candidate for ASI therapy. Theratope vaccine is a cancer vaccine that was designed by Biomira, Inc. (Edmonton, Alberta, Canada) by incorporating a synthetic STn antigen that emulates the carbohydrate seen on human tumours. The clinical trials conducted to date with Theratope vaccine are outlined in this report. Overall, Theratope vaccine has been well-tolerated with minimal toxicity. The most common side effects have been in duration and erythema at the site of injections. Both in a non-transplant setting following low dose iv. cyclophosphamide and high dose autologous transplant setting, there has been a trend toward Theratope vaccine decreasing the risk for relapse, prolonging the time to relapse and thus impacting on overall survival. The definitive Phase III trial comparing the outcome of patients with metastatic breast cancer receiving vaccinations with Theratope vaccine versus vaccination with the nonspecific immune stimulants Keyhole Limpet Hemocyanin (KLH) and Detox -B stable emulsion (Detox-B) (now called Enhanzyn Immunostimulant) was closed to enrolment on March 30, 2001. Over 1000 women with distant metastatic breast cancer were enrolled into the program.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".