FDG-PET/CT for pre-operative staging and prognostic stratification of patients with high-grade prostate cancer at biopsy
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Bibliographic record
Abstract
BACKGROUND: The role of (18)F-fluorodeoxyglucose positron emission tomography/computed tomography (FDG-PET/CT) in prostate cancer (PCa) has not been well defined yet. Because high-grade PCa tends to exhibit increased glycolytic rate, FDG-PET/CT could be useful in this setting. The aim of this study was to assess the value of FDG-PET/CT for pre-operative staging and prognostic stratification of patients with high-grade PCa at biopsy. METHODS: Fifty-four patients with a Gleason sum≥8 PCa at biopsy underwent FDG-PET/CT as part of the staging workup. Thirty-nine patients underwent radical prostatectomy (RP) and pelvic lymph node (LN) dissection, 2 underwent LN dissection only, and 13 underwent non-surgical treatments. FDG-PET/CT findings from clinical reports, blinded reading and quantitative analysis were correlated with clinico-pathological characteristics at RP. RESULTS: Suspicious foci of increased FDG uptake were found in the prostate, LNs and bones in 44, 13 and 6% of patients, respectively. Higher clinical stage, post-RP Gleason sum and pattern, and percentage of cancer involvement within the prostate were significantly associated with the presence of intraprostatic FDG uptake (IPFU) (P<0.05 in all cases). Patients without IPFU who underwent RP were downgraded to Gleason≤7 in 84.6% of cases, as compared to 30.8% when IPFU was reported (P=0.003). Qualitative and quantitative IPFU were significantly positively correlated with post-RP Gleason pattern and sum, and pathological T stage. Absence and presence of IPFU were associated with a median 5-year cancer-free survival probability of 70.2 and 26.9% (P=0.0097), respectively, using the CAPRA-S prognostic tool. CONCLUSION: These results suggest that, among patients with a high-grade PCa at biopsy, FDG-PET/CT could improve pre-treatment prognostic stratification by predicting primary PCa pathological grade and survival probability following RP.
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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) | 0.000 | 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 it