Metastatic Prostate Cancer: An Update on Treatments and a Review of Patient Symptom Management
Bibliographic record
Abstract
BACKGROUND: Available treatment options have improved overall survival and contributed to delayed progression, but metastatic prostate cancer remains incurable. Treatment strategies are based on disease progression assessed by a combination of biochemical, radiographic, and symptomatic changes. OBJECTIVES: The aim of this article is to review metastatic prostate cancer, symptoms representing disease progression, disease treatments, and symptom management. METHODS: A PubMed® search restricted to English-language articles published since 1990 was conducted in August 2018 with combinations of the keywords "metastatic prostate cancer," "symptom assessment," and "treatment." Review articles were excluded, but their reference lists were reviewed to identify additional articles. Information from relevant articles published after August 2018 was added as appropriate based on author consensus. FINDINGS: Nursing professionals play vital roles in symptom recognition and reporting, identification of disease progression, patient education, and implementation of individualized treatment strategies.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".