Performance of FRAX in Men With Prostate Cancer: A Registry-Based Cohort Study
Bibliographic record
Abstract
The Fracture Risk Assessment Tool (FRAX®) was created to predict major osteoporotic fractures (MOF) and hip fractures in the general population. Whether FRAX accurately predicts fractures in men with prostate cancer is unknown. Our objective was to assess the performance of FRAX for predicting incident fractures in men with prostate cancer. Men from the Manitoba Bone Mineral Density (BMD) Registry (1996-2018) with prostate cancer diagnoses in the 3 years prior to dual-energy X-ray absorptiometry (DXA) were identified. FRAX scores with and without BMD were calculated. From population-based healthcare data we identified incident MOF, hip fracture, any osteoporotic fracture and death from the date of BMD testing to March 31, 2018. Cox regression was performed to estimate hazard ratios (HRs) with 95% confidence intervals (95% CIs) per standard deviation increase in FRAX score. Observed 10-year probability (estimated with competing risk of mortality) was compared with 10-year FRAX-predicted fracture probability to assess calibration. The study population included 684 men with prostate cancer (mean age 74.6 years) and 8608 men without prostate cancer (mean age 65.5 years). FRAX stratified risk for MOF (HR 1.91, 95% CI 1.48-2.45 with BMD; HR 1.96, 95% CI 1.43-2.69 without BMD) and hip fracture (HR 3.37, 95% CI 1.90-6.01 with BMD; HR 4.58, 95% CI 2.17-9.67 without BMD) in men with prostate cancer. There was no effect modification observed with prostate cancer status or current androgen deprivation therapy. Observed 10-year fracture probability in men with prostate cancer showed good agreement with FRAX with and without BMD included in the calculation (observed/predicted calibration ratios MOF 0.97, hip 1.00 with BMD; MOF 0.92, hip 0.93 with BMD). In conclusion, FRAX reliably predicts incident fractures in men with prostate cancer. © 2023 The Authors. Journal of Bone and Mineral Research published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research (ASBMR).
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".