Treatment Related Neuroendocrine Prostatic Carcinoma: Review and Update
Bibliographic record
Abstract
Treatment-related neuroendocrine carcinoma of the prostate gland is stated to be a distinctive category of carcinoma of the prostate gland which tends to ensue intensive suppression of the androgen receptor by next-generation therapeutic inhibition of androgen receptor signalling. The biological processes which set in motion the series of events emanating in transformation of adenocarcinoma to neuroendocrine carcinoma has been iterated to include genomic (loss of tumour suppressors TP53 and RB1, amplification of oncogenes N-MYC and Aurora Kinase A, dysregulation of transcription factors SOX2, achaete-scute-homolog 1, and others) as well as epigenomic (DNA methylation, EZH2 overexpression, and others). Pathology examination diagnosis of specimens of the tumour has been iterated to be the key to effective treatment for this disease, and this is aided by localizing metastatic lesions for biopsy utilising radioligand imaging in the appropriate clinical context. As the understanding of biology of the tumour has evolved, there has been increased morphological examination recognition and characterization of tumour phenotypes which are present within this advanced post-treatment setting. New and promising biomarkers (delta-like ligand 3 and others) have been discovered, which has opened up novel treatment avenues including immunotherapy and antibody-drug conjugates for this lethal disease with currently limited treatment options. It is important for clinicians and patients all over the world to appreciate that treatment related neuroendocrine carcinoma of the prostate gland generally has tended to portend an aggressive clinical and biological behaviour that has tended to be associated with poor prognosis and early death of individuals afflicted by the tumour. There is the need for clinicians and research workers to undertake research work that would identify new treatment options that would help improve the outcome of the tumour by destroying the tumour cells effectively.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".