Contributions of Clinical and Technical Factors to Longitudinal Change in Trabecular Bone Score and Bone Density: A Registry-Based Individual-Level Analysis
Bibliographic record
Abstract
Lumbar spine trabecular bone score (TBS), a gray-level texture measure derived from spine dual-energy X-ray absorptiometry (DXA) images, is a bone mineral density (BMD)-independent risk factor for fracture. An unresolved question is whether TBS is sufficiently responsive to change over time or in response to widely used osteoporosis therapy at the individual level to serve as a useful biomarker. Using the Manitoba DXA Registry, we identified 11,643 individuals age 40 years and older with two fan-beam DXA scans performed on the same instrument within 5 years (mean interval 3.2 years), of whom 6985 (60.0%) received antiresorptive osteoporosis medication (majority oral bisphosphonate) between the scans. We examined factors that were associated with a change in lumbar spine TBS, lumbar spine BMD, and total hip BMD exceeding the 95% least significant change (LSC). Change exceeding the LSC was identified in 23.0% (9.3% increase, 13.8% decrease) of lumbar spine TBS, 38.2% (22.1% increase, 16.1% decrease) lumbar spine BMD, and 42.5% (17.6% increase, 24.9% decrease) total hip BMD measurement pairs. From regression models, the variables most strongly associated with significant change in TBS (decreasing order) were tissue thickness change, acquisition mode change, weight change, and spine percent fat change. Consistent with the insensitivity of TBS to oral antiresorptive therapies, use of these agents showed very little effect on TBS change. In contrast, for both spine BMD change and total hip BMD change, osteoporosis medication use was the most significant variable, whereas tissue thickness change, acquisition mode change, and weight change had relatively weak effects. In summary, change in spine TBS using the present algorithm appears to be strongly affected by technical factors. This suggests a limited role, if any, for using TBS change in untreated individuals or for monitoring response to antiresorptive treatment in routine clinical practice with the current version of the TBS algorithm. © 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 | 0.006 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".