PNR-33MOLECULAR RE-EVALUATION OF INSTITUTIONALLY DIAGNOSED CNS-PNETS: CLINICAL CONSEQUENCES OF CONFINED DIAGNOSTIC GROUPS
Bibliographic record
Abstract
Primitive neuroectodermal tumors of the central nervous system (CNS-PNETs) are highly aggressive, poorly differentiated embryonal tumors occurring predominantly in young children but also affecting adolescents and adults. Recently, by utilizing DNA methylation, it has been demonstrated that a large proportion of institutionally-diagnosed CNS-PNETs display molecular profiles indistinguishable from those of various other well defined CNS tumor entities, including high grade gliomas, AT/RTs, and ependymomas. Among institutionally-diagnosed CNS-PNETs that do not align with other tumor types, four distinct molecular entities were defined, each associated with a recurrent genetic alteration and distinct histopathological and clinical features: CNS-NB-FOXR2, CNS-HGNET-BCOR, CNS-HGNET-MN1, and CNS-EFT-CIC (Sturm et al., 2016). Interestingly, after identifying these new entities, additional cases aligning with these profiles were found among patients with historic diagnoses other than CNS-PNETs. In order to develop appropriate treatment strategies for these new molecular entities, it is essential to know the clinical response and outcome from previously applied treatment strategies. Conversely, it is valuable to analyze the outcome of patients with tumors treated as per CNS-PNET strategies that were reclassified into other known entities and compare these data to the clinical and outcome data from the group they were re-classified to. Within a broad international collaborative approach, clinical, molecular and histopathological data are collected for patients with historic diagnoses of CNS-PNET or with tumors not diagnosed as CNS-PNET but that fit the molecular profile of one of the newly defined molecular entities. Clinical and outcome data will be presented for patients with matched molecular profiles.
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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 | 0.002 | 0.060 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".