An introduction to the <scp>WHO</scp> 5th edition 2022 classification of testicular tumours
Bibliographic record
Abstract
The 5th edition of the World Health Organisation Blue Book was published recently and includes a comprehensive update on testicular tumours. This builds upon the work of the 4th edition, retaining its structure and main nomenclature, including the use of the term 'germ cell neoplasia in situ' (GCNIS) for the pre-invasive lesion of most germ cell tumours and division from those not derived from GCNIS. While there have been important developments in understanding the molecular underpinnings of testicular cancer, this updated classification paradigm and approach remains rooted in morphology. Nomenclature changes include replacement of the term 'primitive neuroectodermal tumour' by 'embryonic neuroectodermal tumour' based on the non-specificity of the former term and to separate these tumours clearly from Ewing sarcoma. Seminoma is placed in a germinoma family of tumours emphasising relation to those tumours at other sites. Criteria for the diagnosis of 'teratoma with somatic transformation' have been modified to not include variable field size assessments. The word 'carcinoid' has been changed to 'neuroendocrine tumour', with most examples in the testis now classified as 'prepubertal type testicular neuroendocrine tumour'. For sex cord-stromal tumours, the use of mitotic counts per high-power field has been changed to per mm2 for malignancy assessments, and the new entities, 'signet ring stromal tumour' and 'myoid gonadal stromal tumour', are defined. Well-differentiated papillary mesothelial tumour has now been defined as tumour type with a favourable prognosis. Sertoliform cystadenoma has been removed as an entity from testicular adnexal tumours and placed with Sertoli cell tumours.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.064 | 0.041 |
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".