Clinical Utility of Using Lumbar Spine Trabecular Bone Score to Adjust Fracture Probability: The Manitoba BMD Cohort
Bibliographic record
Abstract
Decreased lumbar spine trabecular bone score (TBS), a dual-energy X-ray absorptiometry (DXA)-derived image texture measurement, is a risk factor for major osteoporotic fracture (MOF) and hip fracture (HF) independent of 10-year fracture probability estimated using FRAX. We determined how often applying the TBS adjustment to fracture probability altered treatment qualification. Using a population-based registry containing all clinical DXA results for Manitoba, Canada, we identified 34,316 women with baseline spine and hip DXA, FRAX-based fracture probability measurements (computed with femoral neck bone mineral density), lumbar spine TBS, and minimum 5 years of observation (mean 8.7 years). Population-based health services data were used to identify incident non-traumatic MOF and HF in 3503 and 945 women, respectively. Baseline MOF and HF probabilities were estimated using FRAX before and after applying the TBS adjustment. Risk recategorization was assessed using net reclassification improvement (NRI) for individual FRAX-based intervention criteria and three national clinical practice guidelines (CPGs) (US National Osteoporosis Foundation, Osteoporosis Canada, and UK National Osteoporosis Guideline Group). Overall, proportions of women reclassified with the TBS adjustment to FRAX were small (less than 5%) with more than 90% of the reclassification occurring close to the intervention threshold. For women close to an intervention cut-off reclassification, rates ranged from 9.0% to 17.9% and were <1% otherwise. There was a small but significant improvement in overall NRI for all individual FRAX-based intervention criteria (range 0.007 to 0.018) and all three national CPGs (range 0.008 to 0.011). NRI was larger in women below age 65 years (up to 0.056 for hip fracture). In summary, a small but significant improvement in MOF and HF risk assessment was found by using lumbar spine TBS to adjust FRAX probability. An improvement in risk reclassification was observed for CPGs from three different countries, with almost all of the benefit found in individuals close to an intervention threshold. © 2017 American Society for Bone and Mineral Research. © 2017 American Society for Bone and Mineral Research.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".