Efficacy and tolerability of bacillus Calmette-Guérin strain Russia for the treatment of non-muscle-invasive bladder cancer
Bibliographic record
Abstract
INTRODUCTION: Little is known about the efficacy and tolerability of intravesical bacillus Calmette-Guérin (BCG) strain Russia for treatment of non-muscle-invasive bladder cancer (NMIBC) in a middle-European population. METHODS: A prospective collection of outcomes of 101 BCG-naive patients with urothelial bladder carcinoma was carried out between January 2013 and October 2023 at the University Hospital Basel, Basel, Switzerland. Patients underwent BCG (ONCO-BCG-SIIL, Serum Institute of India, Pune, India) induction and a maximum of three maintenance cycles within one year. Adverse events were classified according to the World Health Organization rating scale. RESULTS: One-, three-, and five-year recurrence-free survival (RFS) was 75.9%, 65.6%, and 61.6%, respectively. Tumor recurrence was seen in 31.7% of patients. One-, three-, and five-year progression-free survival (PFS) was 100%, 93.4%, and 93.4%, respectively. Cystectomy rate was 8.9%, with progression to muscle-invasive disease seen in two patients. Adverse events occurred in 72.3% of patients, with adverse events >class II seen in 8.9%. No BCG-related deaths occurred. Early cessation due to side effects resulting in non-adequate BCG therapy was seen in 3% of patients during induction and in 1% during maintenance therapy. CONCLUSIONS: BCG Russia was well-tolerated and resulted in comparable RFS and PFS to historical results of prospective clinical trials with other BCG strains. The use of BCG Russia for adjuvant treatment of papillary NMIBC and therapy of carcinoma in situ of the urinary bladder could help alleviate the BCG shortage.
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 | 0.001 | 0.001 |
| 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 | 0.000 |
| 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".