Treatment Effects in the Prostate Including Those Associated With Traditional and Emerging Therapies
Bibliographic record
Abstract
Classic treatment options for prostate cancer consist of radical prostatectomy, antiandrogen (or hormonal) therapy, and radiation therapy. Hormonal and radiation therapy, in particular, have well known, often profound effects on the histologic appearance of benign prostate tissue and prostatic carcinoma. The tissue changes induced by these treatments have been comprehensively described in several sources. Novel therapies ranging from focal ablative treatments to highly targeted molecular therapies are beginning to emerge and pathologists will play a central role in documenting the effects of these treatments on normal and malignant prostate tissue. It is therefore important that pathologists have access to basic treatment information and a solid working knowledge of the morphologic changes induced by these therapies. This will ensure accurate interpretation and reporting of posttreatment prostate specimens. This review is based on a presentation given by Dr A. Evans at the International Society of Urological Pathology Companion Society Meeting (Hot Topics in Urological Pathology) at The United States Canadian Academy of Pathology Meeting in Washington DC on March 20, 2010. This review will cover the histopathologic features seen in benign prostate tissue and prostatic carcinoma seen following: hormonal therapy, radiation therapy, ablative therapies such as vascular-targeted photodynamic therapy, interstitial laser thermotherapy, and high-intensity focussed ultrasound. An emphasis is placed on these specific modalities as they are currently in use as primary, salvage, or investigational therapy in the treatment of prostate cancer.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".