Prevalence of Biopsy-Proven Clinically Significant Prostate Cancer in Patients with PI-RADS 3 on MRI and Factors Associated with It
Bibliographic record
Abstract
Background: To assess prevalence of prostate cancer and clinically significant prostate cancer in patients with PI-RADS 3 on bpMRI and factors associated with them. Methods: Patients suspicious for prostate cancer following serum Prostate Specific Antigen (PSA) screening, who had PI-RADS 3 on bpMRI, were included. All patients underwent systemic plus MRI targeted biopsy of prostate. Gleason score 3+3 was considered positive for prostate cancer but clinically non-significant one. Higher scores were pertained to as clinically significant prostate cancer. The relationship between patient age, PSA level, PSA density, number of core biopsies, and number of PI-RADS 3 lesions on bpMRI with presence of prostate cancer per se and presence of clinically significant prostate cancer in our patients is assessed. Results: 244 patients were enrolled. 101 patients had prostate cancer (41.4%). Out of these 101 patients, 34 (13.9% of total) had clinically significant prostate cancer. Among different factors, only PSA density was associated with both prostate cancer (OR=1.05, p=0.001) and clinically significant prostate cancer (OR=1.03, p=0.001). According to receiver operating characteristic curve analysis, best cut off value of PSA density which has highest association with clinically significant prostate cancer in PI-RADS 3 patients would be 0.36; with a sensitivity of 0.38 and specificity of 0.93. Conclusion: Considering PSA density with threshold of 0.36 for performing biopsy in patients with PI-RADS 3 on bpMRI might lower the rate of unnecessary biopsies.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".