Management of men with previous negative prostate biopsy
Bibliographic record
Abstract
PURPOSE OF REVIEW: Up to 70% of prostate biopsies are negative in men with suspected prostate cancer. Because of inherent limitations in biopsy strategies, a significant proportion of cancers are missed on initial biopsy. Following negative biopsy, men frequently exhibit persistently elevated prostate-specific antigen - raising concerns for missed diagnosis. We highlight the recent updates in the management of negative prostate biopsy. RECENT FINDINGS: Advances in noninvasive diagnostics are available and assist clinicians in further substratifying risk of prostate cancer. Despite limited data, urinary prostate cancer antigen 3 and transmembrane protease serine 2 appear to have a promising predictive value for patients suspected of prostate cancer. The advent of multiparametricMRI allows the visualization of intermediate and high-grade prostate cancer, particularly in the troublesome anterior prostate. This modality may further provide the potential for magnetic resonance-guided targeted biopsies. Current data suggest that in the presence of suspicious radiological findings, magnetic resonance-guided biopsies have superior sensitivity profiles compared with traditional rebiopsy approaches. In the absence of multiparametricMRI or suspicious findings, traditional saturation biopsies are sufficient. SUMMARY: The management of negative biopsies is evolving rapidly with emerging diagnostics to stratify risk of prostate cancer in men with previous negative biopsies. An increasing body of information supports the use of magnetic resonance-guided biopsies.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".