Global Cytopathology-Hematopathology Practice Trends
Bibliographic record
Abstract
OBJECTIVES: Small-volume biopsy-fine-needle aspiration biopsy (FNAB) with or without core biopsy-is in increasing use in diagnosis and management of lymphoma patients. Our objective was to survey the current practice in small-volume biopsy diagnosis of lymphoma, focusing on the interaction among hematopathologists and cytopathologists and the integration of FNAB, core biopsy, and flow cytometry studies at sign-out. METHODS: This study used a cross-sectional survey design employing the RedCap database distributed via nine pathology professional society email listservs. The survey consisted of 25 multiple-choice questions and several free text fields. In total, 128 pathologists participated. RESULTS: Most respondents indicated that FNAB specimens in which lymphoma is a diagnostic consideration (FNAB-L) are seen daily or weekly (68/116; 58.6%). However, most institutions have separate hematopathology and cytopathology services (72/116; 62.1%) with inconsistent communication. When communication occurred, respondents were frequently inclined to reconsider their original diagnoses. Barriers identified included lack of communication, inadequate access to diagnostic studies, no formal subspecialty training, and various opinions regarding FNAB in diagnosing lymphoma. CONCLUSIONS: This survey showed that FNAB-L specimens are common, with a lack of uniformity in how complementary fine-needle aspiration and core biopsy specimens or flow immunophenotyping results are shared across hematopathology and cytopathology services.
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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 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".