Evidence-based guideline recommendations on multiparametric magnetic resonance imaging in the diagnosis of prostate cancer: A Cancer Care Ontario clinical practice guideline
Bibliographic record
Abstract
This clinical guideline focuses on: 1) the use of multiparametric magnetic resonance imaging (mpMRI) in diagnosing clinically significant prostate cancer (CSPC) in patients with an elevated risk of CSPC and who are biopsy-naïve; and 2) the use of mpMRI in diagnosing CSPC in patients with a persistently elevated risk of having CSPC and who have a negative transrectal ultrasound (TRUS)-guided systematic biopsy.The methods of the Practice Guideline Development Cycle were used. MEDLINE, EMBASE, the Cochrane Library (1997‒April 2014), main guideline websites, and relevant annual meeting abstracts (2011‒2014) were searched. Internal and external reviews were conducted.The two main recommendations are:Recommendation 1: In patients with an elevated risk of CSPC (according to prostate-specific antigen [PSA] levels and/or nomograms) who are biopsy-naïve: mpMRI followed by targeted biopsy (biopsy directed at cancer-suspicious foci detected with mpMRI) should not be considered the standard of care; data from future research studies are essential and should receive high-impact trial funding to determine the value of mpMRI in this clinical context.Recommendation 2:In patients who had a prior negative TRUS-guided systematic biopsy and demonstrate an increasing risk of having CSPC since prior biopsy (e.g., continued rise in PSA and/or change in findings from digital rectal examination): mpMRI followed by targeted biopsy may be considered to help in detecting more CSPC patients compared with repeated TRUS-guided systematic biopsy.
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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 | 0.021 | 0.084 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.008 |
| Bibliometrics | 0.010 | 0.012 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.010 | 0.004 |
| Research integrity | 0.014 | 0.009 |
| Insufficient payload (model declined to judge) | 0.012 | 0.006 |
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".