Transitional Cell Carcinoma of the Bladder in Pediatric Patients: Where Do We Stand?
Bibliographic record
Abstract
Abstract Introduction Transitional cell carcinoma of the bladder (TCCB) is uncommon in the pediatric population, and its etiology, natural history and epigenetics remain poorly understood. We aim to describe six cases of TCCB in pediatric patients and discuss the state of the art in the management and follow-up of the patients with this uncommon early presentation. Methods The clinicopathological data of 6 patients with TCCB who underwent transurethral resection of bladder tumor (TURBT) were obtained from our institutional database. The patient data were collected retrospectively. A review of the literature was performed, and the most relevant and trending data were analyzed. Results A total of 6 patients (4 female, 2 male) were treated at our institution between 2004 and 2019. The mean age of the sample was 12 years, and the presenting symptoms were macroscopic hematuria (3 cases), suprapubic pain (2 cases), and 1 case was an incidental finding during pelvic ultrasonography. The long-term follow-up (median follow-up of 61 months) did not reveal recurrence. Conclusion Transitional cell carcinoma of the bladder rarely presents in the pediatric population. Genetic and epigenetic anomalies have been proposed as causes, as well as carcinogenic exposure. The reported cases tend to have a good prognosis, and most are non-invasive at the diagnosis. Follow-up protocols are still lacking, as well as molecular insights on tumor development and prognostic markers.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".