A randomized trial comparing fluorocholine-PET/CT with conventional imaging in prostate cancer.
Bibliographic record
Abstract
2 Background: We conducted a randomised trial comparing 18Flourocholine-PET/CT (FCH) to Computed Tomography (abdomen and pelvis) plus 99mTc-Whole Body Bone Scan (Conventional Imaging [CIm]) to determine imaging performance in prostate cancer (PC). Methods: This prospective two-arm 1:1 randomised trial enrolled men with newly diagnosed or biochemically recurrent PC to first-line imaging (FLI) with either CIm or FCH. Participants without evidence of metastases proceeded to second-line imaging (SLI) using the alternative imaging strategy. The primary aim was to determine whether FCH was more effective as a FLI approach in changing management. Secondary endpoints included incremental utility of SLI and negative predictive value (NPV) based on progression-free survival (PFS). Australian New Zealand Clinical Trials Registry ACTRN12608000641392. Results: 108 men were enrolled; 44% were for staging of newly-diagnosed PC and median follow-up 43 months. Imaging impacted clinical management in 32.4% of men (95% CI=23.7-42.1%), mostly with FLI (n=30). High-impact management changes occurred in 27.8% (95% CI=16.5-41.6%) of FCH cases compared with 11.1% (95% CI=4.2-22.6%) in the CIm arm (p=0.032). The final management plan was derived using FCH in 98.1% (95% CI = 90.1-100%) of cases and 92.6% (95%CI = 82.1-97.9%) of CIm cases (p=0.242). FLI with FCH showed unequivocally N1 or M1 disease in 22.2% (95% CI = 12-35.6%), and 16.7% (95% CI = 7.9-29.3%; p= 0.531) of CIm cases. The overall NPV for stage TxN0M0 (from all imaging) was 26.3% (95% CI: 13.9 - 41.2%), with no significant difference between arms (p=0.9). For N1M0 cases, the NPV was 14.3% (95% CI: 7.1 - 35.7%). The identification of N1M0 by FCH resulted in a longer time to identification of progressive disease, with a median PFS of 32 months (95% CI=2-68months) compared with 3 months (95% CI=1-16 months) in the CIm N1M0 cohort (p=0.05). Conclusions: FCH-PET/CT identifies more high-clinical-impact lesions than CIm as first-line imaging. All imaging modalities were poor at predicting subsequent progressive disease. Isolated node-positive disease seen with FCH is associated with a longer time to - but similarly high rates of - recurrence, suggesting a lead-time bias. Clinical trial information: ACTRN12608000641392.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.012 | 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".