Contemporary outcomes and disease burden of high-grade T1 bladder cancer
Bibliographic record
Abstract
INTRODUCTION: High-grade T1 (HGT1) bladder cancer is considered to have high five-year recurrence and progression rates, at 50-70% and 25-50%, respectively; however, contemporary data are lacking. We examined the contemporary outcomes of HGT1 bladder cancer to inform patient counseling, management, and clinical trial design. METHODS: We identified patients aged ≥18 years with a new diagnosis of HGT1 bladder cancer between 2010 and 2022 treated at our institution. Recurrence-free (RFS), progression-free (PFS), and cancer-specific (CSS) survival were estimated using the Kaplan-Meier method. Associations of baseline characteristics with outcomes were evaluated using Cox regression. RESULTS: A total of 213 patients were included, representing 332 cancer occurrences. Median age at diagnosis was 72 (interquartile range [IQR] 65-80) years. Median followup for RFS, PFS, and CSS was 13, 20, and 36 months, respectively. The one-, three-, and five-year event-free rates were 65%, 51%, and 48% for RFS; 85%, 78%, and 72% for PFS; and 99%, 95%, and 95% for CSS. There was a median of 1 (IQR 1-2) recurrence per patient, with a median time to first recurrence of seven months (IQR 4-14) and a median time between recurrences of seven months (IQR 5-18). Larger tumor size was associated with increased risks of recurrence. Receipt of adjuvant intravesical therapy was associated with reduced risks of recurrence and progression. CONCLUSIONS: Contemporary five-year recurrence and progression rates for HGT1 bladder cancer remain high at 53% and 28%, respectively. The disease burden is substantial, with a median time between recurrences of seven months. These results can inform patient counseling, management, and clinical trial design.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".