Prostate Cancer Liver Metastasis: An Ominous Metastatic Site in Need of Distinct Management Strategies
Bibliographic record
Abstract
Prostate cancer liver metastasis (PCLM), seen in upwards of 25% of metastatic castration-resistant PC (mCRPC) patients, is the most lethal site of mCRPC with a median overall survival of 10-14 months. Despite its ominous prognosis and anticipated rise in incidence due to longer survival with contemporary therapy, PCLM is understudied. This review aims to summarize the existing literature regarding the risk factors associated with the development of PCLM, and to identify areas warranting further research. A literature search was conducted through Ovid MEDLINE from 2000 to March 2023. Relevant subject headings and text words were used to capture the following concepts: "Prostatic Neoplasms", "Liver Neoplasms", and "Neoplasm Metastasis". Citation searching identified additional manuscripts. Forty-one studies were retained for detailed analysis. The clinical risk factors for visceral/liver metastasis included <70 years, ≥T3 tumor, N1 nodal stage, de novo metastasis, PSA >20 ng/mL, and a Gleason score >8. Additional risk factors comprised elevated serum AST, LDH or ALP, decreased Hb, genetic markers like RB1 and PTEN loss, PIK3CB and MYC amplification, as well as numerous PC treatments either acting directly or indirectly through inducing liver injury. Further research regarding predictive factors, early detection strategies, and targeted therapies for PCLM are critical for improving patient outcomes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 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".