Fracture prediction and calibration of a Canadian FRAX® tool: A population-based report from CaMos
Bibliographic record
Abstract
Summary: A new Canadian WHO fracture risk assessment ( FRAX® ) tool to predict 10-year fracture probability was compared with observed 10-year fracture outcomes in a large Canadian population-based study ( CaMos ). The Canadian FRAX tool showed good calibration and discrimination for both hip and major osteoporotic fractures. Introduction: The purpose of this study was to validate a new Canadian WHO fracture risk assessment ( FRAX® ) tool in a prospective, population-based cohort, the Canadian Multicentre Osteoporosis Study ( CaMos ). Methods: FRAX tool calibrated to the Canadian population was developed by the WHO Collaborating Centre for Metabolic Bone Diseases using national hip fracture and mortality data. Ten-year FRAX probabilities with and without bone mineral density ( BMD ) were derived for CaMos women ( N = 4,778 ) and men ( N = 1,919 ) and compared with observed fracture outcomes to 10 years ( Kaplan–Meier method ). Cox proportional hazard models were used to investigate the contribution of individual FRAX variables. Results: Mean overall 10-year FRAX probability with BMD for major osteoporotic fractures was not significantly different from the observed value in men [predicted 5.4% vs. observed 6.4% ( 95%CI 5.2–7.5% )] and only slightly lower in women [predicted 10.8% vs. observed 12.0% ( 95%CI 11.0–12.9% )]. FRAX was well calibrated for hip fracture assessment in women [predicted 2.7% vs. observed 2.7% ( 95%CI 2.2–3.2% )] but underestimated risk in men [predicted 1.3% vs. observed 2.4% ( 95%CI 1.7–3.1% )]. FRAX with BMD showed better fracture discrimination than FRAX without BMD or BMD alone. Age, body mass index, prior fragility fracture and femoral neck BMD were significant independent predictors of major osteoporotic fractures; sex, age, prior fragility fracture and femoral neck BMD were significant independent predictors of hip fractures. Conclusion: The Canadian FRAX tool provides predictions consistent with observed fracture rates in Canadian women and men, thereby providing a valuable tool for Canadian clinicians assessing patients at risk of fracture.
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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 | 0.006 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 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".