Are serial bone scans useful for the follow‐up of clinically localized, low to intermediate grade prostate cancer managed with watchful observation alone?
Bibliographic record
Abstract
OBJECTIVE: To assess the predictive value of serial bone scans as a surveillance tool for bone metastasis in men with clinically localized prostate cancer and managed with watchful observation. PATIENTS AND METHODS: A prospective single-arm study was conducted to assess the feasibility of a watchful observation protocol with selective delayed intervention for patients with clinically localized prostate cancer, i.e. T1b-T2bN0M0, a Gleason score of 15 ng/mL the patient underwent bone scintigraphy every year. RESULTS: In all, 244 eligible patients were enrolled into the study. With a median follow-up of 30 months, 449 bone scans were taken (150 at baseline and 299 in follow-up evaluations); all 299 follow-up scans were negative for bone metastasis. Hence, the true rate of positive follow-up bone scans was estimated to be 0-1.0% (95% confidence). In all, 171 patients had at least one follow-up bone scan; of these, the number (%) of patients who had 1, 2, 3, 4 and >or= 5 follow-up scans was 89 (52), 53 (31), 17 (10), eight (4.7) and four (2.3), respectively. The PSA levels (ng/mL) corresponding to all follow-up bone scans were: 214 scans at PSA < 10, 61 at 10-14.9, 18 at 15-19.9 and six at >or= 20 (range 20.2-24.9). The probability of a negative bone scan was estimated to be 88-100% (95% confidence interval) when a PSA threshold of 15 ng/mL was used. CONCLUSION: The probability of positive findings in serial bone scans in untreated, localized, low to intermediate grade prostate cancer was low when the follow-up PSA level remained < 15 ng/mL. Avoiding bone scans in this group of patients would translate into a significant cost saving and reduction in their psychological and physical burden. As for those with a follow-up PSA of> 15 ng/mL, the role of serial bone scintigraphy remains undefined, as a longer follow-up and a larger sample are needed.
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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 | 0.002 | 0.012 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".