Nongynecologic Cytology Practice Patterns: A Survey of Participants in the College of American Pathologists Interlaboratory Comparison Program in Nongynecologic Cytopathology
Bibliographic record
Abstract
CONTEXT: Nongynecologic cytology (NGC) practices are expected to expand relative to gynecologic cytology. The College of American Pathologists attempts to track practice patterns in NGC using a self-reported questionnaire. OBJECTIVE: To analyze self-reported laboratory staffing and practices from a 2010 survey relating to NGC specimens, stains, preparation, procedures, and ancillary testing. DESIGN: The "NGC 2010 Demographics and Supplemental Questionnaire: Current Nongynecologic Practices in Cytopathology Laboratories" was mailed to 2059 laboratories. RESULTS: Survey response rate was 51% (1048 of 2059), predominantly from voluntary, nonprofit hospitals, where NGC samples were reviewed in nontraining settings by pathologists without American Board of Pathology Added Qualification in Cytopathology. Cytotechnologists reviewed NGC cases in 67.4% (675 of 1002) of laboratories. The annual mean and median volumes of NGC cases were 1927 and 858, respectively. Laboratories used more than one method to process NGCs; cell-blocks were most frequently used (930 of 1029; 90.4%) and were created with centrifugation to pellet (538 of 961; 56%). Direct smears were second in preparation frequency; discrete staining was preferred to batch staining. Nongynecologic cytology was used for molecular studies in 34.9% (350 of 1002) of laboratories, most commonly for fluorescent in situ hybridization of urine specimens. Flow cytometric immunophenotyping was performed by 55.9% (554 of 991) and immunohistochemistry by 91.9% (911 of 991) of the responding laboratories. Most laboratories (911 of 993; 91.7%) report specimen completion in 2 or fewer days. Cytohistologic correlation was performed by 71.6% (722 of 1008) of the laboratories both concurrently and retrospectively. CONCLUSION: The various parameters examined in the 2010 survey provide a benchmark for future efforts in quality assurance and process improvement in NGC.
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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 | 0.002 | 0.004 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".