Treatment Sequence Matters: Anabolic and Antiresorptive Therapy for Osteoporosis
Bibliographic record
Abstract
The effects of anabolic medications (teriparatide [TPTD] and parathyroid hormone [PTH]) differ in patients who have received recent treatment with potent antiresorptives. This perspective reviews studies evaluating bone density (BMD) and histomorphometric effects of treatment sequences beginning with TPTD/PTH followed by potent antiresorptives and those beginning with potent antiresorptives followed by switching to or adding TPTD. Effect of treatment sequence on spine BMD outcome is minor, with modest quantitative differences. However, when individuals established on potent bisphosphonates are switched to TPTD, hip BMD declines below baseline for at least the first 12 months after the switch to TPTD. This transient hip BMD loss is more prominent when the antiresorptive is denosumab; in this setting, hip BMD remains below baseline for almost a full 24 months. In a controlled comparison of those who switched from alendronate to TPTD versus those who added TPTD to ongoing alendronate, the effect on hip BMD was improved with combination therapy. Furthermore, hip strength improved with the addition of TPTD to ongoing alendronate, whereas it was neutral after switching from alendronate to TPTD, primarily due to the effect on cortical bone. Bone biopsy studies indicate that TPTD stimulates bone formation in patients who have not been treated previously as well as in patients on prior and ongoing bisphosphonates. Histomorphometric evidence suggests that use of alendronate with TPTD blocks the TPTD-induced increase in cortical porosity. When possible, we suggest anabolic therapy first, followed by potent antiresorptive therapy. The common practice of switching to TPTD only after patients have an inadequate response to antiresorptives (intercurrent fracture or inadequate BMD effect) is not the optimal utilization of anabolic treatment. In fact, this may result in transient loss of hip BMD and strength. In this setting, continuing a potent antiresorptive while starting TPTD might improve hip outcomes. © 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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".