Young age and adequate BCG are key factors for optimal BCG treatment efficacy in non-muscle-invasive bladder cancer
Bibliographic record
Abstract
OBJECTIVE: To investigate the impact of ageing on survival outcomes in Bacillus Calmette-Guérin (BCG) treated non-muscle invasive bladder cancer (NMIBC) patients and its synergy with adequate BCG treatment. METHOD: Patients with NMIBC who received BCG treatment from 2001 to 2020 were divided into group 1 (< = 70 years) and group 2 (> 70 years). Overall Survival (OS), Cancer-Specific Survival (CSS), Recurrence-Free Survival (RFS), and Progression-Free Survival (PFS) were analyzed using the Kaplan-Meier method. Multivariable Cox regression analysis was used to adjust potential confounding factors and to estimate Hazard Ratio (HR) and 95% Confidence Interval (CI). Subgroup analysis was performed according to adequate versus inadequate BCG treatment. RESULTS: Overall, 2602 NMIBC patients were included: 1051 (40.4%) and 1551 (59.6%) in groups 1 and 2, respectively. At median follow-up of 11.0 years, group 1 (< = 70 years) was associated with better OS, CSS, and RFS, but not PFS as compared to group 2 (> 70 years). At subgroup analysis, patients in group 1 treated with adequate BCG showed better OS, CSS, RFS, and PFS as compared with inadequate BCG treatment in group 2, while patients in group 2 receiving adequate BCG treatment had 41% less progression than those treated with inadequate BCG from the same group. CONCLUSIONS: Being younger (< = 70 years) was associated with better OS, CSS, and RFS, but not PFS. Older patients (> 70 years) who received adequate BCG treatment had similar PFS as those younger with adequate BCG treatment.
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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 | 0.001 | 0.003 |
| 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".