Treatment of BCG failures with intravesical BCG/Interferon: the University of Montreal experience.
Bibliographic record
Abstract
OBJECTIVE: Bacillus Calmette-Guerin (BCG) has shown promise in large scale studies. We assessed recurrence-free survival in patients treated with intravesical BCG/Interferon (IFN) for non-muscle invasive, BCG refractory, transitional cell carcinoma (TCC) of the urinary bladder at our local institution. METHODS: Cancer control data were gathered for patients enrolled in a BCG/Interferon protocol at the University of Montreal. The main inclusion criteria consisted of pathologically proven evidence of intravesical BCG failure, and of complete transurethral resection of latest post BCG recurrence. Induction consisted of eight intravesical BCG/Interferon instillations. Select patients were treated with BCG/Interferon maintenance therapy. RESULTS: Thirteen patients aged from 45 to 81 years (mean: 65) were included. Stages at TCC diagnosis were distributed as follows: 6 (46%) CIS, 3 (23%) Ta, and 4 (31%) T1. Induction BCG consisted of an average of 11 weekly instillations (range 3-24). Prior to BCG/Interferon stage distribution was as follows: 9 (69%) CIS, and 4 (31%) T1. BCG/Interferon maintenance was administered to 5 (38%) patients. Follow-up ranged from 1.5 to 32 months (mean=15, median=12). Recurrence was diagnosed in 5 patients (38%). Recurrence free survival (RFS) at 24 months was 66%. When stratified according to T stage prior to BCG/IFN, patients with CIS fared worse than T1 patients (50% versus 100%). Maintenance had no effect on RFS (75% versus 69%). CONCLUSIONS: Our results corroborate previous BCG/IFN reports. In selected patients, intravesical BCG/IFN offers a valid alternative to definitive therapy.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".