Impact of concomitant carcinoma in situ distribution on non‐muscle‐invasive bladder cancer progression risk
Bibliographic record
Abstract
OBJECTIVE: To assess whether the distribution of concomitant carcinoma in situ (CIS; unifocal or multifocal) with papillary non-muscle-invasive bladder cancer (NMIBC) impacts the risk of progression, as concomitant CIS is an established risk factor for progression in papillary NMIBC and commonly used calculators do not make this distinction. PATIENTS AND METHODS: In this multi-institutional retrospective cohort study from both academic and community hospitals, clinicopathological data were collected from patients with pTa/pT1 NMIBC treated from 2005 to 2022. Unifocal concomitant CIS was defined as CIS present in only one specimen (i.e., papillary disease with CIS at the tumour base or isolated CIS in one specimen). Multifocal concomitant CIS was characterised by CIS in multiple specimens. Progression was defined as the development of muscle-invasive or metastatic disease. Fine-Gray regression was performed to identify progression-associated factors, using all-cause mortality as a competing risk. RESULTS: Among 2923 patients, 383 (13%) progressed over a median (interquartile range) follow-up of 5.1 (3.0-8.5) years. Concomitant CIS was found in 327 patients (11%), with 233 and 94 harbouring unifocal and multifocal CIS, respectively. Recurrent tumours, T1 stage, high-grade disease, multifocal CIS, and multiple tumours were independently associated with increased progression risk (all P < 0.05). Among patients with concomitant CIS, multifocal CIS remained a significant prognosticator (sub-distribution hazard ratio 1.90, 95% confidence interval 1.18-3.05; P = 0.008) adjusting for age, sex, tumour history, stage, grade, number of tumours, tumour diameter, and Bacillus Calmette-Guérin treatment. CONCLUSIONS: Papillary NMIBC progression risk varies with concomitant CIS distribution. Only multifocal concomitant CIS is a risk factor for progression in patients with T1 NMIBC. If validated in further studies, risk calculators should consider including this CIS distinction. Submitting separate specimens at the time of transurethral resection, as recommended by guidelines, should be encouraged.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".