Utility of FDG-PET/CT in Patients with Advanced Renal Cell Carcinoma with Osseous Metastases: Comparison with CT and <sup>99m</sup> Tc-MDP Bone Scan in a Prospective Clinical Trial
Bibliographic record
Abstract
Objective: Compare FDG-PET/CT, CT, and bone scan for detecting and monitoring bone metastases’ response in metastatic renal cell cancer (mRCC). Methods: Patients with mRCC prospectively underwent FDG-PET/CT, CT, and bone scans at baseline and after 8 weeks of therapy. Tumor visibility and metabolic activity were retrospectively recorded. Response was evaluated by PERCIST, RECIST, and MD Anderson bone criteria. Kaplan-Meier methodology estimated event-time distributions for PFS, OS, and time to symptomatic skeletal event (SSE). Log-rank test tested differences in event-time distributions between response at 8 weeks by response criteria. Results: Sixteen patients ( n = 30; 53%) were evaluable. Baseline FDG-PET/CT detected more osseous metastases ( n = 55) than CT ( n = 45) or bone scan ( n = 34). From baseline to 8 weeks, metabolic activity of lesions decreased >20%, while qualitative and quantitative CT and bone scan parameters were unchanged for most patients. Partial metabolic responders by PERCIST had longer PFS and OS ( n = 5, 20+ months) versus those with stable ( n = 9; PFS = 9.2 mos, OS = 8.7 mos) and progressive ( n = 2; PFS = 5.4 mos, OS = 12.1 mos) metabolic disease, p = 0.09 and 0.42, respectively. By RECIST, longer PFS and OS was seen for stable ( n = 12, PFS = 8.3 mos, OS = 17.7 mos) versus progressive ( n = 4; PFS = 3.7 mos, OS = 7.5 mos) disease, p = 0.16, 0.02, respectively. OS was not reached, but estimated ≥20 mos, for 4 patients with RECIST SD and PERCIST PMR, compared to OS of 17.7 mos for other patients with RECIST SD. Conclusions: FDG-PET/CT identified more bone metastases and greater numbers of quantitative and qualitative treatment responses in mRCC compared to CT and bone scan. FDG-PET/CT also may identify a sub-group of patients with better outcomes than predicted by standard imaging modalities.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".