Bisphosphonates in Glucocorticoid-Treated Patients With Duchenne Muscular Dystrophy
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Bisphosphonates are routinely used to treat osteoporosis in patients with Duchenne muscular dystrophy (DMD), a rare, severely debilitating neuromuscular disease. We sought to synthesize and grade benefits and harms evidence of bisphosphonates in glucocorticoid-treated patients with DMD. METHODS: In this systematic review (PROSPERO identifier: CRD42020157606), we searched MEDLINE, CINAHL, Embase, PsycINFO, Web of Science, and CENTRAL for articles published from inception up to and including March 31, 2023, reporting results in any language from any study type. Quality of evidence was assessed using the Grading of Recommendations, Assessment, Development, and Evaluations framework. RESULTS: We identified 19 publications involving 1,010 children and adults from 12 countries across all inhabited continents except South America. We found high-quality evidence that bisphosphonates significantly increase the areal lumbar spine bone mineral density (BMD) Z score in glucocorticoid-treated patients with DMD. The greatest improvements were recorded in controlled settings among patients treated with intravenous zoledronate. Evidence of benefits to fracture risks was inconclusive and/or of low quality, primarily due to lack of controlled data and small samples. Bisphosphonates were generally well-tolerated, although adverse events related to the first infusion (i.e., "acute phase reaction") were frequently reported. DISCUSSION: There is high-quality evidence supporting the use of bisphosphonates to increase the areal lumbar spine BMD Z score in patients with DMD and glucocorticoid-induced osteoporosis. Our synthesis and grading affirm current recommendations put forward in the 2018 DMD Clinical Care Considerations and should be helpful in raising awareness about anticipated benefits of bisphosphonates, prevailing unmet needs, and potential safety issues in their use.
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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 | 0.008 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".