Synchronous uterine and bladder cancers detected in urine and vaginal samples by cytology
Bibliographic record
Abstract
Novel diagnostics for uterine cancer are urgently needed to reduce the burden of invasive testing for the majority of healthy women with postmenopausal bleeding. We have previously shown that uterine cancer cells can be detected by cytology in urine and vaginal samples with high diagnostic accuracy. Here, we demonstrate its potential to distinguish malignant cells of different aetiologies in the same urogenital biofluid sample according to their distinctive morphology and immunoprofiles. Synchronous tumours of the urogenital tract are uncommon but can cause diagnostic confusion, delays and poor outcomes. A 79-year-old woman presented to accident and emergency with postmenopausal bleeding. Voided urine and Delphi screener-collected vaginal samples were assessed by cytology and immunocytochemistry. Two malignant cell populations with distinct morphology and immunophenotypes consistent with synchronous uterine and urothelial tumours were identified. Subsequent routine diagnostics confirmed concurrent uterine carcinosarcoma and high-grade urothelial carcinoma of the bladder. This case demonstrates that cytology and adjunctive immunocytochemistry can simultaneously identify and phenotype cancers of different aetiologies from a single urogenital biofluid sample. This can help rationalise diagnostic pathways in complex, unusual cases of dual urogenital primaries.
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 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 | 0.000 | 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".