A proposal for cellularity assessment for EGFR mutational analysis with a correlation with DNA yield and evaluation of the number of sections obtained from cell blocks for immunohistochemistry in non-small cell lung carcinoma
Bibliographic record
Abstract
AIMS: Different approaches have been described for reporting specimen adequacy for epidermal growth factor receptor (EGFR) mutation analysis. We aimed: (1) to conduct cellularity assessment and to investigate its association with DNA yield, (2) to compare the H&E slides taken before and after the thick sections (curls) obtained for EGFR testing and (3) to evaluate the number of ancillary studies performed. METHODS: Cell block (CB) slides of 110 non-small cell lung carcinoma cases submitted to EGFR analysis from 2010 to 2012 were reviewed for total cellularity (ranges 1-100, 100-250, 250-500, 500-750, 750-1000 and >1000 cells), tumour cellularity (ranges 1-50, 50-100, 100-300 and >300 cells) and the percentage of tumour cells. Precurl and postcurl H&E slides were compared using the three criteria. The number of immunohistochemistry (IHC) markers and special stains and DNA yield were recorded. RESULTS: DNA yield was significantly associated with the total cellularity, number and percentage of tumour cells. For 46 cases with precurl and postcurl slides, only three (6.5%) were classified as being different and in two of them the postcurl slide had greater cellularity than the precurl. IHC was performed in 83 cases, with a minimum of 1 and a maximum of 11 markers (median of 3) per case. CONCLUSIONS: An association between the total cellularity and the tumour cellularity with the DNA yield was demonstrated using the ranges described. Evaluation of a postcurl slide is an unnecessary practice. The majority of the CB had sufficient material for ancillary studies (up to 11 markers) and mutation testing.
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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 | 0.017 | 0.023 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.020 | 0.008 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.004 | 0.007 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.004 |
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".