The Triple‐Tracer strategy against Metastatic PrOstate cancer (3TMPO) study protocol
Bibliographic record
Abstract
Objective To determine the prevalence of intra‐patient inter‐metastatic heterogeneity based on positron emission tomography (PET)/computed tomography (CT) in patients with metastatic castration‐resistant prostate cancer (mCRPC) and to determine the prevalence of neuroendocrine disease in these patients and their eligibility for radioligand therapies (RLTs). Patients and Methods This multicentre observational prospective clinical study will include 100 patients with mCRPC from five Canadian academic centres. Patients with radiological or biochemical progression and harbouring at least three metastases by conventional imaging will be accrued. Intra‐patient inter‐metastatic heterogeneity will be determined with triple‐tracer imaging using fluorine‐18 fluorodeoxyglucose ( 18 F‐FDG), gallium‐68‐( 68 Ga)‐prostate‐specific membrane antigen (PSMA)‐617 and 68 Ga‐DOTATATE, which are a glucose analogue, a PSMA receptor ligand and a somatostatin receptor ligand, respectively. The 68 Ga‐PSMA‐617 and 18 F‐FDG PET/CT scans will be performed first. If at least one PSMA‐negative/FDG‐positive lesion is observed, an additional PET/CT scan with 68 Ga‐DOTATATE will be performed. The tracer uptake of individual lesions will be assessed for each PET tracer and patients with lesions presenting discordant uptake profiles will be considered as having inter‐metastatic heterogeneous disease and may be offered a biopsy. Expected Results The proposed triple‐tracer approach will allow whole‐body mCRPC characterisation, investigating the inter‐metastatic heterogeneity in order to better understand the phenotypic plasticity of prostate cancer, including the neuroendocrine transdifferentiation that occurs during mCRPC progression. Based on 68 Ga‐PSMA‐617 or 68 Ga‐DOTATATE PET positivity, the potential eligibility of patients for PSMA and DOTATATE‐based RLT will be assessed. Non‐invasive whole‐body determination of mCRPC heterogeneity and transdifferentiation is highly innovative and might establish the basis for new therapeutic strategies. Comparison of molecular imaging findings with biopsies will also link metastasis biology to radiomic features. Conclusion This study will add novel, biologically relevant dimensions to molecular imaging: the non‐invasive detection of inter‐metastatic heterogeneity and transdifferentiation to neuroendocrine prostate cancer by using a multi‐tracer PET/CT strategy to further personalise the care of patients with mCRPC.
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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 | 0.007 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.017 | 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".