Small volume biopsy diagnostic yield at initial diagnosis versus recurrence/transformation of follicular lymphoma: A retrospective Cyto‐Heme Interinstitutional Collaborative study
Bibliographic record
Abstract
BACKGROUND: Few studies have evaluated diagnostic yield of small volume biopsies (SVB) for the diagnosis and management of follicular lymphoma (FL). METHODS: The authors performed a multi-institutional retrospective analysis of SVBs including fine-needle aspiration (FNA) and needle core biopsy (NCB) for initial FL diagnosis and suspected recurrence or transformation of FL. A total of 676 workups beginning with SVB were assessed for the mean number of biopsies per workup, the proportion of workups requiring multiple biopsies, and the proportion with a complete diagnosis including grade, on initial biopsy. RESULTS: Compared to workups performed for question transformation/recurrence, those done for initial FL diagnosis were significantly more likely to require multiple biopsies (p < .01), had a higher mean number of biopsies per workup (1.7 vs. 1.1, absolute standardized difference = 1.1), and a lower complete diagnosis rate at initial biopsy (39% vs. 56%). At initial FL diagnosis, NCB +/- FNA was associated with fewer biopsies per workup compared to FNA +/- CB (1.2 vs. 1.9), fewer workups requiring multiple biopsies (23% vs. 83%), and a higher complete diagnosis rate (71% vs. 18%). In contrast, during assessment for transformation/recurrence, NCB and FNA showed a similar mean number of biopsies per workup (1.2 vs. 1.2) and few workups required multiple biopsies (6% vs. 19%). CONCLUSIONS: SVB at initial FL diagnosis often required additional biopsies to establish a complete diagnosis. In contrast, when assessing for transformed/recurrent FL, additional biopsies were generally not obtained regardless of SVB type, suggesting that in these clinical settings SVB may be sufficient for clinical decision-making.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.001 | 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 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".