Reflex somatic testing for the detection of <i>FGFR</i> alterations in urinary tract carcinomas: A dual-institutional experience
Bibliographic record
Abstract
OBJECTIVE: To describe the prevalence and clinicopathologic associations of FGFR-altered urinary tract carcinomas in institutions incorporating reflex testing. METHODS: Next-generation sequencing was prospectively performed on urinary tract carcinomas for the detection of FGFR1-4 alterations at 2 tertiary care centers (2021-2025), using the Oncomine Comprehensive Assay (OCA) v3 DNA and OCA Plus RNA. Reflex testing was conducted on metastatic and/or advanced (pT3/4) carcinomas. RESULTS: The cohort included 366 patients (239 lower tract carcinomas, 72 upper tract carcinomas, and 55 metastases). Median age was 72.5 years (range, 36-97). Fifty-nine (16.1%) tumors were FGFR-altered. Forty-nine (13.4%) patients with actionable FGFR alterations (33 FGFR3 mutations, 13 FGFR3 fusions, and 3 FGFR2 mutations) were all 55 years or older (P = .097). The prevalence of actionable FGFR alterations was significantly higher in upper vs lower tract carcinomas (23.8% vs 13.8%, P = .007) and in lung metastases vs other metastatic sites (57.1% vs 10.4%, P = .002). A higher frequency was also seen in metastases vs primary tumors (16.4% vs 12.9%), although this difference did not reach statistical significance (P = .482). Actionable FGFR alterations were observed in urothelial carcinoma not otherwise specified (40/261) and in urothelial carcinoma with squamous differentiation (6/43), micropapillary features (2/11), or nested features (2/7). CONCLUSIONS: The detection rate for FGFR1-4 alterations in a real-world, dual-institution cohort of urinary tract carcinomas was reported.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".