Integration of bone scan (BS) and computerized tomography (CT) findings as an endpoint to assess bone metastasis in metastatic castration-resistant prostate cancer (mCRPC).
Bibliographic record
Abstract
191 Background: Progression of bone metastasis in mCRPC is assessed solely by BS findings and correlates modestly with overall survival (OS). Given the lack of reliability of BS findings and the ready availability of routinely performed CT scans, which commonly identify bone metastases, we aimed to better assess progression in bone by integrating BS and CT findings and to explore their association with OS. Methods: Data were obtained from patients treated at the University of Utah receiving docetaxel-based chemotherapy (D) or post-docetaxel therapy with orteronel (O). Patients with both baseline and on-therapy CT and BS within 90 days were eligible for analysis. CT and BS underwent central radiology review for bone lesions by a single radiologist. Progressive disease (PD) was defined as ≥ 1 new lesion. Survival was measured from start of therapy. Cox proportional hazards regression was used to explore potential prognosticators of overall survival (OS). Statistical significance was defined as 2-sided p < 0.05. Therapy was a stratification factor. Results: Twenty-eight patients were evaluable including 18 patients receiving D, and 10 receiving O post-docetaxel. The mean age of these patients was 71.4 years and median (95% CI) overall survival was 18.4 (9.7-35.4) months. Four patients had PD on both BS and CT, while 2 (7%) had PD on CT but not BS and 3 had PD on BS but not CT. Patients with PD on BS or CT had worse OS (HR = 2.68, 95% CI = 1.04-6.90, p = 0.041) than those with no PD on either CT or BS. Looking at individual lesions, 4 (14%) patients had new lesions identified on CT which was not observed using BS, and they were associated with worse OS (HR = 3.72, 1.01-13.66, p = 0.048). Conversely, no significant difference in OS was observed for 4 patients with lesions identified on BS which were not observed using CT (HR = 2.67, 0.58-12.32, p = 0.21). Conclusions: This hypothesis-generating study suggests that CT can complement and enhance the ability of BS to capture PD and predict OS. Integration of BS findings using Prostate Cancer Working Group (PCWG)-3 guidelines to define PD and CT bone findings should be investigated in a larger study as an intermediate endpoint.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".