Multiparametric magnetic resonance imaging for pre-treatment local staging of prostate cancer: A Cancer Care Ontario clinical practice guideline
Bibliographic record
Abstract
INTRODUCTION: The utility of T2-weighted magnetic resonance imaging (MRI) in the local staging of prostate cancer is controversial. Due to the success of multiparametric MRI in cancer localization, there is renewed interested in MRI (± functional sequences) for local staging. Guidance on pre-treatment local staging of prostate cancer by MRI was developed using systematic review methodology and expert consultation. METHODS: MEDLINE, EMBASE, Cochrane Database of Systematic Reviews, and other databases were searched to identify studies comparing: (1) MRI staging vs. radical prostatectomy staging on diagnostic accuracy outcomes; and (2) MRI staging vs. routine clinical staging on clinical and patient outcomes. Studies meeting inclusion criteria were synthesized by outcome and sensitivity/specificity analysis by tumour location was performed. Evidence quality of included studies was assessed and considered in recommendation formulation. RESULTS: The literature search identified 2510 citations; 62 studies were included. Analysis of MRI ≥1.5 T plus endorectal coil (ER) (± functional sequences) in the detection of extraprostatic extension or seminal vesicle invasion showed modest sensitivities (≥50%) and excellent specificities (>85%) among patients scheduled for radical prostatectomy. MRI upstaging was shown in 20/21 studies, with large variation in correctness (11-85%). Scarcity of clinical and patient outcomes among studies limited synthesis and evaluation. Quality assessment found non-trivial biases. CONCLUSIONS: Modest imaging performance was shown for MRI (1.5 T + ER and 3 T ± ER) ± functional sequences in regards to sensitivity. Limitations in study design, reporting of clinical and patient outcomes, and the heterogeneous use of MRI tempered the strength of the recommendations.
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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 | 0.018 | 0.038 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.005 |
| Bibliometrics | 0.009 | 0.012 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.008 | 0.004 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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".