Bone turnover markers for assessment of anti-resorptive effect in clinical practice: A good idea meets the problem of measurement uncertainty
Bibliographic record
Abstract
OBJECTIVES: Bone turnover markers (BTM) are measures for understanding the effect of anti-resorptives upon osteoclast activity. Post-hoc trial data suggests reduction in BTM of 40% may represent a target for defining appropriate response to therapy. We modeled clinical application of this target threshold in an individual patient setting where assay measurement uncertainty and biological variation are included. DESIGN: Using serum C-telo-peptide (ß-CTX), we constructed hypothetical scenarios of ß-CTX measurement pre and post bisphosphonate therapy. Using typical ß-CTX assay characteristics (analytical coefficient of variation, CV 5.0%) and published intra-individual ß-CTX data for post-menopausal women (CV 18.0%), we calculated the post-therapy ß-CTX that must be seen on single repeat measure for 95% confidence that the observed result was ≥40% below baseline. Sensitivity analyses considered greater and lesser variations in the combined sources of variation. RESULTS: The one-tailed 95% reference change value for any detectable therapeutic decrease in ß-CTX was 22%. However, to have 95% confidence of having achieved a reduction ≥40%, an observed ß-CTX decrease of ≥56% is required. Larger decreases are needed for scenarios of greater analytical or intra-individual variation. CONCLUSIONS: Although population data suggest a ß-CTX decrease of 40% is commensurate with adequate therapeutic response to anti-resorptives, application to an individual patient where measurement and natural variation are present is problematic. ß-CTX decreases much >40% are required to be confident of having achieved the optimal treatment response. It is uncertain whether this is a legitimate change to be expected in all individual patients and therefore clinical application of this threshold is uncertain.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.023 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".