Cytopathologic Detection of Circulating Tumor Cells Using the Isolation by Size of Epithelial Tumor Cell Method
Bibliographic record
Abstract
Detection of circulating tumor cells (CTCs) morphologically may be a promising new approach in clinical oncology. We tested the reliability of a cytomorphologic approach to identify CTCs: 808 blood samples from patients with benign and malignant diseases and healthy volunteers were examined using the isolation by size of epithelial tumor cell (ISET) method. Cells having nonhematologic features (so-called circulating nonhematologic cells [CNHCs]) were classified into 3 categories: CNHCs with malignant features, CNHCs with uncertain malignant features, and CNHCs with benign features. CNHCs were found in 11.1% and 48.9% of patients with nonmalignant and malignant pathologies, respectively (P < .001). CNHCs with malignant features were observed in 5.3% and in 43.1% of patients with nonmalignant and malignant pathologies, respectively. Cytopathologic identification of CTCs using the ISET method represents a promising field for cytopathologists. The possibility of false-positive diagnosis stresses the need for using ancillary methods to improve this approach.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".