Androgen-targeted therapy in men with prostate cancer: evolving practice and future considerations
Bibliographic record
Abstract
BACKGROUND: Androgen deprivation therapy (ADT) is foundational in the management of advanced prostate cancer (PCa) and has benefitted from a recent explosion in scientific advances. These include approval of new therapies that suppress testosterone (T) levels or inactivate its function, improvements in diagnostic and assay technologies, identification of lower therapeutic targets for T, discovery of the relevance of germline genetic mutations and identification of the benefits of sequential and combination therapies. METHODS: This review discusses the clinical profiles of the most up-to-date options for ADT, best practices for managing patients with advanced PCa and future directions in therapy. RESULTS AND CONCLUSIONS: Modern assay technologies reveal that bilateral orchiectomy results in a serum T level of approximately 15 ng/dL as compared to the historical definition of castration of T < 50 ng/dL. Evidence shows that lowering T levels to <20 ng/dL improves patient survival and delays disease progression. Routine monitoring of T in addition to prostate-specific antigen throughout treatment is important to ensure continuing efficacy of T suppression. New drugs that inhibit androgen signaling in combination with traditional ADT suppress T activity to near zero and have significantly improved patient survival. When personalizing ADT regimens physicians should consider a number of factors including initiation and duration of ADT, monitoring of T levels and PSA, the possibility of switching monotherapies if a patient does not achieve adequate T suppression, and consideration of intermittent vs. continuous ADT according to patients' lifestyles, comorbidities, risk factors and tolerance to treatment.
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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 | 0.007 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".