The development of multiple bladder tumour recurrences in relation to the <i>FGFR3</i> mutation status of the primary tumour
Bibliographic record
Abstract
Non-muscle invasive bladder cancers (NMI-BCs) represent 75% of bladder cancers upon presentation. After removal of the primary tumour by transurethral resection, multiple recurrences continue to develop in 70% of patients. Consequently, prolonged and costly surveillance by cystoscopy is required. Mutations in the FGFR3 oncogene are common in NMI-BCs and are associated with a lower chance of progression to muscle-invasive disease. Here we analysed the consistency of FGFR3 mutations in primary and recurrent tumours. This knowledge is of crucial importance if FGFR3 mutation analysis on urinary cells is to be used as an alternative for cystoscopical surveillance. To this end, we monitored the disease process and FGFR3 mutation status of primary and recurrent tumours in 118 patients with NMI-BC. During median follow-up of 8.8 years, these patients underwent 2133 cystoscopies and 80 patients developed 414 recurrences. FGFR3 mutations were equally prevalent in primary and recurrent tumours (63%). Patients can have different types of FGFR3 mutations in different tumours. Recurrence risk was not significantly different for patients with a mutant or wild-type primary tumour. Recurrence rates varied widely between patients but were constant for a patient and were unrelated to FGFR3 status. In the mutant patient group, in contrast to the wild-type group, recurrences continued to develop after 10 years. In 81% of the recurrences of patients with a mutant primary tumour, a mutation was found. Moreover, recurrences in this patient group were of lower stage and grade than those of patients with a wild-type primary tumour (p < 0.001). These results suggest that surveillance by FGFR3 mutation analysis on voided urine in combination with a reduced cystoscopy frequency of patients presenting with an FGFR3 mutant tumour is worth investigating.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".