Call for a European programme in external quality assurance for bone marrow immunohistochemistry; report of a European Bone Marrow Working Group pilot study
Bibliographic record
Abstract
BACKGROUND AND AIMS: In diagnostic immunohistochemistry (IHC), daily quality control/quality assurance measures (QC/QA) and participation in external quality assurance programmes (EQA) are important in ensuring good laboratory practice and patient care. Bone marrow trephine biopsies (BMTB) have been generally excluded from EQA programmes for diagnostic IHC due to a lack of standards for tissue processing. The European Bone Marrow Working Group (EBMWG) has set up an EBMWG IHC Committee with the task of exploring the plausibility of an EQA programme for BMTB IHC in Europe. METHODS: 28 laboratories participated in a web-based anonymous survey; 19 laboratories submitted a total of 109 slides stained for CD34, CD117, CD20, CD3, Ki-67 and a megakaryocyte marker of choice. RESULTS: Eight different fixatives and nine different decalcification methods were used. While 93% of participants believed that they produced excellent results in BMTB IHC, only 4/19 (21%) laboratories did not have any poor results. CD117 and Ki-67, with 53% and 50% poor results, respectively, were the most problematic immunostains, while CD20 was the least problematic, with only 11% poor results. CONCLUSIONS: The EBMWG IHC Committee calls for a reduction in the tissue processing methods for BMTB and establishment of an EQA programme for BMTB IHC to help diagnostic IHC laboratories calibrate their tests according to expert recommendations. This is especially necessary in the light of recent introduction of predictive IHC tests in BMTB.
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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 | 0.078 | 0.047 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.005 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".